1. Biochemistry and Chemical Biology
  2. Structural Biology and Molecular Biophysics
Download icon

Structural basis for the activation of PLC-γ isozymes by phosphorylation and cancer-associated mutations

  1. Nicole Hajicek
  2. Nicholas C Keith
  3. Edhriz Siraliev-Perez
  4. Brenda RS Temple
  5. Weigang Huang
  6. Qisheng Zhang
  7. T Kendall Harden
  8. John Sondek  Is a corresponding author
  1. The University of North Carolina at Chapel Hill, United States
Research Article
  • Cited 1
  • Views 1,263
  • Annotations
Cite this article as: eLife 2019;8:e51700 doi: 10.7554/eLife.51700

Abstract

Direct activation of the human phospholipase C-γ isozymes (PLC-γ1, -γ2) by tyrosine phosphorylation is fundamental to the control of diverse biological processes, including chemotaxis, platelet aggregation, and adaptive immunity. In turn, aberrant activation of PLC-γ1 and PLC-γ2 is implicated in inflammation, autoimmunity, and cancer. Although structures of isolated domains from PLC-γ isozymes are available, these structures are insufficient to define how release of basal autoinhibition is coupled to phosphorylation-dependent enzyme activation. Here, we describe the first high-resolution structure of a full-length PLC-γ isozyme and use it to underpin a detailed model of their membrane-dependent regulation. Notably, an interlinked set of regulatory domains integrates basal autoinhibition, tyrosine kinase engagement, and additional scaffolding functions with the phosphorylation-dependent, allosteric control of phospholipase activation. The model also explains why mutant forms of the PLC-γ isozymes found in several cancers have a wide spectrum of activities, and highlights how these activities are tuned during disease.

eLife digest

Many enzymes are poised to receive signals from the surrounding environment and translate them into responses inside the cell. One such enzyme is phospholipase C-γ1 (PLC-γ1), which controls how cells grow, divide and migrate.

When activating signals are absent, PLC-γ1 usually inhibits its own activity, a mechanism called autoinhibition. This prevents the enzyme from binding to its targets, which are fat molecules known as lipids. When activating signals are present, a phosphate group serves as a ‘chemical tag’ and is added onto PLC-γ1, allowing the enzyme to bind to lipids.

Failure in the regulation of PLC-γ1 or other closely related enzymes may lead to conditions such as cancer, arthritis and Alzheimer’s disease. However, it remains unclear how autoinhibition suppresses the activity of the enzyme, and how it is stopped by the addition of the phosphate group.

Here, Hajicek et al. determine in great detail the three-dimensional structure of the autoinhibited form of the enzyme using a method known as X-ray crystallography. This reveals that PLC-γ1 has two major lobes: one contains the active site that modifies lipids, and the other sits on top of the active site to prevent lipids from reaching it. The findings suggest that when the phosphate group attaches to PLC-γ1, it triggers a large shape change that shifts the second lobe away from the active site to allow lipids to bind.

The three-dimensional structure also helps to understand how mutations identified in certain cancers may activate PLC-γ1. In particular, these mutations disrupt the interactions between elements that usually hold the two lobes together, causing the enzyme to activate more easily.

The work by Hajicek et al. provides a framework to understand how cells control PLC-γ1. It is a first step toward designing new drugs that alter the activity of this enzyme, which may ultimately be useful to treat cancer and other diseases.

Introduction

The 13 phospholipase C (PLC) isozymes expressed in humans preferentially hydrolyze the membrane phospholipid phosphatidylinositol 4,5-bisphosphate (PIP2) to generate the second messengers diacylglycerol and inositol 1,4,5-trisphosphate (IP3) (Harden and Sondek, 2006; Kadamur and Ross, 2013). Diacylglycerol is retained within membranes where it recruits and activates numerous proteins including conventional isoforms of protein kinase C. In contrast, IP3 diffuses throughout the cytosol where it binds to IP3 receptors embedded in endoplasmic reticulum leading to mobilization of sequestered calcium. PLC-mediated depletion of PIP2 also modulates the activities of several ion channels and proteins with phosphoinositide-binding domains. Thus, the PLCs coordinate fluctuations in PIP2 levels and the bifurcating signaling pathways emanating from PIP2 hydrolysis to regulate numerous cellular processes, including fertilization and embryogenesis, cell proliferation and differentiation, as well as various types of cell migration (Asokan et al., 2014; de Gorter et al., 2007; Jones et al., 2005; Mouneimne et al., 2004).

The two PLC-γ isozymes, PLC-γ1 and PLC-γ2, are unique among the PLCs in that they are directly activated by tyrosine phosphorylation. PLC-γ1 and PLC-γ2 are phosphorylated on equivalent sites, Tyr783 and Tyr759, respectively, and this phosphorylation is typically required to stimulate phospholipase activity. Several classes of tyrosine kinases phosphorylate and activate the PLC-γ isozymes. These include a large number of receptor tyrosine kinases (RTKs) including Trk receptors (Minichiello et al., 2002; Vetter et al., 1991) and many growth factor receptors such as epidermal growth factor receptor (EGFR) (Kim et al., 1991; Nishibe et al., 1990; Peters et al., 1992; Takahashi et al., 2001; Wahl et al., 1989). A second large group is soluble tyrosine kinases coupled to immune receptors and includes members of the Src, Syk, and Tec families (Law et al., 1996; Nakanishi et al., 1993; Schaeffer et al., 1999). In this way, the PLC-γ isozymes are poised to transduce signals initiated by a wide variety of extracellular stimuli.

The regulated, phosphorylation-dependent activation of PLC-γ1 and -γ2 controls numerous aspects of biology including proper development of the vascular, neuronal, and immune systems during embryonic development, adaptive immune responses, neuronal transmission, bone homeostasis, chemotaxis, and platelet aggregation (Yang et al., 2012). The PLC-γ isozymes have also recently emerged as drivers of several human diseases (Koss et al., 2014). Notably, genome-wide sequencing studies have demonstrated that PLC-γ1 and PLC-γ2 are frequently and recurrently mutated in several leukemias and lymphomas. In fact, PLC-γ1 is the most frequently (~40%) mutated gene in adult T cell leukemia/lymphoma, where mutant forms of the isozyme are presumed to drive oncogenesis through enhanced phospholipase activity coupled to elevated NFAT- and NF-κB-dependent transcription (Kataoka et al., 2015; Vaqué et al., 2014). Moreover, activating mutations in PLC-γ2 arise with high frequency (~30%) in patients with B cell leukemias treated with ibrutinib (Woyach et al., 2014), a covalent inhibitor of Bruton’s tyrosine kinase (BTK). PLC-γ2 is a major BTK substrate and mutations in PLC-γ2 likely function as escape mutations, reactivating pathways controlling cell survival and proliferation that are usually rendered quiescent by ibrutinib treatment. Mutated, and presumably active, forms of the PLC-γ isozymes are also found in patients with angiosarcomas (Behjati et al., 2014), and several disorders associated with dysregulated immune responses (Ombrello et al., 2012; Zhou et al., 2012), inflammatory bowel disease (de Lange et al., 2017), and familial steroid-sensitive nephrotic syndrome (Gbadegesin et al., 2015; Parker et al., 2019). A naturally occurring variant of PLC-γ2 that is moderately active is strongly associated with protection from late-onset Alzheimer’s disease (Magno et al., 2019; Sims et al., 2017) and highlights the notion that aberrant PLC activity can be either deleterious or beneficial depending on the context. However, for the vast majority of mutant forms of PLC-γ1 and PLC-γ2, an increase in lipase activity has not been demonstrated directly.

While the PLC-γ isozymes control essential aspects of both normal and disease-associated cellular processes, the molecular mechanisms controlling these enzymes remain elusive. Broadly, phosphorylation-dependent activation of PLC-γ1 and PLC-γ2 is controlled by an array of regulatory domains unique to these isozymes. In particular, the regulatory array harbors the obligatory sites of tyrosine phosphorylation (Gresset et al., 2010; Kim et al., 1991; Nishibe et al., 1990), and also includes an SH2 domain (nSH2) required for tyrosine kinase binding (Bae et al., 2009). The array also mediates basal autoinhibition of phospholipase activity, since removal or mutation of a second SH2 domain (cSH2) within the array results in robust and constitutive activation of PLC-γ isozymes in vitro and in cells (Gresset et al., 2010; Hajicek et al., 2013). The regulatory array is completed by a split PH (sPH) domain and an SH3 domain, which modulate PLC activity by scaffolding numerous signaling and adaptor proteins (Sherman et al., 2016; Walliser et al., 2008).

Although these general aspects of the regulation of PLC-γ1 and PLC-γ2 are well-documented, several fundamental questions remain unresolved. For example, the other half of the autoinhibitory interface formed by the cSH2 domain has not been identified, and how this domain enforces autoinhibition of phospholipase activity is unknown. Possibilities include physical occlusion of the lipase active site, steric hindrance that prevents the enzyme from engaging membranes, or a combination of both as is observed for the PLC-β isozymes (Hicks et al., 2008). Although the cSH2 domain is presumed to be the primary arbiter of autoinhibition, several reports have also implicated the sPH domain in maintaining an autoinhibited state (Everett et al., 2011; Gresset et al., 2010). How this domain might contribute to autoinhibition is unknown.

Similarly unclear is how autoinhibition is relieved by tyrosine phosphorylation. Phosphorylated Tyr783 in PLC-γ1 binds with nanomolar affinity to the cSH2 domain, and this engagement presumably couples a large, but ill-defined conformational rearrangement within the array to activation (Gresset et al., 2010; Hajicek et al., 2013; Poulin et al., 2005). However, even these few mechanistic details are under debate since an alternative model posits engagement of RTKs by the cSH2 domain as an initial step required for activation (Huang et al., 2016).

The paucity of mechanistic understanding of the activation of the PLC-γ isozymes is largely attributable to a lack of structural information. While structures of isolated portions of the regulatory array of PLC-γ1 are available, these structures provide an incomplete and sometimes erroneous context for defining how the array integrates the functions of basal autoinhibition and phosphorylation-dependent activation. There are no structures of full-length PLC-γ isozymes.

Here, we describe the 2.5 Å-resolution crystal structure of essentially full-length PLC-γ1. The structure highlights a regulatory array exquisitely positioned to prevent membrane engagement of the catalytic core while simultaneously arranged to scaffold tyrosine kinases and additional regulatory proteins into a signaling nexus. Kinases have unfettered access to the nSH2 domain of the regulatory array and will dock here initially. In contrast, the phosphotyrosine binding pocket within the cSH2 domain is buried through interactions with the catalytic core. Docked kinases are well positioned to phosphorylate Tyr783 located within a nearby solvent-exposed loop and phosphorylated Tyr783 (pTyr783) is expected to bind the cSH2 domain to disrupt its interaction with the catalytic core. This disruption is predicted to favor a substantial rearrangement of PLC-γ1 required for productive membrane engagement and hydrolysis of PIP2. The structure also explains how cancer-associated substitutions disrupt autoinhibition to elevate basal PLC-γ1 activity and contribute to supra-activation of the isozyme in the context of receptor overexpression. The combined effects of substitution and tyrosine phosphorylation suggest that cellular context, for example overexpression of EGFR found in many cancers, will be especially important for understanding diseases modulated by the PLC-γ isozymes.

Results

Structure of full-length PLC-γ1

In addition to the aforementioned array of regulatory domains, the PLC-γ isozymes also possess a set of core domains common to most other isoforms of PLC: an N-terminal PH domain, two pairs of EF hands, a catalytic TIM barrel, and a C2 domain. The regulatory array bisects the TIM barrel, subdividing this domain into the X- and Y-boxes (Figure 1a, Figure 1—figure supplement 1). To facilitate crystallization, several regions predicted to be disordered were removed from the construct used for structure determination. In particular, 20 and 75 residues were deleted from the N- and C-terminus, respectively. In addition, an internal loop of 25 residues connecting the cSH2 and SH3 domains was removed and replaced with a flexible linker; we refer to this internal deletion as Δ25 (Figure 1—figure supplement 1, also see Materials and methods). The crystallized construct therefore contains residues 21–765 and 791–1215 of PLC-γ1.

Figure 1 with 4 supplements see all
Crystal structure of autoinhibited PLC-γ1.

(a) Domain architecture of PLC-γ1 drawn to scale. (b) 2.5 Å resolution structure of PLC-γ1, domains are colored as in (a); TIM barrel and C2 domain are depicted as surfaces to highlight interactions with regulatory domains. The calcium cofactor (orange sphere) marks the active site and dashed lines indicate regions not built due to the absence of observable electron density. Borders of the Δ25 deletion (residues 766–790) used to facilitate crystallization are indicated with spheres. The hydrophobic ridge of the TIM barrel, which interacts with lipid membranes to facilitate catalysis, is occluded by the sPH domain. This arrangement of the sPH domain is supported by contacts with the cSH2 domain and further reinforced by a ‘brace’ formed by the C-terminal extension of the SH3 domain. (c–d) Structural details between the regulatory and core domains of PLC-γ1. (e) Expanded view of the SH3 domain. (f) Structure of the isolated cSH2 domain of PLC-γ1 bound to a peptide (spheres) encompassing phosphorylated Tyr783 (red) of PLC-γ1. Orientation is approximately the same as in panels (b) and (d). For panels (c–f) interfacial residues are numbered, dashed lines are hydrogen bonds, and residues mutated in Figure 3 are underlined. (g) Schematic emphasizing large conformational change that is proposed to occur before PLC-γ1 can access membrane-resident PIP2.

The cSH2/SH3 domain loop contains Tyr783, which is required for phosphorylation-dependent activation of PLC-γ1. However, we have demonstrated previously that this loop is not directly required for autoinhibition (Gresset et al., 2010), and consistent with this notion, the crystallized form of PLC-γ1 was autoinhibited in cells (Figure 1—figure supplement 2). While nuanced differences in regulation between the wild-type and crystallized version of PLC-γ1 cannot be excluded, the latter faithfully recapitulated the mutational activation of the wild-type enzyme (Figure 1—figure supplement 2). In addition, deletion of the cSH2/SH3 domain loop had no measurable effect on the hydrodynamic radius or specific activity of the purified protein (Figure 1—figure supplement 2), further demonstrating that removal of the loop did not significantly alter the biochemical properties of the enzyme.

The 2.5 Å crystal structure (Supplementary file 1) of essentially full-length rat PLC-γ1 readily explains the autoinhibition of the PLC-γ isozymes. In particular, the regulatory array sits ‘atop’ the conserved catalytic core and blocks the core from productively engaging membranes (Figure 1b). In addition, the overall structure is highly electronegative (Figure 1—figure supplement 3), and this property will also inhibit lipase activity by disfavoring interactions with negatively charged membranes. In particular, the overall negative charge of the PH domain indicates that it is unlikely to bind phosphatidylinositol 3,4,5-trisphosphate as previously reported (Falasca et al., 1998). For PLCs to hydrolyze membrane-embedded PIP2, the hydrophobic ridge of the catalytic TIM barrel must insert into lipid bilayers (Ellis et al., 1998). However, in the case of PLC-γ1, the hydrophobic ridge interacts with portions of the sPH domain in the regulatory array; this arrangement is expected to effectively block membrane engagement. The active site sits beneath the hydrophobic ridge and is readily located by the bound Ca2+ cofactor (Figure 1—figure supplement 2). As implied by the visibility of the Ca2+ cofactor, the active site is fully solvent-exposed and could presumably hydrolyze soluble substrates not embedded in lipid bilayers.

Two major interfaces lock the regulatory array on top of the catalytic core. The first is the aforementioned sPH domain interacting with the hydrophobic ridge of the TIM barrel (Figure 1c). Here, residues from the sPH domain interdigitate with residues of the hydrophobic ridge in a ‘zipper-like’ arrangement. A second interface is formed between loops of the cSH2 domain and the C2 domain of the catalytic core (Figure 1d). In this case, the BG and EF loops of the cSH2 domain clasp prominent turns of the C2 domain—almost as if the loops are pinching the C2 domain. The pinched region of the C2 domain is an additional membrane anchor point in the PLC-δ isozymes, where Ca2+ mediates between the C2 domain and negatively charged membranes (Ananthanarayanan et al., 2002; Lomasney et al., 2012). Based on sequence conservation and overall charge distribution, this region of the C2 domain of PLC-γ1 also seems likely to interact with Ca2+ and membranes, although this idea has not been tested. The analogous portion of the C2 domain of PLC-γ2 is anticipated to engage Ca2+ in a similar manner. Of note, this loop was implicated in the Ca2+-dependent translocation of PLC-γ2 to the plasma membrane necessary for amplification of the Ca2+ signaling cascade in B cells (Nishida et al., 2003). The two interfaces between the regulatory array and catalytic core do not overlap, but the sPH and cSH2 domains within the regulatory array brace each other through the C-terminal portion of the SH3 domain that lies between them (Figure 1e): picture an arch with the tail end of the SH3 domain acting as the keystone.

The structure of full-length and autoinhibited PLC-γ1 immediately evokes a straightforward mechanism for its activation upon tyrosine phosphorylation. The same BG and EF loops of the cSH2 domain that pinch the C2 domain are also used to engage pTyr783 and surrounding regions (Hajicek et al., 2013) (Figure 1f, Figure 1—figure supplement 4). Therefore, when Tyr783 is phosphorylated, we propose that it will compete with the C2 domain for binding to the cSH2 domain. This competition would presumably disengage the cSH2 domain from the C2 domain to initiate a rearrangement of the regulatory array relative to the catalytic core. Moreover, perturbations at the interface of the cSH2 and C2 domains may propagate to the interface between the sPH domain and TIM barrel through keystone residues of the SH3 domain tail to amplify the original structural rearrangements. Indeed, the structure suggests that a wholesale rearrangement of the regulatory array relative to the catalytic core is required for productive membrane engagement by PLC-γ1 (Figure 1g). This idea is consistent with previous studies using small-angle X-ray scattering (SAXS) that showed phosphorylation of PLC-γ1 is coupled to a conformational change that has yet to be defined (Bunney et al., 2012).

The SAXS studies were also used by Bunney and colleagues to analyze the arrangement of domains within PLC-γ1. They posited a fundamentally distinct arrangement of domains relative to the crystal structure presented here. In particular, the sPH and cSH2 domains were modeled as occupying the central volume of the SAXS envelope with the nSH2 and SH3 domains assuming flanking positions. In this model, the sPH domain does not contact the PLC core. This arrangement of domains would necessarily require a different mode of autoinhibition with the main autoinhibitory interface formed between the cSH2 domain and the TIM barrel.

The overall structure of PLC-γ1 also supports the multivalent scaffolding properties of the PLC-γ isozymes required for proper signaling (Lemmon and Schlessinger, 2010; Rouquette-Jazdanian et al., 2012; Timsah et al., 2014). In particular, both the nSH2 and SH3 domains are organized within the overall structure for unfettered access to cognate ligands (Figure 2, Figure 1—figure supplement 4). For example, the phosphotyrosine-binding pocket of the nSH2 domain is fully solvent exposed and the major site for engagement of phosphorylated RTKs (Bae et al., 2009; DeBell et al., 1999; Poulin et al., 2000). Likewise, the canonical polyproline-binding site of the SH3 domain is positioned to readily engage various proteins. Relevant examples include the scaffolding protein SLP-76 (Deng et al., 2005), the E3 ubiquitin ligase Cbl (Tvorogov and Carpenter, 2002), and the guanine nucleotide exchange factor Vav1 (Braiman et al., 2006; Knyazhitsky et al., 2012; Sherman et al., 2016)—all of which must be engaged by PLC-γ1 for the proper clustering of T cell receptors and subsequent downstream signaling. PLC-γ2 mediates similar clustering in response to active B cell receptors (Wang et al., 2014) and presumably will be structurally similar to PLC-γ1.

The regulatory domains of PLC-γ1 are organized to integrate multiple inputs simultaneously.

Structures of fragments of PLC-γ1 or -γ2 bound to biologically relevant proteins were superimposed on the structure of PLC-γ1 (gray ribbon) and partner proteins highlighted in color as space filling models. PDB accession numbers are listed in parentheses and the domain architecture of PLC-γ1 is shown at upper left in the same orientation.

In addition, the monomeric GTPase Rac2 binds the sPH domain of PLC-γ2 to elevate lipase activity (Piechulek et al., 2005; Walliser et al., 2008) and the equivalent surface within the sPH domain of PLC-γ1 is fully exposed to solvent (Figure 1—figure supplement 4). This last observation suggests that binding of Rac2 would not disrupt the overall structure of autoinhibited PLC-γ2. Rather, Rac2 may stabilize an active conformation of PLC-γ2 once PLC-γ2 is engaged with membranes as previously suggested (Walliser et al., 2016).

In counterpoint to the above examples, the canonical phosphotyrosine-binding site of the cSH2 domain is buried in the structure of PLC-γ1. This site is presumably reserved as the ‘trigger’ for phospholipase activation upon engagement of pTyr783. Therefore, pTyr783 is suggested to function as an intramolecular ligand that can effectively compete for the buried surface of the cSH2 domain. This situation is in contrast to intermolecular competitors such as kinases that would need to overcome substantial entropic penalties in order to bind the cSH2 domain.

Tyr783 in PLC-γ1 is presumed to be the primary site of phosphorylation coupled to enzyme activation (Gresset et al., 2010; Kim et al., 1991). Eight additional tyrosines are phosphorylated (positions 186, 472, 481, 771, 775, 959, 977, and 1254), but these sites appear dispensable for RTK-dependent activation in cells (Bunney et al., 2012). In contrast, activation of PLC-γ1 by soluble tyrosine kinases requires phosphorylation of both Tyr775 and Tyr783 (Serrano et al., 2005) and this situation is similar for PLC-γ2 where the analogous tyrosines (positions 753, 759) are also phosphorylated during phospholipase activation (Humphries et al., 2004; Ozdener et al., 2002; Rodriguez et al., 2001; Watanabe et al., 2001). How dual sites of phosphorylation cooperate to drive phospholipase activity is an open question but presumably shares aspects of regulation described above. Additional tyrosines (positions 1197, 1217) in PLC-γ2 are also phosphorylated and implicated in regulation (Watanabe et al., 2001), but these sites are not conserved in PLC-γ1.

Interfacial regulation

While the structure of PLC-γ1 strongly suggests that it must undergo a substantial rearrangement in order to gain access to its membrane-resident substrate, PIP2, this idea is speculative without substantiation. We formally tested this idea using two bespoke fluorescent substrates of mammalian PLCs (Figure 3). The first case, WH-15, is a soluble analogue of PIP2 (Huang et al., 2011). It is predicted to have unimpeded access to the active site of PLC-γ1 and mutations assumed to relieve autoinhibition by wholesale rearrangement should not affect basal specific activity for the hydrolysis of WH-15. This is in fact the case since wild-type PLC-γ1 and a set of mutated forms that are constitutively active in cells (Hajicek et al., 2013) (also see below) have essentially identical capacity to hydrolyze WH-15 in vitro (Figure 3a). In contrast, XY-69 is a fluorescent substrate of PLCs that was specifically designed to embed into lipid bilayers (Huang et al., 2018). When XY-69 in lipid vesicles was presented to the same set of PLCs, there was now a dramatic difference in hydrolytic rates (Figure 3b). Wild-type PLC-γ1 had very low specific activity, while the mutated forms were up to 30-fold more active. This discrimination presumably reflects the capacity of mutations to disrupt the interface between the regulatory domains and the catalytic core to favor a form of PLC-γ1 better able to engage PIP2 in membranes. Discrimination was greatly diminished—albeit not completely eliminated—when XY-69 was solubilized in detergent micelles (Figure 3c). These results are consistent with the postulation that autoinhibition arises from the overall spatial arrangement of PLC-γ1 that prevents it from productively engaging membranes. Mutations that destabilize this arrangement are proposed to concomitantly relieve autoinhibition and allow PLC-γ1 better access to membranes and PIP2.

Interfacial regulation of purified forms of PLC-γ1.

(a) Specific activities measured with the soluble substrate, WH-15 (3 μM). Purified PLC-γ1 variants (2 μg) shown in inset in the same order as bar chart. Data represent the mean ± SEM calculated from three independent experiments. (b–c) Quantification of phospholipase activity at lipid interfaces. The membrane-associated substrate XY-69 (5 μM) was incorporated into phospholipid vesicles containing 220 μM PE and 20 μM PIP2 (vesicles) or detergent-mixed micelles containing 0.5% w/v sodium cholate (micelles) prior to the addition of indicated forms of PLC-γ1 (wild-type PLC-γ1, 1 nM; mutant forms, 0.5 nM). Phospholipase activity determined by quantifying XY-69 hydrolysis in real-time and presented as the mean ± SEM of three independent experiments. Phosphorylation of PLC-γ1 by a constitutively active version of the FGFR2 kinase domain confirmed by native PAGE followed by Coomassie Brilliant blue staining (inset).

Accelerated molecular dynamics (aMD) simulations support the proposed mechanism of activation. In particular, all-atom simulations of PLC-γ1 reproducibly highlighted a flexible set of regulatory domains relative to a virtually static catalytic core (Figure 4a, Figure 4—figure supplement 1). Moreover, this flexibility increased for simulations of a constitutively active mutant form of PLC-γ1 harboring a single substitution (D1165H) within the C2 domain at the interface with the phosphotyrosine-binding site of the cSH2 domain (Figure 4—figure supplement 2). Of note, D1165H corresponds to the D1140G substitution in PLC-γ2; PLC-γ2(D1140G) has been identified in patients with relapsed chronic lymphocytic leukemia treated with ibrutinib (Burger et al., 2016; Landau et al., 2017). For both wild-type and mutant PLC-γ1, the correlated motions indicate that the regulatory domains tended to move as a relatively rigid block (Figure 4b).

Figure 4 with 3 supplements see all
The regulatory domains of PLC-γ1 are dynamic in aMD simulations.

(a) Root mean square deviations (RMSD) of backbone atoms for the indicated trajectories relative to the starting model of autoinhibited PLC-γ1. For comparison, the equivalent RMSDs for the PLC core (‘core only’) are also shown. (b) Correlation matrix for pairs of residues in PLC-γ1 and PLC-γ1(D1165H). Correlated motions were calculated over the first 75 nanoseconds of each simulation. (c) Superimposition of the average structures of PLC-γ1 and PLC-γ1(D1165H). Structures were calculated over 75–150 nanoseconds of each simulation. Domains in wild-type PLC-γ1 and PLC-γ1(D1165H) are shown in light and dark colors, respectively; the remainder of the proteins are gray. Red arrows indicate displacement of select Cα atoms (yellow spheres).

Comparisons of average structures derived from the aMD simulations highlight increased disorganization within the interface between the cSH2 and C2 domains upon mutation (Figure 4c). For example, Asp1165 resides within the β5/β6 turn of the C2 domain where it participates in two hydrogen bonds that stabilize the turn that forms a major part of the interface with the cSH2 domain. Substitution of Asp1165 to His (D1165H) disrupts the proximal hydrogen-bonding network and results in the partial unfolding of the β5 and β6 strands of the C2 domain during simulations. The collapse of this region is linked to an approximately 30° rotation of the cSH2 domain as it moves toward the C2 domain by approximately 10 Å. The relative movements of the C2 and cSH2 domains are propagated to the rest of the regulatory array due to its propensity to move as a block. Movements are essentially identical for a constitutively active mutant form of PLC-γ1 harboring two substitutions (Y747E+R748E) within the phosphotyrosine-binding site of the cSH2 domain and on the opposite side of the interface from Asp1165 (Figure 4—figure supplements 1, 2 and 3). This result suggests that diverse mutations within the cSH2/C2 domain interface will favor similar movements.

PLC-γ isozymes in cancers

The PLC-γ isozymes are frequently mutated in several leukemias (Burger et al., 2016; Kataoka et al., 2015) and lymphomas (Choi et al., 2015; da Silva Almeida et al., 2015; Kiel et al., 2015; Vaqué et al., 2014). In particular, PLC-γ1 is the most frequently mutated protein in adult T cell leukemia/lymphoma (Kataoka et al., 2015). In this disease, sites of substitution in PLC-γ1 are found throughout the entire primary sequence with clusters at several hotspots (Figure 5a). This rather uninformative arrangement is dramatically clarified when the entire set of substitutions is mapped onto the structure of autoinhibited PLC-γ1 (Figure 5b). Now, the majority of sites localize to the interfaces formed between the PLC core and the regulatory array. This three-dimensional clustering strongly suggests that most cancer-associated substitutions in PLC-γ1 disrupt the placement of the regulatory domains atop the core to disfavor autoinhibition. Indeed, in a panel of PLC-γ1 isozymes expressed in HEK293 cells, cancer-associated substitutions at these interfaces produced a spectrum of constitutively active phospholipases—sometimes exceeding 1500-fold greater activity than wild-type PLC-γ1 (Figure 5c). Cancer-associated mutations within the equivalent regions of PLC-γ2 produced similar enhancements, indicating conserved regulation between the two isozymes (Figure 5—figure supplement 1).

Figure 5 with 2 supplements see all
Substitutions of PLC-γ1 found in cancers activate the enzyme.

(a) Position (n = 26) and frequency of substitutions (red spheres) in PLC-γ1 for a cohort of 370 patients with adult T cell leukemia/lymphoma. (b) Mutations from (a) mapped onto the structure of PLC-γ1. (c) Basal phospholipase activity of mutant forms of PLC-γ1 in cells. Data represent the mean ± SEM of triplicate samples from a single experiment representative of three independent experiments. Inset shows mutant forms of PLC-γ1 with the lowest relative basal activity. Immunoblots of cell lysates are presented in the same order as the bar graph.

Cancer-derived mutations outside the autoinhibitory interfaces generally produced the smallest increases in basal lipase activities—but these increases were nonetheless significant in comparison to the wild-type isozyme (Figure 5c, inset). How might these additional mutations lead to constitutive phospholipase activity? Based on the sites of mutation within the structure of autoinhibited PLC-γ1, three mechanisms are likely. First, substitutions may increase the affinity of the active form of PLC-γ1 for membranes. This option is likely the case for R48W located in the PH domain near the presumed interface with membranes. A similar mode leading to elevated phospholipase activation was proposed for a substituted form of PLC-γ2 that causes arthritis in mice and has increased affinity for membranes relative to wild-type PLC-γ2 (Everett et al., 2009). Second, substitutions might disrupt interactions provided by the keystone residues of the SH3 domain that buttress the organization of the sPH and cSH2 domains needed to maintain autoinhibition. Representative substitutions include R687W and R753H and additional examples are found in both PLC-γ1 (Figure 5—figure supplement 2) and -γ2 (Figure 5—figure supplement 1). Of note, R687W is analogous to R665W in PLC-γ2 and arises in patients with relapsed chronic lymphocytic leukemia treated with ibrutinib (Woyach et al., 2014). Finally, mutations within the nSH2 domain, for example Q606R and D625Y, are near the binding site for phosphotyrosine (Bae et al., 2009) and may increase affinity for phosphorylated kinases.

The PLC-γ isozymes are normally activated upon phosphorylation, especially by diverse growth factor receptors. Therefore, the cancer-associated mutations in PLC-γ1 were further tested for effects on lipase activity after co-expression of PLC-γ1 and EGFR (Figure 6a). In all cases, a high concentration of EGF used to activate the receptor produced elevated lipase activity relative to wild-type PLC-γ1. This result indicates an untapped reserve of lipase activity that is, at least partially, released by these cancer-associated mutations in response to EGF. This point is further emphasized for lipase responses measured at varying concentrations of EGF for a representative subset of mutant PLC-γ1 isozymes with varying levels of constitutive activation (Figure 6b, upper graph). Both P867R and D1165H occur at the autoinhibitory interfaces and produced substantially elevated lipase activity relative to wild-type PLC-γ1 at all concentrations of EGF. In contrast, R48W occurs at the predicted interface of the active isozyme with membranes and abnormally elevated lipase activity of PLC-γ1(R48W) manifests only at high concentrations of EGF. This functional difference possibly reflects a mechanistic difference: P867R and D1165H likely destabilize the inactive ensemble of PLC-γ1 while simultaneously favoring active forms of the isozyme; in contrast, R48W has no substantive effect on the inactive population under these conditions and presumably only stabilizes the active isozyme once bound to membranes (Figure 6b, lower graph).

Cancer-associated substitutions prime PLC-γ1 for activation by EGFR in cells.

(a) Receptor-dependent activation of mutant forms of PLC-γ1. A substitution that abolishes phosphorylation-dependent activation of PLC-γ1 is indicated (cSH2*). Data are the mean ± SEM of triplicate samples from one experiment representative of two independent experiments. (b) EGF concentration-effect curves for wild-type and select mutant forms of PLC-γ1. Data are presented as the mean ± SEM of single data sets pooled from three independent experiments. Hypothetical reaction coordinates for each form of PLC-γ1 are shown below. In both panels, immunoblots of cell lysates transfected with PLC-γ1 are presented in the same order as the bar chart (top to bottom).

Regardless of the mechanistic details, these functional results suggest important biological ramifications. Namely, the lipase activity of mutant PLC-γ isozymes should be dependent on cellular context. For example, PLC-γ1 or -γ2 harboring mutations such as R48W that preferentially stabilize active ensembles may be essentially quiescent until the isozymes are activated by phosphorylation. These situations are relatively nuanced in comparison to more robustly activating mutations, for example P867R and D1165H, that disrupt core aspects of autoinhibition. However, the more subtly activating substitutions may nonetheless contribute to cancer in cells with high levels of active kinases such as upon the overexpression of EGFR or other growth factor receptors—situations with widespread clinical relevance (Wilson et al., 2012).

Discussion

The structure of full-length, autoinhibited PLC-γ1 provides a first clear view of the regulated activation of the PLC-γ isozymes. The overall picture is of a catalytic core that is conserved among all PLCs and that is prevented from spuriously hydrolyzing PIP2 by a set of interdependent regulatory domains stationed to preclude access of the active site to membranes. Additionally, the regulatory domains are organized to integrate numerous molecular inputs that ultimately control phospholipase activity and mediate necessary scaffolding functions (Figure 7). Importantly, the nSH2 domain is optimally positioned to readily bind phosphorylated kinases and align them to promote the phosphorylation of Tyr783 needed for activation of PLC-γ1. Although capable of engaging phosphorylated portions of kinases (Groesch et al., 2006), the equivalent surface of the cSH2 domain is buried through interactions with the C2 domain and is unlikely to initiate engagement of kinases as previously suggested (Huang et al., 2016).

Figure 7 with 1 supplement see all
Model for phosphorylation-induced activation of PLC-γ1.

In the basal state, the nSH2 domain of PLC-γ1 mediates recruitment of the autoinhibited enzyme to activated receptor tyrosine kinases, for example FGFR1. The nSH2 domain binds to phosphorylated Tyr766 (pTyr766) in the C-terminal tail of FGFR1, and its kinase domain acts as a lever to destabilize the interaction between the cSH2 and C2 domains of PLC-γ1, priming the lipase for phosphorylation-dependent activation. PLC-γ1 is subsequently phosphorylated on Tyr783, and the engagement of pTyr783 by the cSH2 domain results in the full dissociation of the cSH2 domain from the C2 domain. Importantly, the phosphorylation of Tyr783 and its subsequent engagement by the cSH2 domain is predicted to induce a large-scale rearrangement of the regulatory domains with respect to the core before the phospholipase can hydrolyze membrane-resident PIP2.

However, the two SH2 domains might work in concert upon receptor engagement to facilitate the binding of phosphorylated Tyr783 to the cSH2 domain. This idea is supported by the comparison of the full-length structure of PLC-γ1 with a structure of the two SH2 domains of PLC-γ1 bound to the phosphorylated kinase domain of fibroblast growth factor receptor 1 (FGFR1) (Bae et al., 2009). Based on this comparison, the βA/αA loop of the nSH2 domain is rearranged to accommodate pTyr766 of FGFR1 and this rearrangement leads to additional movements of the cSH2 domain (Figure 7—figure supplement 1). In the full-length structure, equivalent movements upon binding FGFR1 would open the surface of the cSH2 domain that binds pTyr783, effectively priming it to engage pTyr783. Engagement of pTyr783 by the cSH2 domain is presumed to unlatch the cSH2 domain from the catalytic core and initiate what is likely to be a relatively massive rearrangement of the regulatory domains with respect to the core before the core can engage membranes and hydrolyze PIP2.

The model of activation described above provides the mechanistic underpinnings for understanding the mutational landscape of the PLC-γ isozymes associated with disease. In particular, most of the substitutions and small deletions in these isozymes that are linked to cancers (Burger et al., 2016; Kataoka et al., 2015; Woyach et al., 2014) or autoimmune disease (Ombrello et al., 2012) occur at the interfaces between the core and regulatory domains based on the structure of autoinhibited PLC-γ1. These mutations disrupt these interfaces, release autoinhibition, and favor conformations that engage membranes to promote constitutive phospholipase activity. Shifted conformational equilibria may also explain the supra-activation of mutant forms of PLC-γ1 by EGFR. That is, mutant forms of PLC-γ1 that are predisposed to be ‘open’ may also have a greater propensity to bind EGFR and a lower probability of turning off.

Constitutive activation varies greatly, ranging from approximately 10-fold to over 1500-fold, with important cellular implications: highly active forms are expected to drive downstream signaling under all circumstances while more subtly active forms are likely to promote disease only within specific cellular contexts. An excellent example of this latter class includes mutated forms of PLC-γ2 (R665W or L845F) that arise in patients treated with ibrutinib. B cells harboring either mutant of PLC-γ2 possess normal calcium homeostasis until B cell receptors are activated, at which point intracellular calcium levels rise and remain elevated, while in the equivalent wild-type case, calcium homeostasis is rapidly reestablished (Woyach et al., 2014). Both mutant forms have essentially wild-type phospholipase activity at low levels of expression but are hypersensitive to activation by Rac2 (Walliser et al., 2016). These results suggest that once active, the mutant forms of PLC-γ2 are stabilized at membranes by binding to Rac2. That is, the mutations are cryptic until the isozymes are activated, at which point the mutated PLC-γ2 isozymes are slow to return to their autoinhibited state.

Similar context-dependent activation of mutant forms of the PLC-γ isozymes should also occur upon activation by kinases. PLC-γ1(R48W) provides an example: it has essentially wild-type phospholipase activity until co-expressed with high levels of active EGFR. Analogous scenarios may be wide-spread in cancers where tyrosine kinases are constitutively active upon substitution, truncation, fusion, or overexpression—all conditions shown to activate PLC-γ1 (Arteaga et al., 1991; Peles et al., 1991). Alternatively, the activation of RTKs by stromal components contributes to treatment-resistant cancers (Straussman et al., 2012) and roles for wild-type and mutant PLC-γ isozymes under these conditions need to be explored.

On a final note, the interfacial regulation of the PLC-γ isozymes suggests promising avenues for their isozyme-specific, allosteric modulation by small molecules to advance related chemical biology and on-going drug discovery. Namely, compounds that inhibit the movement of the regulatory domains relative to the catalytic core should also prevent membrane engagement and consequent PIP2 hydrolysis. Such compounds might treat cancers and immune diseases driven by constitutively active forms of the PLC-γ isozymes. Conversely, allosteric modulators that stabilize active forms of the PLC-γ isozymes might bolster immunotherapies (Guittard et al., 2018) or provide promising leads for the treatment of Alzheimer’s disease where a naturally occurring hypermorphic variant of PLC-γ2 is linked to protection from this disease (Magno et al., 2019).

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Escherichia coli)Rosetta2 (DE3) pLysSNovagenCat# 71403Chemically competent cells
Cell line (Homo sapiens)HEK293American Type Culture CollectionCat# CRL-1573
RRID:CVCL_0045
Cell line (Trichoplusia ni)HighFiveInvitrogenCat# B85502
RRID:CVCL_C190
Antibodyanti-HA epitope
(mouse monoclonal)
BioLegendCat# 901513
RRID:AB_2565335
WB
(1:1000)
Antibodyanti-β-actin
(mouse monoclonal)
SigmaAldrichCat# A1978
RRID:AB_476692
WB
(1:4000)
Recombinant DNA reagentpcHALIC-PLC-γ1 (plasmid)this paperVector is a modified version of pcDNA3.1 containing HA tag
Recombinant DNA reagentpcHALIC-PLC-γ2 (plasmid)this paperVector is a modified version of pcDNA3.1 containing HA tag
Recombinant DNA reagentp15LIC2-FGFR2K E565A
(plasmid)
PMID: 20807769Vector is a modified version of pET15b containing His6tag and TEV cleavage sequence
Recombinant DNA reagentpFBLIC2-PLC-γ1(21–1215) (plasmid)this paperVector is a modified version of pFastBacHT1 containing His6 tag and TEV cleavage sequence
Recombinant DNA reagentpFBLIC2-PLC-γ1(21–1215) Δ25 (plasmid)this paperVector is a modified version of pFastBacHT1 containing His6 tag and TEV cleavage sequence
Recombinant DNA reagentpcDNA3-EGFR
(plasmid)
this paperOriginal source: Dr. H. Shelton Earp, UNC-Chapel Hill
Peptide, recombinant proteinhuman epidermal growth factorInvitrogenCat# PHG0313
Software, algorithmHKL2000PMID: 27799103
Software, algorithmPhenixPMID: 20124702RRID:SCR_014224Version 1.10.1–2155
Software, algorithmWinCootPMID: 20383002RRID:SCR_014222Version 0.8.2
Software, algorithmPyMOLpymol.orgRRID:SCR_000305Version 1.8.2
Software, algorithmModellerPMID: 10940251RRID:SCR_008395Version 9.16
Software, algorithmAmberambermd.orgRRID:SCR_014230Version 14
OtherWH-15PMID: 21158426Fluorescent PIP2 analogue, soluble
OtherXY-69PMID: 29263090Fluorescent PIP2 analogue, membrane-associated

DNA constructs

Mammalian expression constructs

Request a detailed protocol

Gibson Assembly cloning (Gibson et al., 2009) was used to introduce single amino acid substitutions into full-length rat PLC-γ1 (UniProt accession number P10686; 96% identical to human PLC-γ1) and human PLC-γ2 (P16885) in a modified pcDNA3.1 expression vector that incorporates an HA epitope tag at the N-terminus of the expressed protein. The entire open-reading frame of all constructs was confirmed by automated dideoxy sequencing.

Bacterial expression constructs

Request a detailed protocol

The construct encoding a constitutively active form of the soluble kinase domain of FGFR2 (FGFR2K E565A) was described previously (Gresset et al., 2010).

Baculovirus transfer vectors

Request a detailed protocol

PLC-γ1(21–1215) was amplified from full-length rat PLC-γ1 by PCR and then subcloned into a modified pFastBacHT1 vector that incorporates a His6 tag followed by a tobacco etch virus (TEV) protease recognition sequence at the N-terminus of the expressed protein. Transfer vectors encoding PLC-γ1(21–1215) harboring the P867R or D1165H substitutions were generated similarly, using the full-length mutant forms of PLC-γ1 as PCR templates.

The Δ25 deletion, which replaces residues 766–790 of PLC-γ1 with a Ser-Gly-Ser linker, was introduced into the transfer vector encoding PLC-γ1(21–1215) by standard primer-mediated mutagenesis. PLC-γ1(21–1215) and PLC-γ1(21–1215) Δ25 were amplified by PCR and subcloned into the modified pcDNA3.1 expression vector described above using a ligation-independent cloning strategy (Stols et al., 2002).

Protein expression and purification

Request a detailed protocol

PLC-γ1(21–1215) Δ25

Request a detailed protocol

Recombinant baculovirus encoding His6-PLC-γ1(21–1215) Δ25 was prepared using the Bac-to-Bac Baculovirus Expression System according to the manufacturer’s protocol (Invitrogen). Four liters of HighFive (T. ni) cells at a density of ~2.0×106 cells/mL were infected with amplified baculovirus stock (10–15 mL/L) and harvested ~60 hr post-infection by centrifugation at 6000 rpm in a Beckman JA-10 rotor at 4°C. All subsequent centrifugation and chromatography steps were performed at 4°C.

The cell pellet was resuspended in 200 mL of ice-cold buffer N1 (20 mM HEPES (pH 7.5), 300 mM NaCl, 10 mM imidazole, 10% v/v glycerol, 0.1 mM EDTA, and 0.1 mM EGTA) supplemented with 10 mM 2-mercaptoethanol and protease inhibitor cocktail prior to lysis using an EmulsiFlex-C5 homogenizer. Crude lysate was centrifuged at 50,000 rpm for 1 hr in a Beckman Ti70 rotor. The supernatant was filtered through a 0.45 μm PES low protein-binding filter and loaded onto a 5 mL HisTrap HP IMAC column equilibrated in buffer N1 supplemented with 5 mM 2-mercaptoethanol. The column was washed with 15 column volumes (CV) of buffer N1, followed by 15 CV of 2.5% buffer N2 (buffer N1 + 1 M imidazole and 5 mM 2-mercaptoethanol). Bound proteins were eluted with 40% buffer N2. Fractions containing PLC-γ1 were pooled and dialyzed overnight in the presence of 2% w/w TEV protease to remove the His6 tag in buffer containing 20 mM HEPES (pH 7.5), 300 mM NaCl, 10% v/v glycerol, 1 mM DTT, 1 mM EDTA, and 0.1 mM EGTA. The sample was subsequently diluted two-fold with buffer N1 and applied to a 5 mL HisTrap HP column. Flow-through fractions containing cleaved PLC-γ1 were pooled, diluted three-fold with buffer Q1 (20 mM HEPES (pH 7.5) and 2 mM DTT), and loaded onto an 8 mL SourceQ anion exchange column equilibrated in 10% buffer Q2 (buffer Q1 + 1 M NaCl). Bound proteins were eluted in a linear gradient of 10–60% buffer Q2 over 50 CV. Fractions containing PLC-γ1 were pooled, concentrated using a VivaSpin 50K MWCO centrifugal concentrator, and applied to a 16 mm x 700 mm HiLoad Superdex 200 size exclusion column equilibrated in buffer containing 20 mM HEPES (pH 7.5), 150 mM NaCl, and 2 mM DTT. Pure PLC-γ1 was concentrated as described above to a final concentration of 40–50 mg/mL, aliquoted, snap-frozen in liquid nitrogen, and stored at −80°C until use.

Wild-type PLC-γ1(21–1215), PLC-γ1(21–1215) P867R, and PLC-γ1(21–1215) D1165H used for biochemical assays were purified using the method described above except that the buffer for size exclusion chromatography was supplemented with 5% v/v glycerol.

FGFR2K E565A

Request a detailed protocol

The soluble kinase domain of FGFR2 (residues 458–778) harboring a His6 tag at its N-terminus was expressed in the Rosetta2 pLysS strain of E. coli (Novagen). Cells were grown at 37°C in TB medium containing 0.1 mg/mL ampicillin and 0.034 mg/mL chloramphenicol to an OD600 of ~3.0. Protein expression was induced for 2 hr at 30°C with 0.1 mM IPTG (final concentration). Cells were collected by centrifugation, resuspended in lysis buffer (20 mM HEPES (pH 7.5), 300 mM NaCl, 10 mM 2-mercaptoethanol, 10 mM imidazole, 10 mM MgCl2, 10 μM ATP, 10% v/v glycerol, and protease inhibitor cocktail), and lysed using an EmulsiFlex-C5 homogenizer. CHAPS was then added to a final concentration of 0.5% w/v and the lysate incubated at 4°C for 30 min. Soluble lysate was prepared by ultracentrifugation and the kinase domain isolated by IMAC on a HisTrap HP column. The protein was further purified by size exclusion chromatography on a Sephacryl 200 size exclusion column equilibrated in 20 mM HEPES (pH 7.5), 200 mM NaCl, 2 mM DTT, and 5% v/v glycerol. Protein was aliquoted, snap-frozen in liquid nitrogen, and stored at −80°C until use.

Size-exclusion chromatography coupled to multi-angle light scattering

Request a detailed protocol

Multi-angle light scattering measurements were performed using Wyatt DAWN HELEOS II light scattering instrumentation (with Wyatt Optilab T-rEX refractometer and Wyatt dynamic light scattering module) coupled to a Superdex 200 10 mm x 300 mm GL size exclusion column. Following equilibration with buffer containing 20 mM HEPES (pH 7.4), 150 mM NaCl, and 0.02% w/v NaN3, 50 μL of PLC-γ1(21–1215) proteins at 2 mg/mL were loaded onto the column. Data analysis was performed with ASTRA software version 6 (Wyatt Technologies).

Crystallization of PLC-γ1(21–1215) Δ25

Request a detailed protocol

Native PLC-γ1(21–1215) Δ25

Request a detailed protocol

Crystals of PLC-γ1(21–1215) Δ25 were grown initially by sitting drop vapor diffusion. PLC-γ1(21–1215) Δ25 was diluted to 20 mg/mL in buffer containing 20 mM HEPES (pH 7.5), 150 mM NaCl, 5 mM DTT, and 0.25% w/v CHAPSO. Two hundred nanoliters of this protein solution was mixed with 100 nanoliters of reservoir solution (200 mM di-sodium tartrate and 20% w/v PEG 3,350) and equilibrated against a 30 μL reservoir. Crystals grew as a cluster of thin plates and appeared after 9 days at 20°C. Diffraction quality crystals of PLC-γ1(21–1215) Δ25 were grown at 20°C by microseeding hanging drops. Protein solution was prepared by diluting PLC-γ1(21–1215) Δ25 to 40 mg/mL in buffer containing 20 mM HEPES (pH 7.5), 150 mM NaCl, 5 mM DTT, and 0.25% w/v CHAPSO. Solutions of seed crystals were obtained by vortexing crystals of PLC-γ1(21–1215) Δ25 with a glass bead in buffer containing 200 mM di-sodium tartrate, 25% w/v PEG 3,350, 150 mM NaCl, 5 mM DTT, and 0.25% w/v CHAPSO. Seed crystals were diluted 100-fold in the same buffer prior to use. Drops were prepared by mixing, in order, 1 μL of reservoir solution (12.5% w/v PEG 3,350, 50 mM di-sodium tartrate, and 5% v/v glycerol), 2 μL of protein solution, and 0.5 μL of seed solution. Drops were equilibrated against a 500 μL reservoir. Crystals ~100 μm on the longest edge appeared after 1–2 days and were flash-frozen in liquid nitrogen on nylon loops.

Gadolinium-derivatized PLC-γ1(21–1215) Δ25

Request a detailed protocol

PLC-γ1(21–1215) Δ25 (335 μM) was treated with a 50-fold molar excess of EGTA for 1 hr at 4°C. The protein was then exchanged into crystallization buffer (20 mM HEPES (pH 7.5), 150 mM NaCl, 5 mM DTT, 5 μM EGTA, 1 mM GdCl3, and 0.25% w/v CHAPSO) using a 7K MWCO Zeba spin desalting column (Thermo Scientific). The final protein concentration in this solution was 36 mg/mL. A solution of seed crystals was prepared as described above except that the buffer contained 50 mM di-sodium tartrate, 20% w/v PEG 3,350, 5% v/v glycerol, 150 mM NaCl, 5 mM DTT, 0.25% w/v CHAPSO, 5 μM EGTA, and 1 mM GdCl3. Drops were prepared by mixing, in order, 1 μL of reservoir solution (12.5% w/v PEG 3,350, 25 mM di-sodium tartrate, and 10% v/v glycerol), 2 μL of protein solution, and 0.5 μL of seed solution. Drops were equilibrated against a 500 μL reservoir. Crystals grew at 20°C and were transferred from the mother liquor and soaked in buffer containing 25 mM HEPES (pH 7.5), 150 mM NaCl, 5 mM DTT, 0.25% w/v CHAPSO, 12.5% w/v PEG 3,350, 10% v/v glycerol, and 5 mM GdCl3 for 3 min at room temperature. Crystals were mounted on nylon loops and flash-frozen in liquid nitrogen.

X-ray diffraction data collection and structure determination

Request a detailed protocol

X-ray diffraction data were collected on crystals of native PLC-γ1(21–1215) Δ25 at the Southeast Regional Collaborative Access Team (SER-CAT) beamline 22-BM at the Advanced Photon Source at Argonne National Laboratory. One scan totaling 200° of data was collected at 100 K on a MAR 200 CCD detector. Each frame was exposed for 10 s and consisted of a 1° oscillation.

Gadolinium-derivatized crystals of PLC-γ1(21–1215) Δ25 were used to collect a single-wavelength anomalous diffraction (SAD) dataset at the gadolinium absorption peak (λ = 7,244.3 eV). Data were acquired at SER-CAT beamline 22-ID on a Rayonix MX300-HS CCD detector. Each frame consisted of a 1° oscillation and was exposed for 1 s. A total of 240° of data were collected at 100 K in 30° wedges using an inverse beam strategy. Both sets of diffraction data were indexed, integrated, and scaled using HKL2000 (Otwinowski and Minor, 1997).

Phases for the gadolinium-bound form of PLC-γ1(21–1215) Δ25 were solved by SAD using the AutoSol routine in the Phenix software suite (Adams et al., 2010). A partial model of this structure was built using AutoBuild (Terwilliger et al., 2008) and used as a molecular replacement search model to solve phases for the structure of native PLC-γ1(21–1215) Δ25. The remainder of the model was then built in an iterative process that consisted of manual model building in Coot (Emsley et al., 2010) followed by restrained refinement in Phenix. The structure was validated using MolProbity (Chen et al., 2010) and molecular representations produced with PyMOL (Schrodinger LCC, 2019). Complete data collection and refinement statistics are shown in Supplementary file 1.

Quantification of phospholipase activity in cells

Request a detailed protocol

To quantify basal phospholipase activity, HEK293 cells were plated at a density of ~75,000 cells/well in 12-well cluster plates and transiently transfected with 100 ng of vector encoding wild-type or mutant forms of PLC-γ1. Twenty-four hours post-transfection, cells were metabolically labeled overnight in serum-free, inositol-free medium containing 1 μCi of [3H]myo-inositol and 10 mM LiCl. Accumulation of [3H]inositol phosphates was quantified as described previously (Waldo et al., 2010). In all experiments, counts that accumulated in cells transfected with empty vector (~500–1000 cpm) were subtracted as background.

EGFR-dependent activation of PLC-γ1 and PLC-γ2 was quantified in HEK293 cells transiently co-transfected with 200 ng of vector expressing various forms of the PLC-γ isozymes and 100 ng of vector expressing wild-type EGFR. Cells were metabolically labeled as described above, except LiCl was omitted from the radiolabeling medium. Cells received a 30 min challenge with the indicated concentrations of recombinant human EGF (Invitrogen) diluted in Hank’s Balanced Salt Solution containing 20 mM HEPES (pH 7.5), 10 mM LiCl, and 200 μg/mL fatty acid-free bovine serum albumin (BSA).

Expression of each form of PLC-γ1 and PLC-γ2 was confirmed by immunoblotting of cell lysates using a monoclonal antibody against the HA epitope (BioLegend, clone 16B12). Lysates were also probed with a monoclonal antibody against β-actin (SigmaAldrich, clone AC-15) as a loading control. All immunoblots represent a single exposure from one experiment, and the HA epitope and β-actin were detected on the same blot. Immunoblots were loaded with all mutant versions of PLC-γ1 or PLC-γ2 in numerical order; bands were subsequently cropped and then reordered in Photoshop to reflect the order in which data are presented in bar graphs and dose-response curves. The identity of the HEK293 cell line was not authenticated, and testing for mycoplasma contamination was not performed.

In vitro quantification of phospholipase activity

Request a detailed protocol

WH-15 fluorogenic assay

Request a detailed protocol

Assays utilizing WH-15 as enzyme substrate were performed as described previously (Charpentier et al., 2014) with the following modifications. WH-15 (3 μM, final concentration) was solubilized in a final assay buffer containing 50 mM HEPES (pH 7.4), 70 mM KCl, 3 mM EGTA, 2.9 mM CaCl2, 50 μg/mL fatty acid-free BSA, 2 mM DTT, and 0.25% w/v sodium cholate. Baseline fluorescence was stabilized for 10 min, and fluorescence intensity then was quantified for an additional 15 min following addition of various forms of purified PLC-γ1(21–1215) (1 nM, final concentration). Fluorescence intensity was converted to pmol of 6-aminoquinoline using a standard curve, and initial rates of WH-15 hydrolysis were calculated from the slope of linear data points.

XY-69 fluorogenic assay

Request a detailed protocol

All assays with XY-69 (Huang et al., 2018) were performed at 30°C in 384-well plates in a PHERAstar multi-mode plate reader. Data were recorded for 30 min at intervals of 1 min using excitation and emission wavelengths of 485 nm and 520 nm, respectively. Fluorescence intensity was normalized to a blank reaction lacking phospholipase, and initial rates of XY-69 hydrolysis were calculated from the slope of the linear portion of the curve. The amount of wild-type and mutant forms of PLC-γ1(21–1215) used in all experiments was adjusted to maintain assay linearity with respect to time and protein concentration.

To prepare mixed micelles, XY-69 (5 μM, final concentration) was dried under a stream of nitrogen and solubilized by sonication in a final assay buffer containing 30 mM HEPES (pH 7.4), 70 mM KCl, 3 mM EGTA, 2.35 mM CaCl2, 2 mM DTT, and 0.5% w/v sodium cholate. PLC-γ1(21–1215) proteins (0.5–1 nM, final concentration) were diluted in 20 mM HEPES (pH 7.4), 50 mM NaCl, 1 mg/mL fatty acid-free BSA, and 2 mM DTT. Reactions were initiated by adding 10 μL of detergent micelles to 2 μL of PLC-γ1.

Phospholipid vesicles were prepared by combining XY-69, porcine brain phosphatidylinositol 4,5-bisphosphate (PIP2), and bovine liver phosphatidylethanolamine (PE) and drying the mixture under a stream of nitrogen. Lipids were resuspended by sonication in 20 mM HEPES (pH 7.4). PLC-γ1(21–1215) proteins (0.5–1 nM, final concentration) were diluted as described above for mixed micelle assays. Assays were initiated by adding 10 μL of phospholipid vesicles to 2 μL of PLC-γ1 and performed in a final assay buffer consisting of 20 mM HEPES (pH 7.4), 70 mM KCl, 3 mM EGTA, 2.35 mM CaCl2, and 2 mM DTT. Final concentrations of XY-69, PIP2, and PE were 5 μM, 20 μM, and 220 μM, respectively.

In vitro kinase assay

Request a detailed protocol

Equimolar concentrations (35 μM) of PLC-γ1(21–1215) and FGFR2K E565A were incubated on ice in buffer containing 20 mM HEPES (pH 7.4), 50 mM NaCl, 10 mM MgCl2, 0.2 mM Na3VO4, 50 ng/mL fatty acid-free BSA, 2 mM DTT, and 0.5 mM ATP. After 1 hr, a portion of the reaction mixture was diluted with 20 mM HEPES (pH 7.4), 50 mM NaCl, 1 mg/mL fatty acid-free BSA, and 2 mM DTT. Phospholipase activity was quantified using XY-69 incorporated into mixed micelles or phospholipid vesicles as described above. The concentrations of PLC-γ1(21–1215) and FGFR2K E565A were both 1 nM in the final reaction mixture. Phosphorylation of PLC-γ1(21–1215) was analyzed by native PAGE on PhastGel homogeneous medium containing 7.5% polyacrylamide followed by staining with Coomassie Brilliant blue.

[3H]PIP2 hydrolysis assay

Request a detailed protocol

Quantification of lipase activity using phospholipid vesicles consisting of 200 μM PE, 20 μM PIP2, and ~5000 cpm/assay [3H]PIP2 was performed as described previously (Waldo et al., 2010).

Homology modeling

Request a detailed protocol

PLC-γ2(14–1190)

Request a detailed protocol

A model of PLC-γ1(21–1215) containing residues 766–790 was generated with Modeller v9.16 (Martí-Renom et al., 2000) using the structure of PLC-γ1(21–1215) Δ25 as the template. This model of PLC-γ1 was then used as the template to build a model of PLC-γ2(14–1190).

Molecular dynamics simulations

Request a detailed protocol

Structural model of PLC-γ1(21–1215) Δ25

Request a detailed protocol

The X-ray crystal structure of autoinhibited PLC-γ1 included a number of missing regions presumably due to local disorder. Missing regions that were expected to contain secondary structural elements included: i) helix E of EF hand 2 (residues 190–206) and ii) helix E of EF hand 3 (residues 226–246). In order to build the missing helices, HHpred (Zimmermann et al., 2018) was used to search for suitable templates. The fragment from the structure of cuttlefish PLC21 (PDB code: 3QR0) (Lyon et al., 2011) containing helix F of EF hand 2 through helix F of EF hand 3 provided the best superimposition on the PLC-γ1 structure and was used as a template for building helix E of EF hand 3. Residues 226–233 were deleted from the X-ray structure prior to building a model of this EF hand. The apo structure of troponin C (PDB code: 1TNP) (Gagné et al., 1995) containing helix F of EF hand 1 through helix F of EF hand 2 provided the best superimposition on the structure of PLC-γ1 and was used as the template for building helix E of EF hand 2. The remaining loops missing from the structure of PLC-γ1 were built as random coils with no regular secondary structural elements. A structural model of PLC-γ1 containing all residues from Glu21 - Lys1215, except for the shortened activation loop, was generated with Modeller v9.16 using the autoinhibited PLC-γ1 structure as the template. The wild-type PLC-γ1 model was subsequently mutated in PyMOL to generate the PLC-γ1(D1165H) model used for molecular dynamics simulations.

Accelerated molecular dynamics simulations

Request a detailed protocol

Accelerated molecular dynamics (aMD) simulations utilize an enhanced sampling method that applies a bias or boost potential to the true potential that effectively raises the minima in the potential energy surface, leading to an enhanced escape rate and sampling of longer timescale events with shorter MD simulations. Using the Amber v14 software package (Case et al., 2017), conventional MD (cMD) simulations of PLC-γ1 and PLC-γ1(D1165H) in explicit solvent were used for equilibration, followed by a five nsec cMD simulation for calculating the boost potential, followed by completion of 145 nsec of boosted aMD simulations. The explicit solvent systems for PLC-γ1 and PLC-γ1(D1165H) were generated using LEaP and contained 1173 amino acid residues (PLC-γ1: 18,877 atoms, PLC-γ1(D1165H): 18,882), Na+ ions for charge neutralization (PLC-γ1: 25 ions, PLC-γ1(D1165H): 24 ions), and TIP3P water molecules in an octahedral box (PLC-γ1: 39,688 TIP3P, PLC-γ1(D1165H): 39,700), for total system sizes of ~138,000 atoms. The ff14SB force field (Maier et al., 2015) was used for parameterization and simulations run using pmemd.cuda. First, the systems underwent minimization for 10,000 steps with a convergence criterion of 0.05 kcal/mol-Å. This was followed by 200 psec dynamics (NVT ensemble) for heating, with the thermostat target temperature increasing linearly from 0K to 300K over the course of the 200 psec using a Berendsen thermostat with a relaxation time of 0.5 psec. Protein atoms were restrained with a harmonic potential of weight 1.0 kcal/mol-Å2. For relaxation and density equilibration, 300 psec dynamics (NPT ensemble) were completed using the Langevin thermostat with a collision frequency of 2.0 psec−1 and isotropic pressure scaling with a relaxation time of 1.0 psec. At this stage, protein atoms were restrained with weight 0.1 kcal/mol-Å2. During the next 500 psec of dynamics (NPT ensemble), there were no restraints placed on protein atoms. The last step of cMD was a 5 nsec simulation with snapshots saved every 5 psec. All simulations were under periodic boundary conditions, with a 1 fsec time-step with hydrogen atoms constrained by SHAKE.

Boost potential parameters were determined from the average dihedral energy (Ed) and total potential energy (Ep) over the last 5 nsec of cMD according to the protocol described by Pierce et al. (2012):

  • EthreshD = Ed + (four kcal mol−1 residue−1 * # solute residues)

  • alphaD = (0.2)*(four kcal mol−1 residue−1 * # solute residues)

  • EthreshP = Ep + (0.16 kcal mol−1 atom−1 * # atoms)

  • alphaP = (0.16 kcal mol−1 atom−1 * # atoms)

Using this formulation, the boost potential parameters were EthreshD = 19821, alphaD = 938.4, EthreshP=-395856, and alphaP = 22075. for PLC-γ1 aMD, and EthreshD = 19842, alphaD = 938.4, EthreshP=-395818, and alphaP = 22081 for PLC-γ1(D1165H) aMD.

Two independent simulations with the same starting conformation but different velocity distributions were completed for both PLC-γ1 and PLC-γ1(D1165H). Results from the analysis were consistent between each pair of replicate trajectories, and results from one representative trajectory for each protein are presented in Figure 4. Coordinate trajectories were processed using cpptraj for determining the average structure over the 75–150 nsec period of the simulation, where the conformation appeared to settle into a meta-stable state, as well as the correlated motions for Cα atoms during the first 75 nsec leading to the meta-stable state.

References

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20
    Features and development of Coot
    1. P Emsley
    2. B Lohkamp
    3. WG Scott
    4. K Cowtan
    (2010)
    Acta Crystallographica. Section D, Biological Crystallography 66:486–501.
    https://doi.org/10.1107/S0907444910007493
  21. 21
  22. 22
  23. 23
  24. 24
  25. 25
  26. 26
  27. 27
  28. 28
  29. 29
  30. 30
  31. 31
  32. 32
  33. 33
  34. 34
  35. 35
  36. 36
  37. 37
  38. 38
  39. 39
  40. 40
  41. 41
  42. 42
  43. 43
  44. 44
  45. 45
  46. 46
  47. 47
  48. 48
  49. 49
  50. 50
  51. 51
  52. 52
  53. 53
  54. 54
    Phospholipase C-γ1 associates with viral and cellular src kinases
    1. O Nakanishi
    2. F Shibasaki
    3. M Hidaka
    4. Y Homma
    5. T Takenawa
    (1993)
    Journal of Biological Chemistry 268:10754–10759.
  55. 55
  56. 56
  57. 57
  58. 58
    Processing of X-ray diffraction data collected in oscillation mode
    1. Z Otwinowski
    2. W Minor
    (1997)
    Methods in Enzymology 276:307–326.
  59. 59
  60. 60
  61. 61
  62. 62
  63. 63
  64. 64
  65. 65
  66. 66
  67. 67
  68. 68
  69. 69
  70. 70
    The PyMol Molecular Graphics System
    1. Schrodinger LCC
    (2019)
    The PyMol Molecular Graphics System.
  71. 71
  72. 72
  73. 73
    Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease
    1. R Sims
    2. SJ van der Lee
    3. AC Naj
    4. C Bellenguez
    5. N Badarinarayan
    6. J Jakobsdottir
    7. BW Kunkle
    8. A Boland
    9. R Raybould
    10. JC Bis
    11. ER Martin
    12. B Grenier-Boley
    13. S Heilmann-Heimbach
    14. V Chouraki
    15. AB Kuzma
    16. K Sleegers
    17. M Vronskaya
    18. A Ruiz
    19. RR Graham
    20. R Olaso
    21. P Hoffmann
    22. ML Grove
    23. BN Vardarajan
    24. M Hiltunen
    25. MM Nöthen
    26. CC White
    27. KL Hamilton-Nelson
    28. J Epelbaum
    29. W Maier
    30. SH Choi
    31. GW Beecham
    32. C Dulary
    33. S Herms
    34. AV Smith
    35. CC Funk
    36. C Derbois
    37. AJ Forstner
    38. S Ahmad
    39. H Li
    40. D Bacq
    41. D Harold
    42. CL Satizabal
    43. O Valladares
    44. A Squassina
    45. R Thomas
    46. JA Brody
    47. L Qu
    48. P Sánchez-Juan
    49. T Morgan
    50. FJ Wolters
    51. Y Zhao
    52. FS Garcia
    53. N Denning
    54. M Fornage
    55. J Malamon
    56. MCD Naranjo
    57. E Majounie
    58. TH Mosley
    59. B Dombroski
    60. D Wallon
    61. MK Lupton
    62. J Dupuis
    63. P Whitehead
    64. L Fratiglioni
    65. C Medway
    66. X Jian
    67. S Mukherjee
    68. L Keller
    69. K Brown
    70. H Lin
    71. LB Cantwell
    72. F Panza
    73. B McGuinness
    74. S Moreno-Grau
    75. JD Burgess
    76. V Solfrizzi
    77. P Proitsi
    78. HH Adams
    79. M Allen
    80. D Seripa
    81. P Pastor
    82. LA Cupples
    83. ND Price
    84. D Hannequin
    85. A Frank-García
    86. D Levy
    87. P Chakrabarty
    88. P Caffarra
    89. I Giegling
    90. AS Beiser
    91. V Giedraitis
    92. H Hampel
    93. ME Garcia
    94. X Wang
    95. L Lannfelt
    96. P Mecocci
    97. G Eiriksdottir
    98. PK Crane
    99. F Pasquier
    100. V Boccardi
    101. I Henández
    102. RC Barber
    103. M Scherer
    104. L Tarraga
    105. PM Adams
    106. M Leber
    107. Y Chen
    108. MS Albert
    109. S Riedel-Heller
    110. V Emilsson
    111. D Beekly
    112. A Braae
    113. R Schmidt
    114. D Blacker
    115. C Masullo
    116. H Schmidt
    117. RS Doody
    118. G Spalletta
    119. WT Longstreth
    120. TJ Fairchild
    121. P Bossù
    122. OL Lopez
    123. MP Frosch
    124. E Sacchinelli
    125. B Ghetti
    126. Q Yang
    127. RM Huebinger
    128. F Jessen
    129. S Li
    130. MI Kamboh
    131. J Morris
    132. O Sotolongo-Grau
    133. MJ Katz
    134. C Corcoran
    135. M Dunstan
    136. A Braddel
    137. C Thomas
    138. A Meggy
    139. R Marshall
    140. A Gerrish
    141. J Chapman
    142. M Aguilar
    143. S Taylor
    144. M Hill
    145. MD Fairén
    146. A Hodges
    147. B Vellas
    148. H Soininen
    149. I Kloszewska
    150. M Daniilidou
    151. J Uphill
    152. Y Patel
    153. JT Hughes
    154. J Lord
    155. J Turton
    156. AM Hartmann
    157. R Cecchetti
    158. C Fenoglio
    159. M Serpente
    160. M Arcaro
    161. C Caltagirone
    162. MD Orfei
    163. A Ciaramella
    164. S Pichler
    165. M Mayhaus
    166. W Gu
    167. A Lleó
    168. J Fortea
    169. R Blesa
    170. IS Barber
    171. K Brookes
    172. C Cupidi
    173. RG Maletta
    174. D Carrell
    175. S Sorbi
    176. S Moebus
    177. M Urbano
    178. A Pilotto
    179. J Kornhuber
    180. P Bosco
    181. S Todd
    182. D Craig
    183. J Johnston
    184. M Gill
    185. B Lawlor
    186. A Lynch
    187. NC Fox
    188. J Hardy
    189. RL Albin
    190. LG Apostolova
    191. SE Arnold
    192. S Asthana
    193. CS Atwood
    194. CT Baldwin
    195. LL Barnes
    196. S Barral
    197. TG Beach
    198. JT Becker
    199. EH Bigio
    200. TD Bird
    201. BF Boeve
    202. JD Bowen
    203. A Boxer
    204. JR Burke
    205. JM Burns
    206. JD Buxbaum
    207. NJ Cairns
    208. C Cao
    209. CS Carlson
    210. CM Carlsson
    211. RM Carney
    212. MM Carrasquillo
    213. SL Carroll
    214. CC Diaz
    215. HC Chui
    216. DG Clark
    217. DH Cribbs
    218. EA Crocco
    219. C DeCarli
    220. M Dick
    221. R Duara
    222. DA Evans
    223. KM Faber
    224. KB Fallon
    225. DW Fardo
    226. MR Farlow
    227. S Ferris
    228. TM Foroud
    229. DR Galasko
    230. M Gearing
    231. DH Geschwind
    232. JR Gilbert
    233. NR Graff-Radford
    234. RC Green
    235. JH Growdon
    236. RL Hamilton
    237. LE Harrell
    238. LS Honig
    239. MJ Huentelman
    240. CM Hulette
    241. BT Hyman
    242. GP Jarvik
    243. E Abner
    244. LW Jin
    245. G Jun
    246. A Karydas
    247. JA Kaye
    248. R Kim
    249. NW Kowall
    250. JH Kramer
    251. FM LaFerla
    252. JJ Lah
    253. JB Leverenz
    254. AI Levey
    255. G Li
    256. AP Lieberman
    257. KL Lunetta
    258. CG Lyketsos
    259. DC Marson
    260. F Martiniuk
    261. DC Mash
    262. E Masliah
    263. WC McCormick
    264. SM McCurry
    265. AN McDavid
    266. AC McKee
    267. M Mesulam
    268. BL Miller
    269. CA Miller
    270. JW Miller
    271. JC Morris
    272. JR Murrell
    273. AJ Myers
    274. S O'Bryant
    275. JM Olichney
    276. VS Pankratz
    277. JE Parisi
    278. HL Paulson
    279. W Perry
    280. E Peskind
    281. A Pierce
    282. WW Poon
    283. H Potter
    284. JF Quinn
    285. A Raj
    286. M Raskind
    287. B Reisberg
    288. C Reitz
    289. JM Ringman
    290. ED Roberson
    291. E Rogaeva
    292. HJ Rosen
    293. RN Rosenberg
    294. MA Sager
    295. AJ Saykin
    296. JA Schneider
    297. LS Schneider
    298. WW Seeley
    299. AG Smith
    300. JA Sonnen
    301. S Spina
    302. RA Stern
    303. RH Swerdlow
    304. RE Tanzi
    305. TA Thornton-Wells
    306. JQ Trojanowski
    307. JC Troncoso
    308. VM Van Deerlin
    309. LJ Van Eldik
    310. HV Vinters
    311. JP Vonsattel
    312. S Weintraub
    313. KA Welsh-Bohmer
    314. KC Wilhelmsen
    315. J Williamson
    316. TS Wingo
    317. RL Woltjer
    318. CB Wright
    319. CE Yu
    320. L Yu
    321. F Garzia
    322. F Golamaully
    323. G Septier
    324. S Engelborghs
    325. R Vandenberghe
    326. PP De Deyn
    327. CM Fernadez
    328. YA Benito
    329. H Thonberg
    330. C Forsell
    331. L Lilius
    332. A Kinhult-Stählbom
    333. L Kilander
    334. R Brundin
    335. L Concari
    336. S Helisalmi
    337. AM Koivisto
    338. A Haapasalo
    339. V Dermecourt
    340. N Fievet
    341. O Hanon
    342. C Dufouil
    343. A Brice
    344. K Ritchie
    345. B Dubois
    346. JJ Himali
    347. CD Keene
    348. J Tschanz
    349. AL Fitzpatrick
    350. WA Kukull
    351. M Norton
    352. T Aspelund
    353. EB Larson
    354. R Munger
    355. JI Rotter
    356. RB Lipton
    357. MJ Bullido
    358. A Hofman
    359. TJ Montine
    360. E Coto
    361. E Boerwinkle
    362. RC Petersen
    363. V Alvarez
    364. F Rivadeneira
    365. EM Reiman
    366. M Gallo
    367. CJ O'Donnell
    368. JS Reisch
    369. AC Bruni
    370. DR Royall
    371. M Dichgans
    372. M Sano
    373. D Galimberti
    374. P St George-Hyslop
    375. E Scarpini
    376. DW Tsuang
    377. M Mancuso
    378. U Bonuccelli
    379. AR Winslow
    380. A Daniele
    381. CK Wu
    382. O Peters
    383. B Nacmias
    384. M Riemenschneider
    385. R Heun
    386. C Brayne
    387. DC Rubinsztein
    388. J Bras
    389. R Guerreiro
    390. A Al-Chalabi
    391. CE Shaw
    392. J Collinge
    393. D Mann
    394. M Tsolaki
    395. J Clarimón
    396. R Sussams
    397. S Lovestone
    398. MC O'Donovan
    399. MJ Owen
    400. TW Behrens
    401. S Mead
    402. AM Goate
    403. AG Uitterlinden
    404. C Holmes
    405. C Cruchaga
    406. M Ingelsson
    407. DA Bennett
    408. J Powell
    409. TE Golde
    410. C Graff
    411. PL De Jager
    412. K Morgan
    413. N Ertekin-Taner
    414. O Combarros
    415. BM Psaty
    416. P Passmore
    417. SG Younkin
    418. C Berr
    419. V Gudnason
    420. D Rujescu
    421. DW Dickson
    422. JF Dartigues
    423. AL DeStefano
    424. S Ortega-Cubero
    425. H Hakonarson
    426. D Campion
    427. M Boada
    428. JK Kauwe
    429. LA Farrer
    430. C Van Broeckhoven
    431. MA Ikram
    432. L Jones
    433. JL Haines
    434. C Tzourio
    435. LJ Launer
    436. V Escott-Price
    437. R Mayeux
    438. JF Deleuze
    439. N Amin
    440. PA Holmans
    441. MA Pericak-Vance
    442. P Amouyel
    443. CM van Duijn
    444. A Ramirez
    445. LS Wang
    446. JC Lambert
    447. S Seshadri
    448. J Williams
    449. GD Schellenberg
    450. ARUK Consortium
    451. GERAD/PERADES, CHARGE, ADGC, EADI
    (2017)
    Nature Genetics 49:1373–1384.
    https://doi.org/10.1038/ng.3916
  74. 74
  75. 75
  76. 76
  77. 77
  78. 78
  79. 79
  80. 80
  81. 81
  82. 82
  83. 83
  84. 84
  85. 85
  86. 86
  87. 87
  88. 88
  89. 89
  90. 90
  91. 91
  92. 92

Decision letter

  1. Neel Shah
    Reviewing Editor
  2. John Kuriyan
    Senior Editor; University of California, Berkeley, United States
  3. Neel Shah
    Reviewer
  4. Peter Gierschik
    Reviewer

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

Acceptance summary:

This article represents an important advance in our understanding of the normal regulation and the dysregulation of a key family of signaling enzymes, the phospholipase C-γ proteins. The structure of near-full-length auto-inhibited PLC-γ1, with concomitant biochemical analysis, reveals a clear picture of how PLC-γ isozymes are activated in response to various input signals. The structure and analysis also suggest how disease-associated mutations in PLC-γ proteins can enhance PLC-γ enzymatic activity and signaling. The results presented in this report will be of interest both to structural biologists and cancer biologists. Notably, as the authors point out in the article, the structural insights presented here should also lay the foundation for the development of PLC-γ targeted therapies.

Decision letter after peer review:

Thank you for submitting your article "Structural basis for the activation of PLC-γ isozymes by phosphorylation and cancer-associated mutations" for consideration by eLife. Your article has been reviewed favorably by three peer reviewers, including Neel Shah as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by John Kuriyan as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Peter Gierschik (Reviewer #2).

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

Summary:

Hajicek et al. present the structure of full-length PLC-γ 1 in its auto-inhibited state. The structure shows how the multiple regulatory domains of the enzyme act in concert to prevent membrane localization and access to phospholipid substrates. Furthermore, the structure suggests how recruitment of an activating kinase, such as FGFR1, primes the molecule for the large conformational rearrangement that must occur to fully activate the enzyme. Their results also nicely explain how many disease associate mutations found in PLC-γ dysregulate the enzyme. The structure of auto-inhibited PLC-γ1 reveals that many disease-associated mutations lie at interdomain interfaces and likely disrupt auto-inhibitory interactions.

Overall this is a clear and well written manuscript that provides new mechanistic understanding of an important, and tightly regulated, signaling molecule. The work will be of interest to a wide audience.

Essential revisions:

The reviewers have agreed that no essential experimental revisions are required.

1) The presentation of the results aims at understanding a dynamic process, involving subdomain movements and reorientation of the enzyme vis-à-vis the plasma membrane containing its substrate. Since the structure presented here represents a single snapshot of this dynamic process, many aspects of this process are left open for future discoveries. Our recommendation, therefore, is to more clearly separate, at many points throughout the manuscript, experimental facts from still hypothetical processes (e.g. "wholesale rearrangement") that evolve from the snapshot scenario upon enzyme activation.

2) PLC-γ isozymes are phosphorylated at several tyrosine residues, e.g. PLC-γ2 at Y753, Y759, Y1197, and Y1217. The phosphorylation of these residues has been reported to be functionally important (JBC 276:38595-601 and 276:47982-92). Three of these residues are lacking in the structure analyzed here, but the authors should mention the importance of phosphorylation sites other than Y783 in PLC-γ1. Can anything about these other sites be inferred from this new structure?

3) The authors suggest that activation of PLC-γ isozymes requires wholesale rearrangement of the regulatory domains relative to the catalytic core, and indicate that the details of this change await further studies. In their 2012 Structure article, Bunney and co-workers examine structural rearrangements in the regulatory domains by SAXS and NMR (PMID: 23063561). The authors should address how those low-resolution models relate to the high-resolution structure and mechanistic models described in this manuscript.

4) In the cellular studies, highlighted in Figures 5 and 6, were phosphorylation states/levels of PLC-γ1 mutants measured (with a pTyr783-specific antibody)? If so, this data could be included to help interpret the mechanisms by which the different mutants respond to EGF stimulation.

5) For the data in Figure 6B, it would be interesting to know what the fold-change in activity is for each mutant in the +EGF condition relative to the -EGF condition. Does a comparison of fold-change upon EGFR stimulation across the mutants say anything about the mechanism of activation?

6) Related to the previous point, it is interesting that many of the mutants that destabilize the auto-inhibited state can achieve higher than wild-type levels of activity upon EGFR stimulation. This suggests that activation of PLC-γ1 by EGFR (presumably via phosphorylation of Tyr783) may not alter PLC-γ1 in the same way as these mutations. How do these mutants achieve higher activity in their fully-activated state? Can the authors comment on this?

7) The manuscript very nicely describes that there are differences in enzyme activity, depending on the presentation of the substrate in a water-soluble form, in micelles, in vesicles, and in intact cells. These differences are mostly explained with the intrinsic structural features of the enzyme described in this work. However, in intact cells, extrinsic factor could come into play, such as upstream regulators of the enzyme, which might be present and active, at least to some degree, in transfected cultured model cells.

8) Sequence and structural comparison of the C2 domains of PLC-δ1 and PLC-γ2 suggest that the D1165MFS sequence (PLC-γ1 numbering) may come close to the Ca2+ binding site at the tip of the domain. This, together with the fact that this region of PLC-γ2 has previously been linked to the Ca2+ "off" response in B cells (Nishida et al., 2003) should be considered and dealt with in the text. Also, PLC-δ4 is divergent from PLC-δ1 in that region, with functional consequences (JBC 277:3568-75).

9) Many of the point mutations in PLC-γ2 cause BTK inhibitor resistance in CLL, but have not been described to be (causally) linked to cancer. Hence, the statement, that "… most of the substitutions and small deletions in these isozymes" (i.e. in both isozymes) that are linked to cancer" has to be restricted to PLC-γ1.

10) Regarding the accelerated MD simulations: It is not clear how many independent trajectories were run and analyzed to assess flexibility and correlated motions. Could the authors indicate in the Materials and methods section and/or figure legend the number and duration of independent trajectories?

11) The "Δ25" mutant is defined somewhat cryptically in the Figure 1 legend but nowhere else. It would be helpful if this nomenclature was defined in the main text, where the crystallographic construct is first described.

12) Some of the PLC-γ1 point mutants analyzed are direct counterparts of PLC-γ2 mutants found in tumor cells from ibrutinib-resistant patients. This should be referred to in the text wherever appropriate.

https://doi.org/10.7554/eLife.51700.sa1

Author response

Essential revisions:

The reviewers have agreed that no essential experimental revisions are required.

1) The presentation of the results aims at understanding a dynamic process, involving subdomain movements and reorientation of the enzyme vis-à-vis the plasma membrane containing its substrate. Since the structure presented here represents a single snapshot of this dynamic process, many aspects of this process are left open for future discoveries. Our recommendation, therefore, is to more clearly separate, at many points throughout the manuscript, experimental facts from still hypothetical processes (e.g. "wholesale rearrangement") that evolve from the snapshot scenario upon enzyme activation.

We have updated the main text in several places, as well as the legend to Figure 1, to better emphasize which aspects of the activation process are still hypothetical.

2) PLC-γ isozymes are phosphorylated at several tyrosine residues, e.g. PLC-γ2 at Y753, Y759, Y1197, and Y1217. The phosphorylation of these residues has been reported to be functionally important (JBC 276:38595-601 and 276:47982-92). Three of these residues are lacking in the structure analyzed here, but the authors should mention the importance of phosphorylation sites other than Y783 in PLC-γ1. Can anything about these other sites be inferred from this new structure?

We have added an additional paragraph to the text highlighting the existence and functional implications of phosphorylation sites besides Tyr783 in PLC-γ1 and Tyr759 in PLC-γ2. To the best of our knowledge, only Tyr775 in PLC-γ1 has also been demonstrated to regulate enzyme activity; this regulation seems to be most relevant in the context of soluble tyrosine kinases coupled to immune receptors. The equivalent site in PLC-γ2, Tyr753, has a similar regulatory role. We note that phosphorylation of PLC-γ2 on Tyr1197 and Tyr 1217 has been reported; these sites are not conserved in PLC-γ1. Unfortunately, the Δ25 deletion encompasses Tyr775, limiting the conclusions that can be drawn about how this site regulates activity.

3) The authors suggest that activation of PLC-γ isozymes requires wholesale rearrangement of the regulatory domains relative to the catalytic core, and indicate that the details of this change await further studies. In their 2012 Structure article, Bunney and co-workers examine structural rearrangements in the regulatory domains by SAXS and NMR (PMID: 23063561). The authors should address how those low-resolution models relate to the high-resolution structure and mechanistic models described in this manuscript.

With respect to the structural models and activation mechanism proposed by Bunney et al. (PMID: 23063561), a paragraph has been added to the text discussing similarities and differences with the crystal structure.

4) In the cellular studies, highlighted in Figures 5 and 6, were phosphorylation states/levels of PLC-γ1 mutants measured (with a pTyr783-specific antibody)? If so, this data could be included to help interpret the mechanisms by which the different mutants respond to EGF stimulation.

Excellent question, however, the phosphorylation state of PLC-γ1 mutants was not assessed in this study.

5) For the data in Figure 6B, it would be interesting to know what the fold-change in activity is for each mutant in the +EGF condition relative to the -EGF condition. Does a comparison of fold-change upon EGFR stimulation across the mutants say anything about the mechanism of activation?

Figure 6 has been modified to indicate the fold-change in activity between the -EGF and +EGF conditions. It is unclear if there is any relationship between fold-changes in EGFR stimulation and mechanisms of activation.

6) Related to the previous point, it is interesting that many of the mutants that destabilize the auto-inhibited state can achieve higher than wild-type levels of activity upon EGFR stimulation. This suggests that activation of PLC-γ1 by EGFR (presumably via phosphorylation of Tyr783) may not alter PLC-γ1 in the same way as these mutations. How do these mutants achieve higher activity in their fully-activated state? Can the authors comment on this?

We agree that the higher levels of receptor-dependent lipase activity displayed by mutant forms of PLC-γ1 is intriguing; furthermore, we note in the Discussion that mutant versions of PLC-γ2 are reported to behave similarly. That is, in the context of receptor stimulation, cells expressing mutated versions of PLC-γ2 achieve higher levels of calcium mobilization (and those calcium levels are sustained for a longer period of time) than cells expressing wild-type PLC-γ2 (PMID: 24869598). How mutations might drive supra-activation of the PLC-γ isozymes is not immediately clear, although it may reflect a combination of hypersensitivity to upstream activators and a slower rate of return to the autoinhibited state. We suggest that cancer-associated substitutions drive the equilibrium away from the autoinhibited state towards more active conformations, effectively increasing the amount of time the lipase spends in active state. These ideas are further elaborated in the Discussion.

7) The manuscript very nicely describes that there are differences in enzyme activity, depending on the presentation of the substrate in a water-soluble form, in micelles, in vesicles, and in intact cells. These differences are mostly explained with the intrinsic structural features of the enzyme described in this work. However, in intact cells, extrinsic factor could come into play, such as upstream regulators of the enzyme, which might be present and active, at least to some degree, in transfected cultured model cells.

We agree that extrinsic cellular factors may impact regulation of PLC-γ1. We believe this point is implicitly addressed in the Discussion and has not been developed further.

8) Sequence and structural comparison of the C2 domains of PLC-δ1 and PLC-γ2 suggest that the D1165MFS sequence (PLC-γ1 numbering) may come close to the Ca2+ binding site at the tip of the domain. This, together with the fact that this region of PLC-γ2 has previously been linked to the Ca2+ "off" response in B cells (Nishida et al., 2003) should be considered and dealt with in the text. Also, PLC-δ4 is divergent from PLC-δ1 in that region, with functional consequences (JBC 277:3568-75).

We have expanded the Discussion on the potential of the PLC-γ1 C2 domain to ligate calcium to include the fact that the corresponding region in PLC-γ2 has been implicated in Ca2+-dependent translocation with functional implications for Ca2+ signaling in B lymphocytes.

9) Many of the point mutations in PLC-γ2 cause BTK inhibitor resistance in CLL, but have not been described to be (causally) linked to cancer. Hence, the statement, that "… most of the substitutions and small deletions in these isozymes" (i.e. in both isozymes) that are linked to cancer" has to be restricted to PLC-γ1.

Additional references that link PLC-γ2 to cancer were added.

10) Regarding the accelerated MD simulations: It is not clear how many independent trajectories were run and analyzed to assess flexibility and correlated motions. Could the authors indicate in the Materials and methods section and/or figure legend the number and duration of independent trajectories?

The Materials and methods section has been updated with the requested information.

11) The "Δ25" mutant is defined somewhat cryptically in the Figure 1 legend but nowhere else. It would be helpful if this nomenclature was defined in the main text, where the crystallographic construct is first described.

The °25 mutation is now defined in the main text and readers are directed to the Materials and methods section for a detailed description of the deletion. Figure 1—figure supplement 1 was also modified to highlight explicitly the Δ25 deletion.

12) Some of the PLC-γ1 point mutants analyzed are direct counterparts of PLC-γ2 mutants found in tumor cells from ibrutinib-resistant patients. This should be referred to in the text wherever appropriate.

The direct correspondence between the PLC-γ1(D1165H)/PLC-γ2(D1140G) substitutions and the PLC-γ1(R687W)/PLC-γ2(R665W) substitutions is noted at the first mention of PLC-γ1(D1165H) and PLC-γ1(R687W) in the text.

https://doi.org/10.7554/eLife.51700.sa2

Article and author information

Author details

  1. Nicole Hajicek

    Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Formal analysis, Supervision, Investigation, 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:" 0000-0001-7457-4830
  2. Nicholas C Keith

    Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Formal analysis, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4050-9261
  3. Edhriz Siraliev-Perez

    Department of Biochemistry and Biophysics, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Formal analysis, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1824-863X
  4. Brenda RS Temple

    1. Department of Biochemistry and Biophysics, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    2. R L Juliano Structural Bioinformatics Core Facility, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Software, Formal analysis, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9233-0191
  5. Weigang Huang

    Division of Chemical Biology and Medicinal Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Resources, Writing - review and editing, Synthesized and characterized WH-15
    Competing interests
    No competing interests declared
  6. Qisheng Zhang

    1. Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    2. Division of Chemical Biology and Medicinal Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    3. Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Resources, Supervision, Funding acquisition, Writing - review and editing
    Competing interests
    No competing interests declared
  7. T Kendall Harden

    Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Conceptualization, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
  8. John Sondek

    1. Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    2. Department of Biochemistry and Biophysics, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    3. Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Methodology, Writing - original draft, Writing - review and editing
    For correspondence
    sondek@med.unc.edu
    Competing interests
    partial ownership of KXTbio, Inc which licenses the production of WH-15
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1127-8310

Funding

National Institutes of Health (R01-GM057391)

  • John Sondek

National Institutes of Health (R01-GM098894)

  • Qisheng Zhang
  • John Sondek

National Science Foundation (DGE-1650116)

  • Edhriz Siraliev-Perez

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

Acknowledgements

We gratefully acknowledge Drs. M Lemmon and J Schlessinger for a critical reading of the manuscript. We thank Dr. M Miley for assistance with in-house collection of X-ray diffraction data and Dr. S Endo-Streeter for assistance with validation of the PLC-γ1 model. We thank the staff of SER-CAT beamlines 22-ID and 22-BM for assistance with collection of X-ray diffraction data; use of the Advanced Photon Source was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract W-31–109-Eng-38. This work was supported by The National Institutes of Health Grants R01-GM057391 (JS) and R01-GM098894 (QZ and JS). ES-P was supported by a National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650116. The UNC Macromolecular Crystallization Core Facility and R L Juliano Structural Bioinformatics Core Facility are supported by P30-CA016086.

Senior Editor

  1. John Kuriyan, University of California, Berkeley, United States

Reviewing Editor

  1. Neel Shah

Reviewers

  1. Neel Shah
  2. Peter Gierschik

Publication history

  1. Received: September 6, 2019
  2. Accepted: December 30, 2019
  3. Accepted Manuscript published: December 31, 2019 (version 1)
  4. Version of Record published: February 6, 2020 (version 2)

Copyright

© 2019, Hajicek 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.

Metrics

  • 1,263
    Page views
  • 328
    Downloads
  • 1
    Citations

Article citation count generated by polling the highest count across the following sources: PubMed Central, Crossref, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Andrea Graziadei et al.
    Research Article
    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Xinru Wang et al.
    Research Article