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Chronic optogenetic induction of stress granules is cytotoxic and reveals the evolution of ALS-FTD pathology

  1. Peipei Zhang
  2. Baochang Fan
  3. Peiguo Yang
  4. Jamshid Temirov
  5. James Messing
  6. Hong Joo Kim
  7. J Paul Taylor  Is a corresponding author
  1. St. Jude Children’s Research Hospital, United States
  2. Howard Hughes Medical Institute, United States
Research Communication
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Cite this article as: eLife 2019;8:e39578 doi: 10.7554/eLife.39578

Abstract

Stress granules (SGs) are non-membrane-bound RNA-protein granules that assemble through phase separation in response to cellular stress. Disturbances in SG dynamics have been implicated as a primary driver of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), suggesting the hypothesis that these diseases reflect an underlying disturbance in the dynamics and material properties of SGs. However, this concept has remained largely untestable in available models of SG assembly, which require the confounding variable of exogenous stressors. Here we introduce a light-inducible SG system, termed OptoGranules, based on optogenetic multimerization of G3BP1, which is an essential scaffold protein for SG assembly. In this system, which permits experimental control of SGs in living cells in the absence of exogenous stressors, we demonstrate that persistent or repetitive assembly of SGs is cytotoxic and is accompanied by the evolution of SGs to cytoplasmic inclusions that recapitulate the pathology of ALS-FTD.

Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

https://doi.org/10.7554/eLife.39578.001

Introduction

Genetic, pathologic, biophysical, and cell biological evidence has implicated disturbances in stress granules as a primary driver of several common neurodegenerative diseases, including ALS, FTD, and inclusion body myopathy (IBM) (Molliex et al., 2015; Mackenzie et al., 2017; Taylor et al., 2016; Lee et al., 2016; Ramaswami et al., 2013; Buchan et al., 2013; Patel et al., 2015; Hackman et al., 2013). These diseases show substantial clinical and genetic overlap and share the hallmark histopathological feature of cytoplasmic inclusions composed of RNA-binding proteins and other constituents of ribonucleoprotein (RNP) granules in affected neurons and muscle cells. A prominent feature of this end-stage cytoplasmic pathology is ubiquitinated and phosphorylated forms of TDP-43, although a host of other proteins co-localize with these pathological inclusions, including related RNA-binding proteins and ubiquitin-binding proteins such as SQSTM1, UBQLN2, OPTN, and VCP (Neumann et al., 2006; Mackenzie et al., 2007; Mackenzie and Neumann, 2016; Williams et al., 2012; Deng et al., 2011).

Many mutations that cause ALS-FTD and/or IBM impact RNA-binding proteins that are building blocks of stress granules (e.g., TDP-43, hnRNPA1, hnRNPA2B1, hnRNPDL, TIA1, matrin 3, and FUS). Furthermore, these mutations largely cluster in low-complexity, intrinsically disordered regions (IDRs) and in many cases have been shown to change the dynamic properties of stress granules (Mackenzie et al., 2017; Hackman et al., 2013; Kim et al., 2013; Liu-Yesucevitz et al., 2010). Another set of disease-causing mutations impact ubiquitin-binding proteins (e.g., UBQLN2, VCP, p62/SQSTM1, and OPTN) whose functions intersect with disassembly and/or clearance of stress granules (Buchan et al., 2013; Dao et al., 2018; Chitiprolu et al., 2018). Furthermore, pathological poly-dipeptides arising from repeat-expanded C9orf72, the most common genetic cause of ALS-FTD, insinuate into stress granules and other membrane-less organelles, perturbing their dynamics and/or functions (Lee et al., 2016; Boeynaems et al., 2017). Several ALS-, FTD-, and IBM-causing mutations cause aberrant phase separation and change the biophysical and material properties of stress granules, generally resulting in poorly dynamic membrane-less organelles that, it has been suggested, may evolve into the cytoplasmic pathology found in end-stage disease (Mackenzie et al., 2017; Buchan et al., 2013; Kim et al., 2013). However, no direct evidence has demonstrated that perturbation of phase separation is sufficient to drive neurotoxicity or that ALS-FTD-associated inclusions represent the endpoint of a formerly dynamic stress granule. Moreover, capitalizing on mechanistic links between stress granules and disease to identify therapeutic targets has been limited by models employing exogenous stressors (e.g., heat shock, arsenite) to initiate stress granule assembly, with numerous nonspecific and pleiotropic effects.

Stress granules are comparatively large (~50 nm to ~3 μm) biomolecular condensates that rapidly form in the cytoplasm in response to a wide variety of stressors (Protter and Parker, 2016; Panas et al., 2016). Like other RNP granules, stress granules are believed to arise at least in part through liquid-liquid phase separation (LLPS), a biophysical phenomenon in which RNA-protein complexes separate from the surrounding aqueous cytoplasm to create a functional cellular compartment with liquid properties (Molliex et al., 2015; Protter and Parker, 2016). Stress granule assembly is a complex process that involves a cascade of events, including the dismantling of polysomes and reorganization of mRNPs into discrete cytoplasmic foci that contain >400 different protein constituents (Jain et al., 2016; Markmiller et al., 2018; Youn et al., 2018) and >1800 different RNAs (Khong et al., 2017). The assembly of RNP granules, including stress granules, is driven in part by the collective behavior of many macromolecular interactions, including RNA-RNA interactions, protein-RNA interactions, conventional interactions between folded protein domains, as well as weak, transient interactions mediated by low complexity IDRs of proteins – particularly those present in RNA-binding proteins (Banani et al., 2017). While there is consensus about the major underlying forces that drive RNP granule assembly, the precise mechanisms that orchestrate the assembly of distinct types of RNP granules are largely unknown, although general principles have been suggested by in vitro studies (Banani et al., 2016). In this conceptual framework, RNP granules and other biomolecular condensates are established and maintained by a small number of essential constituents defined as scaffolds, whereas the remaining constituents are considered clients (Banani et al., 2016).

Although at least six proteins have been suggested to be ‘essential’ elements of stress granules (Markmiller et al., 2018; Youn et al., 2018; Kedersha et al., 2016; Gilks et al., 2004; Kwon et al., 2007), until recently it was unknown which of these proteins (if any) are true scaffolds for stress granules. In related work that informs the study presented here, we performed a whole-genome screen that identified G3BP as a uniquely essential scaffold in stress granule assembly (Yang, Mathieu et al., unpublished). Moreover, we found that an oligomerization domain within G3BP that is essential to stress granule assembly could be functionally replaced by heterologous oligomerization domains, which suggested the possibility of engineering temporal and spatial control of stress granule assembly without the confounding influences of stress (Yang, Mathieu et al., unpublished). We built upon a previously described system, termed ‘OptoDroplets,’ which uses optogenetic oligomerization of proteins as a means to control intracellular LLPS (Shin et al., 2017). In this system, light-sensitive chimeric proteins are assembled from the IDRs of various RNP granule proteins combined with the light-sensitive oligomerization domain of Arabidopsis thaliana cryptochrome 2 (CRY2) photolyase homology region (PHR) to generate fusion proteins that undergo LLPS in living cells upon blue light activation. Whereas enforced aggregation of IDRs drives LLPS and thereby leads to OptoDroplet formation, it is not anticipated that droplets formed by the IDRs of any given RNP granule protein will initiate the full cascade of bona fide RNP granule assembly. However, we reasoned that adapting this OptoDroplet system might provide a means of testing the hypothesis that enforced LLPS of key stress granule constituents could distinguish between stress granule scaffolds and clients, in which LLPS of a scaffold protein would initiate a process that faithfully reconstitutes the assembly of a stress granule, whereas LLPS of a client protein would not. Moreover, if we succeeded in optical induction of stress granules, it would provide the first opportunity to examine the consequences of protracted stress granule assembly without the confounding variable of exogenous stress.

Herein we report that light-based activation of Opto-G3BP1, a chimeric protein assembled from the IDR and RNA-binding domain of G3BP1 combined with CRY2PHR, initiated the rapid assembly of dynamic, cytoplasmic, liquid granules that were composed of canonical stress granule components, including PABP, TDP-43, TIA1, TIAR, eIF4G, eIF3η, ataxin 2, GLE1, FUS, and polyadenylated RNA, thereby establishing the identity of G3BP1 as a scaffold protein for stress granules. To differentiate these complex assemblies formed by LLPS of the scaffold protein G3BP1 from the relatively homogenous clusters formed by LLPS of client proteins, we termed these structures OptoGranules. Importantly, we found that persistent or repetitive assembly of OptoGranules is cytotoxic and is accompanied by the evolution of these granules to neuronal cytoplasmic inclusions characteristic of ALS-FTD.

Results

To test whether optogenetically induced LLPS of a stress granule scaffold protein could faithfully reconstitute the assembly of a bona fide stress granule, we first investigated G3BP1 as a potential scaffold protein. G3BP1 (and its close paralog G3BP2) has been suggested to be an essential nucleator of stress granule assembly (Kedersha et al., 2016), and a genome-wide screen recently identified G3BP1/2 as a uniquely essential protein for stress granule assembly (Yang, Mathieu et al., unpublished). G3BP1 has an N-terminal 142-amino acid dimerization domain, termed the NTF2L domain, that is essential for nucleation of stress granule assembly. Remarkably, the NTF2L domain can be replaced by generic dimerization domains, and the resulting chimeric proteins are able to fully nucleate stress granule assembly in living cells (Yang, Mathieu et al., unpublished). Thus, the domain architecture of G3BP1 is ideal for engineering light-inducible stress granule assembly by replacing the NTF2L domain of G3BP1 with the blue light-dependent dimerization domain CRY2PHR in frame with the fluorescent proteins mCherry or mRuby. We named this construct ‘Opto-G3BP1’ and also created an ‘Opto-Control’ construct referring to CRY2PHR-mCherry (or mRuby) alone (Figure 1a).

Figure 1 with 4 supplements see all
OptoGranules are light-inducible dynamic stress granules.

(a) Design of Opto-G3BP1 and Opto-Control constructs. (b) U2OS cells stably expressing Opto-Control or Opto-G3BP1 were stimulated with a single 5-msec pulse of 488 nm blue light (power density ~2.5 MW/cm2) in a defined ROI. Representative images are shown from n = 3 independent experiments. (c) Quantification of data in cells treated as in (b). Five cells with similar expression levels were counted. Granule numbers are shown relative to the granule number at the peak of OptoGranule assembly. Error bars represent s.e.m. (d-f) U2OS cells were stably transfected with Opto-Control or Opto-G3BP1, or stable Opto-G3BP1 cells were transiently transfected with G3BP1-GFP, and stimulated with a blue-light laser (power density ~4.5 W/cm2) for 3 mins. Regions marked with yellow circles were photobleached and monitored for fluorescence recovery. Data are shown as representative images (d), relative fluorescence intensity of photobleached region over time (e), and relative mobile fraction derived from (e) (f). For (e, f) n = 15 cells for Opto-Control; n = 12 for Opto-G3BP1; n = 14 for G3BP1-GFP. Data are representative of n = 3 independent experiments. Data shown as mean + s.d. ns, not significant by one-way ANOVA with Dunnett’s test. (g) U2OS cells transiently transfected with Opto-G3BP1 and the stress granule marker GFP-TIA1 were stimulated with a blue-light laser (power density ~2.5 MW/cm2) for 5 msec. Cells were sequentially imaged by 561 nm and 488 nm channels; we note that the 488 nm channel used for imaging also activates Opto-G3BP1 (power density 2.2 W/cm2). Representative images are shown from n = 3 independent experiments. (h-j) U2OS cells stably expressing Opto-Control or Opto-G3BP1 constructs were stimulated for 6 hr without or with continuous blue light (~2 mW/cm2) using custom-made LED arrays for global activation. Cells were immunostained with PABP antibody (h), TDP-43 antibody (i), or RNA fluorescence in situ hybridization using FAM-labelled oligo (dT)20 as a probe (j). Scale bars, 10 µm in all micrographs.

https://doi.org/10.7554/eLife.39578.002

We next generated U2OS cell lines stably expressing Opto-Control or Opto-G3BP1 constructs with comparable expression levels of Opto-G3BP1 and endogenous G3BP1 (Figure 1—figure supplement 1a). Within seconds of blue light activation, Opto-G3BP1 in U2OS cells assembled into numerous, spherical cytoplasmic granules that exhibited liquid behaviors (Figure 1b and Videos 1 and 2). A 5-millisecond pulse of blue light using a 488 nm vector laser (~2.5 MW/cm2) was sufficient to initiate robust induction of these cytoplasmic granules, and these granules spontaneously disassembled over a period of approximately 5 min (Figure 1b,c). These granules were highly dynamic, exhibiting liquid behaviors such as fusion to form larger granules and relaxation to a spherical shape (Video 2). In contrast, under the same conditions, Opto-Control expression remained diffuse, with a modest amount of nuclear and cytoplasmic clusters (Figure 1b and Video 1). To confirm the dynamic nature of the optically induced granules, we performed fluorescence recovery after photobleaching (FRAP) to monitor recovery rates and mobile fractions of individual granules (Figure 1d–f), finding that these properties were very similar between Opto-G3BP1 and the conventional stress granule marker G3BP1-GFP. Furthermore, Opto-G3BP1 localized to spontaneous stress granules induced by expression of ALS mutant proteins (FUS R521C, TDP-43 ΔNLS, TIA1 A381T) even in the absence of blue light activation, demonstrating that the Opto-G3BP1 protein behaves similarly to endogenous G3BP1 (Figure 1—figure supplement 1b).

Video 1
Opto-Control fails to assemble light-dependent cytoplasmic clusters.

U2OS cells stably expressing Opto-Control were stimulated with a single 5-msec pulse of 488 nm blue light (power density ~2.5 MW/cm2) in a defined ROI. See Video 2 for corresponding Opto-G3BP1 condition.

https://doi.org/10.7554/eLife.39578.007
Video 2
Opto-G3BP1 assembles light-dependent cytoplasmic clusters.

U2OS cells stably expressing Opto-G3BP1 were stimulated with a single 5-msec pulse of 488 nm blue light (power density ~2.5 MW/cm2) in a defined ROI. Opto-G3BP1 assembles highly dynamic, liquid-like cytoplasmic granules, and these granules spontaneously disassemble over a period of approximately 5 min. See Video 1 for corresponding Opto-Control condition.

https://doi.org/10.7554/eLife.39578.008

To further define the relationship between light-induced Opto-G3BP1 granules and stress-induced stress granules, we next examined their composition. Employing live cell imaging, we documented the dynamic recruitment of the stress granule marker GFP-TIA1 into optically induced granules following light-induced assembly (Figure 1g and Video 3). In contrast, clusters of Opto-Control (olig), a modified form of the Opto-Control construct designed to produce abundant aggregates, did not recruit GFP-TIA1 (Figure 1—figure supplement 1c), nor did they show dynamic behavior by FRAP (Figure 1—figure supplement 1d–f).

Video 3
Dynamic recruitment of the stress granule marker GFP-TIA1 into light-induced Opto-G3BP1 granules.

U2OS cells transiently transfected with Opto-G3BP1 and the stress granule marker GFP-TIA1 were stimulated with a blue-light laser (power density ~2.5 MW/cm2) for 5 msec. Cells were sequentially imaged by 561 nm and 488 nm channels; we note that the 488 nm channel used for imaging (power density 2.2 W/cm2) also activates Opto-G3BP1.

https://doi.org/10.7554/eLife.39578.009

We further examined the composition of optically induced Opto-G3BP1 granules by staining activated cells for additional stress granule components. In these experiments, we employed a blue-light LED array that permitted global activation of a larger number of cells. This LED array has a much lower energy density (~2 mW/cm2) than the laser used for dynamic imaging, drives less oligomerization of CRY2PHR, and therefore offers slower kinetics to facilitate monitoring of the recruitment of granule components over time. In cells expressing Opto-G3BP1, but not Opto-Control, all stress granule components that we examined, including PABP, TDP-43, TIA1, TIAR, eIF4G, eIF3η, ataxin 2, GLE1, and FUS, were recruited to optically induced granules (Figure 1h–i and Figure 1—figure supplement 2a–g). Since stress granules represent assemblies of mRNA as well as protein (Panas et al., 2016; Kedersha et al., 1999), we used fluorescent in situ hybridization (FISH) with fluorescently conjugated oligo(dT) probes to examine whether polyadenylated mRNAs were present in these optically induced granules as in canonical stress granules. We found that polyadenylated mRNAs were recruited into optically induced granules that assembled after blue light stimulation but showed no relocalization in cells expressing Opto-Control (Figure 1j). These findings indicate that optically induced Opto-G3BP1 granules are stress granules composed of mRNAs and RNA-binding proteins, including ALS-associated proteins such as TDP-43, ataxin 2, GLE1, FUS, and TIA1.

Consistent with prior reports, knockout of endogenous G3BP1 and G3BP2 in U2OS cells abolished stress granule assembly in response to arsenite (Kedersha et al., 2016) (Figure 1—figure supplement 3a). When introduced into these G3BP1/G3BP2 double knockout cells, Opto-G3BP1 (or the analogous chimeric protein Opto-G3BP2) substantially restored stress granule assembly in response to blue light activation, demonstrating that the scaffolding activity of G3BP1 in the chimeric protein is functionally intact (Figure 1—figure supplement 3b,c).

The initiation of stress granule assembly in response to enforced LLPS of G3BP1 differs from prior observations made regarding OptoDroplets, which do not typically represent assembly of complex, physiologically assembled membrane-less organelles (Shin et al., 2017). To examine this in more detail, we generated a series of optically inducible chimeric proteins by generating constructs in which CRY2PHR-mCherry was fused with stress granule constituent proteins, including full-length or truncated versions of FUS, TDP-43, and TIA1. Opto-FUS [CRY2PHR-mCherry-FUS(IDR)] and Opto-TDP-43 [CRY2PHR-mCherry-TDP-43(IDR)] did assemble into droplets with blue light activation, as previously reported (Shin et al., 2017), but these OptoDroplets did not recruit stress granule constituents commonly used as markers, including G3BP1 and PABP (Figure 1—figure supplement 4a–c), and were also negative for stress granule constituents VCP, SQSTM1, and the related protein OPTN (Figure 1—figure supplement 4d,e). Similarly, constructs containing the IDR and RNA recognition motifs of FUS or TDP-43 [CRY2PHR-mCherry-FUS (1–371 aa); CRY2PHR-mCherry-TDP-43 (106–414 aa)] assembled into droplets upon blue light activation, but these droplets were also negative for stress granule markers (Figure 1—figure supplement 4f,g). Expression of Opto-constructs using full-length FUS or TDP-43 [CRY2PHR-mCherry-FUS(FL); CRY2PHR-mCherry-TDP-43(FL)] did not produce stress granules with blue light activation (Figure 1—figure supplement 4f,g). Finally, Opto-TIA1, which represents fusion of CRY2 with TIA1 (CRY2PHR-mCherry-TIA1), also assembled into droplets with blue light activation, but did not drive the assembly of stress granules, as illustrated by lack of colocalization with stress granule markers (Figure 1—figure supplement 4h–j). These data indicate that RNP granule assembly cannot be driven by enforced LLPS of any random constituent, but depends upon specific constituents. This conclusion is consistent with the proposition that LLPS initiated by scaffold proteins (e.g., G3BP1) has the capacity to initiate a membrane-less organelle, whereas client proteins (e.g., FUS, TDP-43, TIA1), even when forced to undergo LLPS, cannot reconstitute such a complex assembly (Banani et al., 2017). Thus, we termed Opto-G3BP1-induced stress granules ‘OptoGranules’ to distinguish them from OptoDroplets.

Phase transitions are highly dependent on protein concentration, and we therefore hypothesized that the induction of OptoGranule assembly would be dependent on the local concentration of activated G3BP1, similar to the concentration-dependent formation of light-activated OptoDroplets (Shin et al., 2017). To test this prediction, we controlled the local G3BP1 molecular concentration by modulating either the intensity of the activating blue light or the expression level of the Opto-G3BP1 construct. As predicted, we observed a strong positive correlation between blue light intensity and induction of OptoGranules (Figure 2a,b) and, independently, a strong positive correlation between Opto-G3BP1 expression level and induction of OptoGranules (Figure 2c,d). Thus, the OptoGranule system is highly tunable, a useful feature for a variety of studies.

Figure 2 with 1 supplement see all
OptoGranule formation is dependent on the local concentration of activated G3BP1 and dependent on polysome disassembly, but independent of eIF2α phosphorylation.

(a) U2OS cells stably expressing Opto-G3BP1 were intermittently exposed to a blue-light laser (488 nm) for activation followed by image acquisition with a 561 nm channel. Blue light intensity was sequentially increased from top to bottom (488 nm power density measurement from top to bottom: 1%, 0.02 W/cm2; 5%, 0.04 W/cm2; 25%, 0.95 W/cm2; 75%, 5.5 W/cm2). Representative images are shown from n = 3 independent experiments. (b) Quantification of data in cells treated as in (a). Error bars represent s.d. (c) U2OS cells with different expression levels of Opto-G3BP1 were intermittently exposed to a 488 nm blue-light laser (90% laser power, power density 6.3 W/cm2) followed by image acquisition with a 561 nm channel. Relative expression levels from top to bottom: 0.19, 0.32, 0.78 and 1 a.u. Representative images are shown from n = 3 independent experiments. (d) Quantification of data in cells treated as in (c). (e) U2OS cells stably expressing Opto-G3BP1 were pre-treated with cycloheximide (CHX) or ISRIB for 30 min and then exposed to 45 min of sodium arsenite (0.5 mM NaAsO2) or 6 hr of continuous blue light (~2 mW/cm2) using custom-made LED arrays for global activation, and immunostained with PABP antibody. (f) Quantification of granule-positive cells from (e). Data are shown as mean ± s.e.m. from n = 3 independent experiments. ****p<0.0001; ns, not significant by one-way ANOVA with Tukey’s post-test. (g) Immunoblot showing phosphorylated eIF2α (P-eIF2α), eIF2α, and actin levels in cells treated with sodium arsenite (0.5 mM NaAsO2) for 45 min, exposed to 42°C heat shock for 1 hr, or activated with blue light for 6 hr. See also Figure 2—figure supplement 1 for sequential probe images. Scale bars, 10 μm in all micrographs.

https://doi.org/10.7554/eLife.39578.010

We next examined the role of upstream events in OptoGranule formation and compared these to the cellular triggers associated with conventional stress granule assembly. Given that conventional stress granule formation is typically linked to the disassembly of translating polysomes (Panas et al., 2016), we tested whether polysome disassembly is required for OptoGranule formation. We determined that treatment with cycloheximide, which traps translating mRNAs within polysomes, strongly mitigated the formation of arsenite-induced stress granules and the formation of light-induced OptoGranules (Figure 2e,f), indicating that OptoGranule formation is dependent on polysome disassembly and further illustrating commonality with conventional stress granules. We next tested the role of eIF2α phosphorylation, which integrates stress granule formation downstream of a variety of stressors, such as arsenite and heat shock (Panas et al., 2016). We used the small molecule ISRIB, which binds eIF2B and interrupts eIF2α-mediated translational control (Sidrauski et al., 2015). We found that formation of arsenite-induced stress granules was blocked by ISRIB, as previously documented (Sidrauski et al., 2015), whereas the formation of light-induced OptoGranules was unaffected by ISRIB treatment (Figure 2e,f). Consistent with this finding, Western blotting also showed minimal phosphorylated eIF2α accompanying OptoGranule assembly (Figure 2g, Figure 2—figure supplement 1). Thus, OptoGranule formation depends upon the recruitment of mRNPs from polysomes, but this assembly occurs downstream and independent of the evolutionarily conserved integrated stress response regulated by eIF2α. This observation is consistent with the notion that OptoGranule formation is not driven by the classic signaling pathway for stress granule formation, which increases the concentration of free, uncoated RNA in the cytoplasm, but rather by oligomerization of G3BP1, which increases the valency for RNA binding.

Given the accumulating evidence that disturbance of membrane-less organelles such as stress granules may contribute to the initiation or progression of disease, we hypothesized that discrete disturbance in the dynamics or material properties of stress granules should be sufficient to cause cytotoxicity and recapitulate the pathognomonic features of specific diseases. To test this prediction, we examined the consequences of chronic OptoGranule assembly. First, we examined the consequences of continuous blue light activation in cells expressing Opto-G3BP1 or Opto-Control. We found that continuous induction of OptoGranules using a blue-light LED array resulted in progressive loss of cell viability reflected by progressive loss of crystal violet staining and depletion of ATP levels (Figure 3a,b). However, we also noted that chronic exposure to blue light resulted in a moderate amount of cytotoxicity in cells expressing Opto-Control or parental U2OS cells (Figure 3b). Although cells expressing Opto-G3BP1 exhibited significantly greater loss of viability upon exposure to blue light than cells expressing Opto-Control or parental U2OS cells, we sought to eliminate this potentially confounding background toxicity.

Figure 3 with 1 supplement see all
Persistent OptoGranules are cytotoxic and evolve to pathological inclusions.

(a,b) U2OS cells stably expressing Opto-Control or Opto-G3BP1 were stimulated with continuous blue light (~2 mW/cm2) for indicated times using custom-made LED arrays and viability was assessed by crystal violet staining (a) or CellTiter-Glo 2.0 luminescence (b). Whiskers represent minimum to maximum from n = 9 biological replicates. ****p<0.0001.; ns, not significant by two-way ANOVA with Tukey’s post-test. (c,d) U2OS cells stably expressing Opto-Control or Opto-G3BP1 were exposed to chronic persistent (c) or chronic intermittent (d) blue light (445 nm) stimulation with live-cell imaging (power density ~0.12 W/cm2) as illustrated in the schematic (left) and assessed for cell survival by counting living cells (right). Blue boxes in schematic indicate the timing of light induction; red line is an idealized graph of the cellular response. Chronic persistent paradigm: n = 26 for Opto-Control and n = 28 for Opto-G3BP1. Chronic intermittent paradigm: n = 7 for Opto-Control and n = 10 for Opto-G3BP1. Data are shown from n = 3 independent experiments. ****p<0.0001 by log-rank (Mantel-Cox) test. (e) Timeline of protein accumulation in OptoGranules in U2OS cells. (f-h) U2OS cells stably expressing Opto-G3BP1 were stimulated with continuous blue light (~2 mW/cm2) for indicated times using custom-made LED arrays and co-immunostained with p-TDP-43 and A11 antibodies (f), SQSTM1 and ubiquitin antibodies (g), or VCP and TDP-43 antibodies (h). (i) quantification of data from (f-h). Error bars represent s.e.m. Images in f-h are representative of n = 3 independent experiments. ***p=0.0002 (2 hr), ***p=0.0001 (3 hr) for TDP-43, **p=0.0048 (2 hr), ***p=0.0002 (3 hr) for A11, **p=0.0051 (5 hr) for ubiquitin, ****p<0.0001 for SQSTM1, ***p=0.0003 for pTDP-43, and ****p<0.0001 for VCP by one-way ANOVA with Dunnett’s test. Scale bars, 10 μm in all micrographs.

https://doi.org/10.7554/eLife.39578.012

We therefore used live, confocal-based imaging to monitor cell viability in real time during 488 nm vector laser-induced OptoGranule induction. We first used a paradigm consisting of 2 s blue light pulses alternating with 12 s of rest, which drove robust OptoGranule assembly but left insufficient time for granules to disassemble prior to the next light pulse, resulting in persistent OptoGranule assembly (Figure 3c). Interestingly, persistent OptoGranule assembly under these conditions (2 s on, 12 s off) resulted in significant loss of viability in cells expressing Opto-G3BP1, with comparatively greatly reduced toxicity in cells expressing Opto-Control (Figure 3c). We next established a paradigm that further minimized blue light exposure, using a 10 s blue light pulse followed by 10 min of rest, which was sufficient to initiate robust assembly of OptoGranules that were able to fully disassemble prior to the next light pulse (Figure 3d). This paradigm of chronic, intermittent OptoGranule assembly, which may more closely reflect physiological, chronic, intermittent stress, greatly mitigated background toxicity due to blue light exposure and revealed significant toxicity in cells expressing Opto-G3BP1 compared to cells expressing Opto-Control (Figure 3d). The cell death associated with chronic intermittent OptoGranule assembly progressed more slowly than the cell death caused by chronic persistent OptoGranule assembly, although this difference did not reach statistical significance (Figure 3—figure supplement 1a). Taken together, these results demonstrate that chronic persistent or chronic intermittent stress granule assembly is intrinsically cytotoxic, independent of exogenous stressors.

Disease pathology in tissue from patients with ALS and FTD is marked by deposits of ubiquitin, ubiquitin-binding proteins, and TDP-43 that is cleaved and abnormally phosphorylated at Ser409/410 (Neumann et al., 2009). Newly formed OptoGranules were easily distinguished from the pathology present in late-stage ALS and FTD. Although OptoGranules were initially immunopositive for TDP-43 (as are conventional arsenite-induced stress granules) and ubiquitin, they were immunonegative for phospho-TDP-43 and ubiquitin-binding proteins (Figure 3e–i). OptoGranules were, however, immunopositive for staining by anti-A11, a conformation-specific antibody that recognizes amyloid oligomer, a feature also shared by conventional stress granules (Figure 3e–i and Figure 3—figure supplement 1b). The presence of A11 immunopositivity in newly formed stress granules suggests that non-pathological amyloid oligomers are present in the mRNPs recruited to these structures, perhaps arising from the prion-like low complexity domains of RNA-binding proteins coating these mRNPs. While these are presumably physiological amyloids, it is conceivable that their close packing in the condensed liquid state of persistent stress granules risks seeding the assembly of pathological amyloids, particularly for proteins like TDP-43 that can adopt highly stable structures.

Remarkably, the characteristics of OptoGranules changed during chronic assembly. First, OptoGranules showed time-dependent reduction in dynamics as assessed by FRAP (Figure 3—figure supplement 1c,d). Moreover, we observed that immunopositivity for TDP-43, A11, and ubiquitin gradually increased over time, and after approximately two hours of OptoGranule assembly, these granules showed immunopositivity using two distinct anti-phospho-TDP-43 antibodies (Figure 3f–i, Figure 3—figure supplement 1e,f). The anti-phospho-TDP-43 antibodies specifically recognize phosphorylation of TDP-43 at residues Ser409/410, a pathological signature specific to a spectrum of sporadic and familial forms of TDP-43 proteinopathies, including ALS-FTD (Neumann et al., 2009). Moreover, after approximately five hours of chronic OptoGranule assembly, we observed a significant increase in immunopositivity using antibodies to phospho-TDP-43 and the ubiquitin-binding proteins SQSTM1 and VCP, illustrating further evolution of these structures (Figure 3g–i).Thus, not only does chronic OptoGranule assembly cause a loss of cell viability, but cell death is preceded by the evolution of OptoGranules into cytoplasmic inclusions that recapitulate features that are pathognomonic for ALS-FTD.

We next examined the consequence of protracted stress granule assembly in a more disease-relevant, neuronal context by generating human induced pluripotent stem cell (iPSC)-derived neurons, which we verified had a cortical molecular identity (Figure 4—figure supplement 1a,b). In response to arsenite or heat shock stresses, these iPSC-derived neurons assembled conventional stress granules that were positive for TIA1 and TDP-43, indicating that they were suitable for examining the consequences of chronic stress granules (Figure 4—figure supplement 1c). Next, we introduced mRuby-tagged Opto-G3BP1 into differentiated neurons (Figure 4a). In mRuby-Opto-G3BP1-expressing neurons, blue light activation induced the assembly of OptoGranules indistinguishable from those observed in U2OS cells (Figure 4b, Figure 4—figure supplement 1d and Videos 4 and 5). Chronic induction of OptoGranules following transient introduction of mRuby-Opto-G3BP1 resulted in progressive loss of neuronal viability (Figure 4c) and the formation of neuronal cytoplasmic inclusions that were immunopositive for TDP-43, A11, and ubiquitin, with time-dependent immunopositivity for phosphorylated TDP-43 and SQSTM1 (Figure 4d–i, Figure 4—figure supplement 1e). We also generated iPSCs stably expressing inducible Opto-G3BP1 (doxycycline-inducible mCherry-tagged Opto-G3BP1), in which Opto-G3BP1 expression was induced simultaneously with neuronal differentiation by the addition of doxycycline (Figure 4—figure supplement 2a). In these cells, Opto-G3BP1 remained diffuse until activation with blue light, whereupon these neurons assembled dynamic OptoGranules (Figure 4—figure supplement 2b). With continuous stimulation, these OptoGranules further evolved into neuronal cytoplasmic inclusions that were positive for phospho-TDP-43, A11, ubiquitin, and SQSTM1 (Figure 4—figure supplement 2c–f). Thus, chronic OptoGranule induction recapitulates the evolution of ALS-FTD pathology and neurotoxicity in human iPSC-derived neurons.

Figure 4 with 2 supplements see all
Persistent OptoGranules are cytotoxic and evolve to pathological inclusions in human iPSC-derived neurons.

(a) Schematic illustrating generation of iPSC-derived neurons stably expressing Opto-G3BP1. (b) iPSC-derived neurons expressing Opto-Control (mRuby) or Opto-G3BP1 (mRuby) were intermittently exposed to a 488 nm blue-light laser (90% laser power, power density 6.3 W/cm2) followed by image acquisition with a 561 nm channel. Representative images are shown from n = 3 independent experiments. (c) iPSC-derived neurons expressing Opto-Control or Opto-G3BP1 were exposed to chronic persistent stimulation as in Figure 3c and survival was assessed by counting living cells. n = 35 cells for Opto-Control and n = 34 cells for Opto-G3BP1. Data are representative of n = 3 independent experiments. ****p<0.0001 by log-rank (Mantel-Cox) test. (d) Timeline of pathological protein accumulation in OptoGranules in iPSC-derived neurons. (e-h) iPSC-derived neurons expressing Opto-G3BP1 were stimulated with continuous blue light (~2 mW/cm2) for indicated times using custom-made LED arrays and co-immunostained with MAP2 and TDP-43 antibodies (e), MAP2 and A11 antibodies (f), MAP2 and p-TDP-43 (P01) antibodies (g), or ubiquitin and SQSTM1 antibodies (h). See also Figure 4—figure supplement 1e for line scans of images shown in (h).(i) quantification of data from e-h. Error bars represent s.e.m. Images in e-h are representative of n = 3 independent experiments. *p=0.0489 (2 hr), ***p=0.0001 (5 hr) for SQSTM1 and ****p<0.0001 for pTDP-43 by one-way ANOVA with Dunnett’s test. Scale bars, 10 μm in all micrographs.

https://doi.org/10.7554/eLife.39578.014
Video 4
Blue light activation fails to induce the assembly of OptoGranules in iPSC-derived neurons expressing Opto-Control.

iPSC-derived neurons expressing Opto-Control (mRuby) were intermittently exposed to a 488 nm blue-light laser (95% laser power, power density 6.5 W/cm2) followed by image acquisition with a 561 nm channel. See Video 5 for corresponding Opto-G3BP1 condition.

https://doi.org/10.7554/eLife.39578.017
Video 5
Blue light activation induces the assembly of OptoGranules in iPSC-derived neurons expressing Opto-G3BP1.

iPSC-derived neurons expressing Opto-G3BP1 (mRuby) were intermittently exposed to a 488 nm blue-light laser (95% laser power, power density 6.5 W/cm2) followed by image acquisition with a 561 nm channel. See Video 4 for corresponding Opto-Control condition.

https://doi.org/10.7554/eLife.39578.018

Discussion

In addition to providing a system to experimentally examine previously untestable hypotheses regarding the role of stress granules in disease, the development of the OptoGranule system provides insights into the nucleation and assembly of stress granules. In particular, we contrast the consequences of optogenetically enforced, intracellular LLPS of G3BP1 to those of FUS, TDP-43, and TIA1. These proteins are all constituents of stress granules (Jain et al., 2016) that undergo LLPS in vitro (Yang, Mathieu et al., unpublished) (Mackenzie et al., 2017; Patel et al., 2015; Conicella et al., 2016). Yet, LLPS of G3BP1 results in the formation of OptoGranules, whereas FUS, TDP-43, and TIA1 form OptoDroplets that do not initiate stress granule assembly. OptoGranules and OptoDroplets are similar insofar as both types of assemblies are initiated with optically induced LLPS. Indeed, it is this similarity that suggested the name ‘OptoGranules,’ since they were inspired by and built upon observations made by Shin et al. regarding OptoDroplets. Beyond this similarity, however, OptoDroplets and OptoGranules are fundamentally different. This distinction is straightforward when considering evidence that biomolecular condensates are composed of clients and scaffolds that play fundamentally different roles in the assembly and maintenance of these condensates (Banani et al., 2016). In unpublished work that strongly informed the development of OptoGranules, we identified G3BP as a uniquely essential central scaffold protein for stress granules, in contrast to TIA1, TDP-43, FUS and many others, which are client proteins (Yang, Mathieu et al., unpublished). The differences in the assemblies formed by client proteins versus those formed by scaffold proteins make sense, since client proteins often reside in multiple biomolecular condensates with distinct identities. In contrast, enforced LLPS of a scaffold protein initiates the cascade of events that seeds the assembly of a full-fledged, complex stress granule.

We also highlight a second, more subtle distinction. OptoDroplets formed by Opto-TDP-43, Opto-FUS, and Opto-TIA1 have their biophysical origin in CRY2 oligomerization that presumably forces the IDRs of these proteins to self-associate and initiate a phase transition (Shin et al., 2017). In contrast, activation of Opto-G3BP1 forms granules because CRY2-based multimerization (specifically via the replaced NTF2L domain) increases the valency of G3BP, permitting it to engage with another scaffolding element (i.e., a class of RNAs), and these interactions create a seed that subsequently undergoes a phase transition that mediates subsequent further assembly of a stress granule.

Among the many membrane-less organelles that arise through phase transitions, stress granules have drawn the most attention from the ALS-FTD field because of their cytoplasmic location, which matches the location of pathological deposits in ALS-FTD, and the many disease-associated proteins that are components of stress granules. However, we must emphatically note that LLPS-mediated assembly, dynamics, and material properties of stress granules must be viewed within the context of a larger cellular network of membrane-less organelles, which include a wide variety of nuclear and cytoplasmic RNP granules. Indeed, membrane-less organelles are now recognized as functionally relevant biomolecular condensates that underlie different segregated biochemistries within a single cell (Banani et al., 2017). Furthermore, their material properties (e.g., assembly/disassembly rates, mobility, viscosity) likely influence these functions; indeed, the data presented here supports the burgeoning hypothesis that ALS-FTD arises from disturbances in the dynamics and material properties of membrane-less organelles, with devastating consequences over time.

Extending this hypothesis, we speculate that disease may reflect simultaneous pathological disturbance of multiple membrane-less organelles that arises by derangement of a network of multiple, independent phases. These interconnections likely reflect communication across different types of membrane-less compartments based on rapid, dynamic exchange of macromolecules (e.g., RNA and RNA-binding proteins) and small molecules that act as vehicles to communicate material states throughout the network. An example of this is seen in the recent report that perturbation of one phase-separated compartment (stress granules) alters the properties and function of a distinct phase-separated structure (the nuclear pore) (Zhang et al., 2018). With such a system-wide regulation, primary disturbances in the material properties of one node of the network (e.g., stress granules) may lead to secondary disturbances that are propagated throughout the entire network of membrane-less organelles.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional information
Cell line (Human)U-2 OSATCCHTB-96; RRID:CVCL_0042
Cell line (Human)Lenti-X 293T(293LE)Clontech632180; RRID: CVCL_4401
Cell line (Human)iPSCsBuilding a KidneyBJFF6; RRID: CVCL_VU02
Recombinant DNA reagentpCRY2PHR-mCherryN1Addgene26866; RRID:Addgene_26866
Recombinant DNA reagentpCMV-CRY2-mCherryAddgene58368;
RRID:Addgene_58368
Recombinant DNA reagentphND2-N174Addgene31822;
RRID:Addgene_31822
Recombinant DNA reagentpKanCMV-mClover3-mRuby3Addgene74252;
RRID:Addgene_74252
Recombinant DNA reagentpTight-hND2-N106Addgene31875; RRID:Addgene_31875
Recombinant DNA reagentpsPAX2Addgene12260;
RRID:Addgene_12260
Recombinant DNA reagentCRY2olig-mCherryAddgene60032; RRID:Addgene_60032
Recombinant DNA reagentpMD2.GAddgene12259;
RRID:Addgene_12259
Recombinant DNA reagentlinear hygromycin markerClontech631625; RRID:Addgene_60032
Antibodygoat polyclonal
anti-β-actin
Santa Cruz
Biotechnology
sc-1616; RRID: AB_630836(1:1000)
Antibodymouse monoclonal anti-eIF2αSanta Cruz
Biotechnology
sc-133132; RRID: AB_1562699(1:1000)
Antibodyrabbit polyclonal anti-β-actinCell Signaling3597S; RRID: AB_390740(1:1000)
Antibodyrabbit polyclonal anti-mCherryAbcam167453; RRID: AB_2571870(1:1000)
Antibodymouse monoclonal anti-G3BP1BD Biosciences611126; RRID: AB_398437(1:1000)
Antibodyrabbit polyclonal anti-PABPAbcamab21060; RRID: AB_777008(1:400)
Antibodyrabbit polyclonal anti-eIF4GSanta Cruz
Biotechnology
sc-11373;
RRID: AB_2095750
(1:400)
Antibodyrabbit polyclonal anti-TDP-43Proteintech12892–1-AP; RRID: AB_2200505(1:400)
Antibodymouse monoclonal
anti-phospho-TDP-43 (M01)
Cosmo Bio COTIP-PTD-MO1; RRID: AB_1961900(1:1000)
Antibodyrabbit polyclonal anti-phospho-TDP-43 (P01)Cosmo Bio COTIP-PTD-PO1; RRID: AB_1961899(1:400)
Antibodymouse monoclonal anti-VCPBD Biosciences612183; RRID: AB_399554(1:100)
Antibodyrabbit polyclonal anti-amyloid-oligomer A11Thermo Fisher
Scientific
AHB0052; RRID: AB_2536236(1:100)
Antibodyrabbit polyclonal anti-UbiquitinDakoZ0458;
RRID: AB_2315524
(1:100)
Antibodymouse monoclonal anti-p62Abcamab56416;
RRID: AB_945626
(1:400)
Antibodymouse monoclonal anti-MAP2SigmaM9942;
RRID: AB_477256
(1:400)
Antibodygoat polyclonal
anti-TIA1
Santa Cruz Biotechnologysc-1751; RRID: AB_2201433(1:400)
Antibodymouse monoclonal anti-TIARBD Biosciences610352; RRID: AB_397742(1:400)
Antibodyrabbit polyclonal anti-ataxin 2Proteintech21776–1-AP; RRID: AB_10858483(1:400)
Antibodygoat polyclonal
anti-eIF3η
Santa Cruz
Biotechnology
sc-16377;
RRID: AB_671941
(1:400)
Antibodyrabbit polyclonal anti-
GLE1
Abcamab96007; RRID: AB_10678755(1:400)
Antibodyrabbit polyclonal anti-
FUS
Bethyl
Laboratories
A300-302A; RRID: AB_309445(1:400)
Antibodyrabbit polyclonal anti-
OPTN
Proteintech10837–1-AP; RRID: AB_2156665(1:400)
Commercial
assay or kit
FuGENE 6PromegaE2691
Commercial assay or kitNEBuilder HiFi
DNA Assembly
Master Mix kit
NEBE2621
Commercial assay or kitQ5 site-directed
mutagenesis
NEBE0054
Commercial assay or kitRNA 3′ End
Biotinylation Kit
Pierce20160
Commercial assay or kitCellTiter-Glo 2.0 assay kitPromegaG9242
Chemical compound, drugISRIBSigmaSML0843200 nM
Chemical compound, drugcycloheximideSigmaC4859100 µg/ml
Chemical compound, drugsodium arseniteSigma35000–1 L-R0.5 mM
Chemical compound, drughygromycin BThermo Fisher
Scientific
10687010200 μg/ml
Chemical compound, drugdoxycycline hyclateSigma-AldrichD98911 µg/ml
Chemical compound, drugpuromycinThermo Fisher
Scientific
A11138031 µg/ml
Software, algorithmImageJNIHhttps://imagej.nih.gov/ij/, RRID:SCR_003073
Software, algorithmGraphPad PrismGraphPad
Software Inc
http://www.graphpad.com/
scientific-software/prism/
RRID:SCR_002798
Software, algorithmSlideBook 6Intelligent Imaging Innovationshttps://www.intelligent-imaging.com/slidebook.php
RRID:SCR_014300
Software, algorithmImage StudioLI-CORhttps://www.licor.com/bio/products/software/image_studio_lite/?utm_source=BIO+Blog&utm_medium=28Aug13post&utm_content=ISLite1&utm_campaign=ISLite, RRID: SCR_014211
RRID:SCR_015795
Software, algorithmLAS X SoftwareLeicahttps://www.leica-microsystems.com/products/confocal-microscopes/p/leica-tcs-sp8/
RRID:SCR_013673

Cell culture and transfection

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U2OS cells were purchased from ATCC (HTB-96) and periodically authenticated by short tandem repeat (STR) profiling. U2OS cells were cultured in Dulbecco’s modified Eagle’s medium (HyClone) supplemented with 10% fetal bovine serum (HyClone SH30071.03 and SH30396.03), 1X GlutaMAX (Thermo Fisher Scientific 35050061), 50 U/ml penicillin, and 50 μg/ml streptomycin (Gibco 15140–122), and maintained at 37°C in a humidified incubator with 5% CO2. FuGENE 6 (Promega E2691) was used for transient transfections per the manufacturer’s instructions. G3BP1/2 KO cells have been previously described (Zhang et al., 2018). U2OS cells stably expressing G3BP1-GFP have been previously described (Figley et al., 2014). Cells were checked for mycoplasma with MycoAlert Mycoplasma Detection Kit (Lonza LT07-318) and then regularly checked for mycoplasma by DAPI staining.

Plasmids

DNA fragments encoding human G3BP1 and TIA1 were PCR-amplified from G3BP1 (DNASU HsCD00042033) and pEGFP-TIA1 (Mackenzie et al., 2017), respectively. FUS and TDP-43 were PCR-amplified from cDNA. The pCRY2PHR-mCherry backbone was PCR-amplified from pCRY2PHR-mCherryN1 (Opto-Control; Addgene 26866). DNA fragments encoding G3BP1, TIA1, TDP-43, or FUS were inserted into pCRY2PHR-mCherryN1 backbone using NEBuilder HiFi DNA Assembly Master Mix kit (NEB E2621). To create Opto-G3BP2, DNA fragments encoding G3BP2 were amplified from cDNA and inserted into pCMV-CRY2-mCherry (Addgene 58368) at XhoI and BamHI using NEBuilder HiFi DNA Assembly Master Mix. Mammalian codon-optimized pCRY2PHR-mCherry was PCR-amplified from pCMV-CRY2-mCherry. mRuby3 was PCR-amplified from pKanCMV-mClover3-mRuby3 (Addgene 74252). Opto-G3BP1 (mRuby) was assembled from codon-optimized pCRY2PHR-mCherry, mRuby3, and G3BP1 DNA using NEBuilder HiFi DNA Assembly Master Mix kit. Opto-G3BP1 (mRuby) lentiviral plasmids were constructed by inserting PCR-amplified CMV-promoted CRY2-mRuby-G3BP1 (ΔNTF2L) into PspXI and EcoRI linearized cloning backbone phND2-N174 (Addgene 31822) using NEBuilder HiFi DNA Assembly Master Mix kit. Dox-Opto-G3BP1 (mCherry) lentiviral plasmids were constructed by inserting PCR-amplified Opto-Control and Opto-G3BP1 into EcoRI-digested cloning backbone pTight-hND2-N106 (Addgene 31875) using NEBuilder HiFi DNA Assembly Master Mix kit. Truncations were introduced using Q5 site-directed mutagenesis (NEB E0054). G3BP1-GFP constructs have been previously described (Lee et al., 2016). All constructs were confirmed by sequencing.

Drugs and heat shock treatments

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ISRIB (200 nM; Sigma SML0843) and cycloheximide (100 µg/ml; Sigma C4859) treatment was performed for 30 min before adding sodium arsenite (0.5 mM; Sigma 35000–1 L-R) or blue light. For sodium arsenite treatment, medium was changed to medium containing 0.25 mM or 0.5 mM sodium arsenite for 30 or 45 min as indicated in figure legends. For heat shock treatment, cells were transferred to a 42°C humidified incubator with 5% CO2 for 1 hr.

Lentivirus production

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Lenti-X 293 T cells (293LE; Clontech 632180) were transfected at 80–90% confluency with viral vectors containing genes of interest and viral packaging plasmids psPAX2 (Addgene 12260) and pMD2.G (Addgene 12259) using polyethylenimine (Polysciences 24765–2). The medium was changed 24 hr after transfection. Viral supernatants were harvested 48 hr after transfection, filtered with 0.45 µM filters, and centrifuged at 100,000 x g at 4°C for 1.5 hr. Ultracentrifugation was carried out through a 20% (w/v in PBS) sucrose cushion at 100,000 x g at 4°C for 1.5 hr. Pellets were resuspended in 100 µl DMEM +10% FBS and stored at −80°C.

Stable cell lines

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Opto-Control (mCherry) or Opto-G3BP1 (mCherry) constructs were co-transfected with linear hygromycin marker (Clontech 631625) into U2OS cells using FuGENE 6 (Promega). 48 hr after transfection, 200 μg/ml hygromycin B (Thermo Fisher Scientific 10687010) was added to culture media for selection. mCherry-positive cells were selected using cell sorting to produce Opto-Control (mCherry) or Opto-G3BP1 (mCherry) stable cell lines. For efficient photoactivation, cells with high expression (top 10%) were selected using cell sorting. Filtered Opto-Control (mRuby) or Opto-G3BP1 (mRuby) viral supernatants and 8 μg/ml polybrene (Sigma H9268) were added to U2OS cells at ~50% confluency in 10 cm plates. mRuby-positive cells were selected using cell sorting to produce Opto-Control (mRuby) or Opto-G3BP1 (mRuby) stable cell lines.

iPSC neuron differentiation

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iPSC neurons were generated as described previously (Zhang et al., 2013) with modifications. iPSCs ((Re)Building a Kidney BJFF6) were dissociated with Gentle Cell Dissociation Reagent (Stemcell Technologies 07174) and 300,000 iPSCs were seeded into one Matrigel (Corning 354277)-coated well of a six-well plate in mTeSR medium (Stemcell Technologies 85850) containing 10 µM ROCK inhibitor (Stemcell Technologies 72302). The next day, the medium was changed to mTeSR medium.

To generate neurons expressing mRuby-tagged Opto-G3BP1 or Opto-Control, lentiviruses encoding Ngn2 and rTTA were added to the medium at MOI = 4, respectively, in the presence of hexadimethrine bromide (4 µg/ml; Sigma-Aldrich H9268) and the medium was changed 24 hr after transduction. When transduced iPSCs reached 75% confluency, 1 µg/ml of doxycycline hyclate (Sigma-Aldrich D9891) was added to mTeSR medium to induce Ngn2 expression. At day 2 of induction, iPSCs were dissociated with Gentle Cell Dissociation Reagent and 150,000 cells were seeded onto coverslips in one well of a 24-well plate or 4-well Nunc Lab-Tek chambered coverglass (Thermo Fisher Scientific 155382) coated with Poly-L-ornithine/laminin/fibronectin (Sigma-Aldrich P4957; Sigma-Aldrich L2020; Sigma-Aldrich F4759 (Richner et al., 2015)), and cultured in BrainPhys neuronal medium (Stemcell Technologies 05790) containing 1 × N2 (Thermo Fisher Scientific 17502048), 1 × B27 (Thermo Fisher Scientific 12587010), 20 ng/ml BDNF (Peprotech 450–02), 20 ng/ml GDNF (Peprotech 450–10), 500 µg/ml Dibutyryl cyclic-AMP (Sigma-Aldrich D0627), 200 nM L-ascorbic acid (Sigma-Aldrich A0278), 1 µg/ml natural mouse laminin (Thermo Fisher Scientific 23017–015), 1 µg/ml doxycycline, and 1 µg/ml puromycin (Thermo Fisher Scientific A1113803). Opto-Control (mRuby) or Opto-G3BP1 (mRuby) lentiviruses and 4 μg/ml hexadimethrine bromide (Sigma H9268) were added to iPSC neurons at 3–5 DIV. Media was changed approximately 12 hr after transduction and then half-changed every other day until the assay was performed.

To generate doxycycline-inducible iPSC-derived neurons with inducible expression of mCherry-tagged Opto-Control or Opto-G3BP1, lentiviruses encoding Ngn2, rTTA, and Dox-Opto-Control or Dox-Opto-G3BP1 were added to the medium at ~MOI = 4, respectively, in the presence of hexadimethrine bromide (4 µg/ml), and the medium was changed 24 hr after transduction. iPSCs were dissociated with Gentle Cell Dissociation Reagent and 150,000 cells were seeded into coverslips in one well of a 24-well plate or 4-well Nunc Lab-Tek chambered coverglass coated with Matrigel/Poly-L-ornithine/laminin/fibronectin and cultured in BrainPhys neuronal medium for 7 days. iPSC neuron cultures were maintained in BrainPhys neuronal medium and half-changed every other day until the assay was performed.

Blue-light LED treatment

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Cells (30–60% confluency) were transferred into blue light illumination at ~2 mW/cm2 using custom-made LED arrays in a humidified incubator with 5% CO2 with blue-light LED array for continuous blue light stimulation. Custom-made LED arrays were arranged with a flexible LED strip light (Ustellar). The light intensity of LED arrays was measured by a power meter (ThorLabs S170C).

Live-cell imaging

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All live-cell imaging experiments were performed using a Marianas 2 spinning disk confocal imaging system except overnight images of cell viability assays (described below). Images were acquired using a 63×/1.4 Plan Apochromat objective. Cells were plated in 4-well Nunc Lab-Tek chambered coverglass (Thermo Fisher Scientific 155382). Before imaging, the medium was changed to FluoroBrite DMEM medium (Thermo Fisher Scientific A1896701) with 10% fetal bovine serum and 1X GlutaMAX. During imaging, cells were maintained at 37°C with an environmental control chamber. Definite focus was used during the live-cell imaging. For one-time photoactivation, indicated cells were initially photoactivated by a 5 ms pulse of 488 nm laser illumination at 55% of maximum laser power, then imaged every 1 s thereafter with a 561 nm laser. For intermittent activation, cells were intermittently exposed to a 488 nm blue light (100 ms, 90% laser power, power density 6.3 W/cm2) followed by image acquisition with a 561 nm channel. Images were analyzed with SlideBook 6 software. Laser power intensity was measured by a power meter (ThorLabs S170C).

Western blotting

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Cells were collected using PBS and lysed for 10 min on ice using RIPA buffer (25 mM Tris-HCl (pH 7.6), 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, 0.1% SDS; Pierce, 89901) supplemented with proteinase inhibitor cocktail (Roche 1186153001) and PhosSTOP (Roche 04906845001). Samples were centrifuged for 20 min at 4°C at 14,000 rpm. 4X NuPAGE LDS sample buffer (Thermo Fisher Scientific NP0008) was added to the supernatant and samples were boiled for 5 min. Samples were run in 4–12% NuPAGE Bis-Tris gels (Invitrogen) and transferred to nitrocellulose membranes using an iBlot 2 transfer device (Thermo Fisher Scientific). Membranes were blocked with Odyssey blocking buffer (LI-COR) and then incubated with primary antibodies. Following incubation with dye-labeled secondary antibodies, signals were visualized using an Odyssey Fc imaging system (LI-COR). Primary western blot antibodies were anti-β-actin (Santa Cruz Biotechnology sc-1616), anti-eIF2α (Santa Cruz Biotechnology sc-133132), anti-phospho-eIF2α (Cell Signaling 3597S), anti-mCherry (Abcam 167453), and anti-G3BP1 (BD biosciences 6111126). Secondary western blot antibodies were IRDye 800CW/680RD (LI-COR) used at a dilution of 1:15,000.

Immunofluorescence

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Cells were grown in 8-well chamber slides (Millipore). Following the indicated stimulation, cells were fixed with 4% paraformaldehyde (Electron Microscopy Science) in PBS for 10 min at room temperature, permeabilized with 0.2% Triton X-100 in PBS for 10 min at room temperature, and then blocked with 10% normal goat serum (Life Technologies 50062) or 5% BSA for 1 hr at room temperature. Samples were incubated with primary antibodies in blocking buffer overnight at 4°C. Samples were then washed three times with PBS and incubated with secondary antibody for 1 hr at room temperature. Primary antibodies were anti-PABP (Abcam ab21060), anti-G3BP1 (BD Biosciences 611126), anti-eIF4G (Santa Cruz Biotechnology sc-11373), anti-TDP-43 (Proteintech 12892–1-AP), anti-phospho-TDP-43 (M01) (Cosmo Bio CO TIP-PTD-MO1), anti-phospho-TDP-43 (P01) (Cosmo Bio CO TIP-PTD-PO1), anti-VCP (BD Biosciences 612183), anti-amyloid-oligomer A11 (Thermo Fisher Scientific AHB0052), anti-ubiquitin (Dako, Z0458), anti-SQSTM1 (Abcam ab56416), anti-MAP2 (Sigma M9942), anti-TIA1 (Santa Cruz Biotechnology sc-1751), anti-TIAR (BD Biosciences 610352), anti-eIF3η (Santa Cruz Biotechnology sc-16377), anti-ataxin 2 (Proteintech 21776–1-AP), anti-FUS (Bethyl Laboratories A300-302A), anti-OPTN (Proteintech 10837–1-AP), and anti-GLE1 (Abcam ab96007). Secondary antibodies were Alexa Fluor 488/555/647 (Life Technologies). For microscopic imaging, slides were mounted with ProLong Gold Antifade Mountant with DAPI (Invitrogen). Images were captured using a Leica TCS SP8 3X confocal microscope with a 63x oil objective.

Fluorescence recovery after photobleaching

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Cells were first stimulated with a blue-light laser (power density ~4.5 W/cm2) for 3 mins to initiate granule formation. Regions of interest expressing Opto-Control, Opto-Control (olig), Opto-G3BP1, or G3BP1-GFP were then photobleached and mCherry or GFP signal intensity was measured before and after photobleaching.

Fluorescence in situ hybridization

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Cells were fixed with 4% paraformaldehyde at room temperature for 10 min and then washed twice with PBS. 70% (v/v) EtOH was then added and cells were stored at 4°C overnight. Cells were then washed twice with wash buffer (2x SSC with 10% formamide in RNase-free water). Following aspiration of the wash buffer, cells were incubated with hybridization buffer (2x SSC, 10% v/v deionized formamide, 10% (w/v) dextran sulfate, 2 mM vanadyl ribonucleoside complex, 1 mg/ml yeast tRNA (Ambion AM7119), 0.005% BSA (Ambion AM2616) with 1 ng/μl 5′ labeled FAM-oligo(dT20) probes (Genelink 26-4620-02) at 37°C overnight. Cells were then washed 3 times with pre-warmed wash buffer at 37°C.

Crystal violet assay

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Cells were seeded at ~20% confluency in 6-well plates and grown for 24 hr before exposure to LED blue light. At the indicated treatment time, media was aspirated and replaced with staining solution (0.05% (w/v) crystal violet, 1% formaldehyde, 1% methanol in 1X PBS) for 20 min at room temperature followed by three washes with water.

CellTiter-Glo 2.0 cell viability assay

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This assay determines the number of viable cells by measuring ATP, which indicates the presence of metabolically active cells. Cells were seeded at 4–5 × 103 cells/well in 96-well plates one day before exposure to blue-light LED. Following blue light exposure, cells were measured using the CellTiter-Glo 2.0 assay kit (Promega G9242) per the manufacturer’s instructions.

Neuron viability imaging

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Opto-Control and Opto-G3BP1 mRuby neurons were imaged on a DMI8 Widefield Microscope (Leica) with a 20x Plan Apo 0.80NA air objective using LAS X 3.4.2.18368 software (Leica). By saving the stage positions, a tilescan capture was taken in the same location every 2 hr using the 561 nm filter at 600 ms exposure. Between imaging, neurons were placed in the blue-light LED incubator until the next time point. Stitching was performed in LAS X, with each merged image totaling an area of ~37.82 mm2.

Overnight live-cell imaging

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Overnight live-cell imaging experiments were performed with an Opterra II Swept Field confocal microscope (Bruker) using Prairie View 5.4 Software. Opto-Control and Opto-G3BP1 cells were plated in the middle two wells of a 4-well Lab-Tek chambered coverglass (Nunc) at ~20% confluency the day prior to imaging. Immediately before imaging, the medium was changed to FluoroBrite DMEM medium supplemented with 10% fetal bovine serum and 1X GlutaMAX. During imaging, cells were maintained at 37°C and supplied with 5% CO2 using a Bold Line Cage Incubator (Okolabs) and an objective heater (Bioptechs). Imaging was performed using a 60x Plan Apo 1.40NA oil objective and Perfect Focus (Nikon) was engaged for the duration of the capture. Continuous activation data was acquired with a script made in Prairie View. The script was set to image the 561 nm channel with 100 ms exposure at 80 power in a multipoint capture once, followed by imaging the 445 nm channel with 2000 ms exposure at 200 power in a multipoint capture five times. This script was repeated continually for the duration of the experiment. Three fields of Opto-Control and Opto-G3BP1 cells, each with similar expression levels, were chosen per experiment. Analysis was performed using ImageJ.

Droplet digital PCR

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The QX200 droplet digital PCR (ddPCR) system (Bio-Rad) was used to measure gene expression levels in iPSCs and iPSC-derived neurons. The reaction was carried out in 20 μl emulsion PCR reactions that contain 20,000 droplets. Total RNAs were extracted by RNeasy Mini kit (Qiagen, 74104) and genomic DNA was removed by column by RNase-Free DNase (Qiagen, 79254). The ddPCR assay consisted of the following components: 1 × One-Step RT-ddPCR mix for probes (Bio-Rad, 1864021), forward primer (900 nM), reverse primer (900 nM), probe (FAM or HEX, 250 nM), nuclease-free water, and 5 ng RNA. All primers and probes were purchased from Thermo Fisher Scientific (MAP2, Hs00258900; OCT4, Hs04260367; BRN2, Hs00271595; FOXG1, Hs01850784; SYN1, Hs00199577) or Bio-Rad (RPP30, 10031228). Droplets were generated in a droplet generator (Bio-Rad) and PCR was performed in a C1000 Touch thermal cycler (Bio-Rad) according to the manufacturer's recommendation. After PCR, readout of positive versus negative droplets was performed using a QX200 droplet reader (Bio-Rad) and calculated by QuantaSoft software version 1.7.4.0917 (Bio-Rad).

Statistical analysis

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p>0.05 was considered not significant. *p≤0.05, **p<0.01, ***p<0.001, and ****p<0.0001 by two-tailed Student’s t test, one-way ANOVA or two-way ANOVA with post-test as indicated in figure legends, or Log-rank (Mantel-Cox) test as appropriate. Statistical analyses were performed in GraphPad Prism or Excel.

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Decision letter

  1. Hong Zhang
    Reviewing Editor; Institute of Biophysics, Chinese Academy of Sciences, China
  2. Huda Y Zoghbi
    Senior Editor; Texas Children's Hospital, United States

In the interests of transparency, eLife includes the editorial decision letter, peer reviews, and accompanying author responses.

[Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed.]

Thank you for submitting your article "Persistent or repetitive assembly of OptoGranules is cytotoxic and reveals the evolution of stress granules to ALS-FTD pathology" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom was the Reviewing Editor, and the evaluation has been overseen by a Senior Editor. The reviewers have opted to remain anonymous.

The Reviewing Editor has highlighted the concerns that require revision and/or responses, and we have included the separate reviews below for your consideration. If you have any questions, please do not hesitate to contact us.

Major concerns:

1) The dynamic recruitment of other stress granule components to OptoGranules should be characterized in detail. It is important to determine whether they are sequentially recruited to OptoGranules.

2) We strongly encourage the authors to include quantification data in the revised version: for example,% of cells with stress granules plotted over time after induction in Figure 2A and 2B should be included. It is hard to assess the degree of recruitment of different factors without any quantification (i.e. just from pictures). Figure 4 also suffers from this lack of quantification. Although images in panels e-h are representative of 3 independent experiments, a clear indication of the% of Optogranules which colocalise with pTDP-43, ubiquitin, P62 etc. and how this changes with time is crucial.

Separate reviews (please respond to each point):

Reviewer #1:

Liquid-liquid phase separation drives the assembly of stress granules (SGs) in response to a variety of exogenous stressors. Accumulation of SGs is associated with the pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The causal relationship has not been firmly demonstrated. In this elegant study, Zhang et al. developed a light-inducible stress granule system, termed OptoGranules, that allows the authors to control the dynamics and composition of SGs in living cells. Using this system, the authors found that OptoGranules contain canonical stress granule components. Zhang et al. further showed that persistence of OptoGranules is cytotoxic, recapitulating the pathology of ALS-FTS. Overall, the findings are interesting. This manuscript is suitable for publication in eLife after appropriate revisions.

1) The dynamic recruitment of other stress granule components to OptoGranules should be characterized in more detail. It is important to determine whether they are sequentially recruited to OptoGranules.

2) The authors showed that the formation of FUS-, TDP-43- or TIA1-based OptoDroplets does not recapitulate the formation of stress granules. OptoDroplets do not colocalize with G3BP1-GFP and PABP. Do OptoDroplets contain other components of SGs such as VCP, p62 and OPTN? Mutations in these ALS disease genes cause accumulation of SGs. Does mutant FUS, TDP-43 or TIA1 induce SG formation in this system?

Minor Comments:

In Figure 1B, enlarged images showing the disassembly of granules could be presented. Discrete granules are hard to see over high expression background.

Reviewer #2:

The paper by Zhang et al. describes the formation of Optogranules induced by blue light. These Optogranules consist of G3BP linked to a light-sensitive CRY2/PHR domain. It is demonstrated that the Optogranules contain polyadenylated mRNAs and stress granule markers (in contrast to the Optodroplets formed based on FUS, TDP-43 and TIA1). Apart from the characterization of the Optogranules, repetitive stimulation of cells with blue light induces cell death. This also leads to a change in the composition of the Optogranules as, amongst others, phospho-TDP43 and ubiquitin stain positive in these Optogranules. In general, this is an interesting paper and most of the experiments are convincingly performed. However, there are a few important issues that need to be addressed and that will further strengthen the conclusions of the paper.

Major comments

– A major concern is that at least some of the data presented in this manuscript are very qualitative in nature. A lot of what is presented is based on co-stainings of a few cells and colocalisation in (part of) one cell. Despite the fact that these are most likely typical examples, one always worries that there could be a selection bias and that stainings are more likely to be selected if these are in accordance with what one expects. With the data provided, it is impossible to judge whether for instance the maturation of the droplets into droplets that are positive for phospho-TDP-43 and ubiquitin, as well as for other markers, is a valid observation. These changes are nicely shown in a schematic overview in Figure 3E and Figure 4D. However, it is not clear on how many cells/droplets this is based and whether there was a real time-dependent quantification underlying these data. Especially Figure 4 suffers from this lack of quantification. Although images in panels e-h are representative of 3 independent experiments, a clear indication of the% of Optogranules which colocalise with pTDP-43, ubiquitin, P62 etc. and how this changes with time is crucial.

– Stress granules are thought to be transient structures, forming rapidly in response to stress. Although the authors demonstrate that Optogranules form rapidly in response to blue light, in seconds or minutes (Figure 1B, Figure 1G), it is unclear why the authors switch from an approx. 5 min induction to a 6 h induction paradigm (Figure 1H to 1J) when demonstrating recruitment of known stress granule proteins. Are these other stress granule proteins only recruited in response to sustained assembly of opto-G3BP1? The authors should look at earlier time points. The same induction paradigm is also used in Figure 2.

- It is not so clear whether it is indeed the change over time of the composition of the Optogranules after repetitive stimulation with blue light that is responsible for the induction of the cell death. Some additional experiments should be performed to clarify this issue. Is the dynamics of the formation and disassembly of Optogranules changing over time? It should also be investigated whether there is an effect of repetitive stimulation of the cells on the physicochemical properties of the stress granules. How is fluorescence for instance recovering after photobleaching?

– The added value of the iPSC related experiments is not so clear. It should be clarified in more detail in which sense the Optogranules are different in these cells in comparison to the Optogranules in the U2OS cells. At present, the overall impression is that what is concluded from these experiments is very similar (identical) to what was observed in the U2OS cells. If so, one wonders how the described process could lead to selective neuronal death.

Minor comments:

– The quality of some of the figures seems suboptimal (could be due to the conversion to a pdf). One clear example is the first figure illustrating the formation of Optogranules. While it is clear in the movie, it is much less clear to observe the individual droplets in Figure 1B.

– It is indicated that the Optocontrol construct also forms a modest amount of nuclear and cytoplasmic clusters. It is not clear what the identity of these clusters is. Can this be determined and discussed in more detail?

– No Opto-control is provided for the experiment in Figure 1G.

– Figure 1—figure supplement 2: The length of time that cells were exposed to blue light is not stated. Was this the same 6 h induction used in Figure 1?

– Figure 2A and 2B, quantification would be more convincing. e.g.% of cells with stress granules plotted over time after induction. The experiment should also be controlled using the Opto-control construct.

– Figure 2C and D: It is concluded that the Optogranule assembly is independent of the regulation by eIF2alpha. This important observation should be discussed in more detail.

– Figure 2E: Not clear whether the same blot was reprobed or whether different blots are shown for phospho-eIF2alpha and eIF2alpha. Why is the eIF2alpha at the top (and not in the middle) of the part of the blot that is shown?

– All stress granule components that were studied colocalised with the Optogranules. One obvious candidate that is missing in this long list is FUS (Results section). Was FUS present in these Optogranules?

– Figure 3A: What is the effect of continuous blue light on the U2OS cells?

– Figure 3C and D: From the Kaplan-Meier plots one can estimate that approximately 10-15 cells are followed after induction of the Optogranule formation. How were these cells selected and how many were selected in the three different independent experiments.

– Figure 3C and D: Is there a statistical difference between the cell death induced by the induction of chronic persistent granules or after induction of chronic intermittent granules?

– Figure 3: On the Y-axis of panel c and d, the numbers are missing. It is also not clear whether the blue boxes are based on a quantification or whether these boxes represent what is expected (should be specified in the legend).

– Figure 4: It is unclear whether persistent induction of Optogranules causes increased phosphorylation of TDP-43 or simply recruitment of a population which is already present in the cell. The authors should quantify the total levels of phospho-TDP-43 before and after chronic induction of Optogranule assembly to determine whether levels are increased.

– More details should be provided on the nature/quality of the neurons that are differentiated from the iPSCs. Are these cortical neurons? How pure are these neuronal cultures? Are these neurons electrically active?

Additional data files and statistical comments:

It is not always clear whether the correct statistics is used. One example is Figure 3B. A Student t-test doesn't seem to be the correct way to evaluate whether these differences are statistically different. Moreover, as these are box plots, it seems unlikely that the variation is indicated as standard deviations (s.d.) as is indicated in the figure legend.

Reviewer #3:

Very interesting paper – extremely easy to read and parse. Important for field, enjoyed reading, lots of interesting insights.

Some comments:

* It is hard to assess the degree of recruitment of different factors without any quantification (i.e. just from pictures). For example, it is not clear to be that there is bona fide p62 recruitment in neurons (Figure 4H). If this were a normal review I would insist this must be quantified to some degree (e.g. pixel mutual information using an intensity threshold as a binary mask, given intensities are hard to interpret).

* There are three distinct modes of illumination: continuous (Figure 3A), chronic persistent (Figure 3C) and chronic intermittent (Figure 3D). It is difficult to determine which is used in which experiment. I would strongly suggest standardizing this and ensuring each experiment is clearly labelled regarding which regime is used. Without this interpreting the data (for the reader) becomes difficult.

* The OptoXXX language used is a little confusing. In the Shin et al. paper, OptoDroplets refers to the general system of a Cry2 domain fused to something:

"Here, we introduce an optogenetic platform that uses light to activate IDR-mediated phase transitions in living cells. We use this 'optoDroplet' system to study condensed phases driven by the IDRs of various RNP body proteins"

Here, OptoGranules refer to the physical cellular assemblies (to distinguish them from stress granules – which makes semantic sense) and OptoG3BP1 is an example of an OptoDroplet construct that contains G3BP1. The fact that the OptoDroplet work is not used to introduce the technology is odd. The results determined here are of significant biological relevance and interest, but the approach is fundamentally the OptoDroplet platform applied to a different protein. The fact that OptoDroplets are only introduced once the OptoGranule system has been described:

'These results contrast with observations made with light-induced aggregation of so-called "OptoDroplets," which nicely…'

Gives the impression that this is a different approach system, which is not the case (Figure 1A from this paper and 1A from Shin et al. are essentially interchangeable), and comes across as a little disingenuous. This was a general sentiment I heard from various places when the original preprint went up. It is surprising to me, because all of the exciting results pertain to the biology, not to the method, so it's unclear why the approach is introduced without basically saying "Here we extended the OptoDroplet system to examine the role of G3BP1 in nucleating stress granules…" or something to this effect.

Minor Comments:

* It would be useful to draw the schematic (Figure 1A) with the domains proportional to their number of amino acids

* Cry2+mCherry = ~840 amino acids (96 kDa), while NTF2 = 142 amino acids (16 kDa)

* This, of course, may be impractical, in which case simply including the regional size in number of amino acids would be sufficient

* Is the absence of SGs in response to the double G3BP1/2 knockout a true absence of stress granules, or an absence of assemblies with G3BP1/Tia1/PAB1 markers – have other markers been checked?

* "…insinuate into stress granules and other membrane-less organelles" – not sure insinuate has an appropriate meaning here? 'Infiltrate' perhaps?

* Figure 1—figure supplement 1B is the same as part of Figure 1A?

* "Opto-Control expression remained diffuse, with a modest amount of nuclear and cytoplasmic clusters (Figure 1B and Supplementary Video 1)." – the text is intriguing, though it wasn't obviously clear to me where these cytoplasmic clusters are in Figure 1B? But assuming you do see some level of clusters, why is an obligate dimer able to lead to any degree of cluster formation? I would have expected dimers to be far far below the resolution limit such that monomer/dimer Opto-Control should be equally diffuse

* When the OptoControl is off it appears to partition into the nucleus (Figure 1H, 1I, 1J) but when activated it is strongly excluded. Both monomeric and dimeric version should be larger than the threshold size for free permeability into the nucleus sans an NLS, so its not clear how/why light should be changing the distribution – some explanation of this would be useful (i.e. does this imply there are additional un-characterized responses to blue-light stimulation?).

* Are the expression levels of OptoG3BP1 comparable to endogenous G3BP1? I realize expression is clearly a tunable parameter as addressed in Figure 2, so it would be useful, as a reference, to mention the expression levels of endogenous protein here.

* "Expression of Opto-constructs using full-length TDP-43 or FUS [CRY2PHR-mCherry-TDP-43(FL); CRY2PHR-mCherry-TDP-43(FL)] did not produce cytoplasmic clusters with blue light activation" (minor point – I believe the second instance here should be CRY2PHR-mCherry-FUS(FL))

This is a very interesting result for two reasons

1) It’ not clear to me why FL-FUS OptoDroplets should not form assemblies, especially given recent reports that FL FUS assemblies much more readily than the LCD alone. Any thoughts on this in the discussion would, I think, be very useful. [1]

2) Recent work has shown that the NTD of TDP43 forms dimers that are necessary for phase separation in full-length TDP-43. In agreement with this, the CRY2 dimerization domain appears able to replace this N-terminal domain and give rise to droplets, HOWEVER, if the N-terminal domain is present (i.e. in CRY2PHR-mCherry-TDP-43(FL)) droplet formation is suppressed – any possible mechanism here would be useful to address – specifically, how does the ADDITION of a dimerization domain between CRY2 and the C-terminal portion of TPD43 suppress assembly?

* These questions are directly related to the comparison of other optoDroplet constructs

* Not sure how to interpret the Opto-G3BP1 vs G3BP1-GFP RNA binding data? Naively from the description of the RNA binding assay I would have expected 1) cross-linking to cause G3BP1 in stress granules to extensively cross-link with local RNAs, while under non-stress/non OptoGranule inducing conditions there would be minimal RNA cross-linking and 2) for Opto-G3BP1 and G3BP1-GFP to be similar. Instead, the data appear to show that you get extensive and essentially identical RNA binding under stressed and non-stressed conditions, and that Opto-G3BP1 and G3BP1-GFP have different RNA binding profiles. Similarly, not sure how to interpret the western blot associated with 2b – it would be useful to explicitly annotate what the bands are. This is almost certainly just a limitation of my understanding of the experimental setup, but it seems at least plausible others might also be confused…

* In the protein name SQSTM1 is used, while in Figure 3 p62 is used – this may confusing for people unfamiliar with the protein, so I'd suggest a consistent naming scheme

* I found the mCherry vs. mRuby optoG3BP1 section confusing on the first read, as it was initially unclear why both would be needed. I would suggest splitting this into a 'first we used mRuby-optoG3BP1…', then once this has been completed, explain why an inducible system is needed and then introduce the inducible mCherry variant.

* Why is the pTDP-43 recruitment to SGs in neurons so much weaker than in U2OS cells? In U2OS see reasonable recruitment just 1 hour in, with robust recruitment after 2 hours. In neurons after 5 hours (4g) there is basically no co-localization with optoG3BP1, and then after 6 robust co-localization is observed.

[1] Qamar, S., Wang, G., Randle, S.J., Ruggeri, F.S., Varela, J.A., Lin, J.Q., Phillips, E.C., Miyashita, A., Williams, D., Ströhl, F., et al. (2018). FUS Phase Separation Is Modulated by a Molecular Chaperone and Methylation of Arginine Cation-π Interactions. Cell 173, 720-734.e15.

[2] Wang, A., Conicella, A.E., Schmidt, H.B., Martin, E.W., Rhoads, S.N., Reeb, A.N., Nourse, A., Montero, D.R., Ryan, V.H., Rohatgi, R., et al. (2018). A single N‐terminal phosphomimic disrupts TDP‐43 polymerization, phase separation, and RNA splicing. EMBO J. e97452.

https://doi.org/10.7554/eLife.39578.021

Author response

The Reviewing Editor has highlighted the concerns that require revision and/or responses, and we have included the separate reviews below for your consideration. If you have any questions, please do not hesitate to contact us.

Major concerns:

1) The dynamic recruitment of other stress granule components to OptoGranules should be characterized in detail. It is important to determine whether they are sequentially recruited to OptoGranules.

2) We strongly encourage the authors to include quantification data in the revised version: for example,% of cells with stress granules plotted over time after induction in Figure 2A and 2B should be included. It is hard to assess the degree of recruitment of different factors without any quantification (i.e. just from pictures). Figure 4 also suffers from this lack of quantification. Although images in panels e-h are representative of 3 independent experiments, a clear indication of the% of Optogranules which colocalise with pTDP-43, ubiquitin, P62 etc. and how this changes with time is crucial.

We thank the reviewers for their constructive critique of this manuscript. The reviewers raised some excellent points, which we address below.

We also wish to highlight our answer to one question from the reviewers regarding the difference between OptoDroplets and OptoGranules. These are similar insofar as both types of assemblies are initiated with optically induced phase separation. Indeed, it is this similarity that suggested the name “OptoGranules,” since they were inspired by and built upon observations made by Shin et al. regarding OptoDroplets. Beyond this similarity, however, OptoDroplets and OptoGranules are fundamentally different. This distinction is straightforward when considering evidence that biomolecular condensates are composed of clients and scaffolds that play fundamentally different roles in the assembly and maintenance of these condensates. In unpublished work that strongly informed the development of OptoGranules, we identified G3BP as a uniquely essential central scaffold protein for stress granules, in contrast to TIA1, TDP-43, FUS, and many others, which are client proteins (Yang, Mathieu et al., in review). Please note, this manuscript has been made available for assessment by the editors and reviewers. In Yang, Mathieu et al., we show that G3BP dimerization and multivalent RNA binding drives phase separation with long, single- stranded mRNAs to form complexes that seed stress granule assembly. Moreover, this work revealed that the native dimerization element in G3BP could be functionally replaced by heterologous dimerization domains, which informed the design of Opto-G3BP1. In fact, simply tagging G3BP1 with CRY2 does not produce a fusion protein capable of efficiently producing stress granules in response to optical induction. In the present manuscript, we show that enforced phase separation of client proteins (TIA1, TDP-43, and FUS) using CRY2 generates OptoDroplets, which are relatively homogenous intracellular condensates, thereby confirming the results of Shin et al., but we also demonstrate that these are not stress granules. This makes sense since client proteins often reside in multiple biomolecular condensates with distinct identities. In contrast, enforced phase separation of a scaffold protein initiates the cascade of events that seeds the assembly of a full-fledged, complex stress granule, which we term an OptoGranule. Thus, an important takeaway from this work is the critical role of specific scaffolding elements in establishing and maintaining the identity of specific biomolecular condensates.

Separate reviews (please respond to each point):

Reviewer #1:

Liquid-liquid phase separation drives the assembly of stress granules (SGs) in response to a variety of exogenous stressors. Accumulation of SGs is associated with the pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The causal relationship has not been firmly demonstrated. In this elegant study, Zhang et al. developed a light-inducible stress granule system, termed OptoGranules, that allows the authors to control the dynamics and composition of SGs in living cells. Using this system, the authors found that OptoGranules contain canonical stress granule components. Zhang et al. further showed that persistence of OptoGranules is cytotoxic, recapitulating the pathology of ALS-FTS. Overall, the findings are interesting. This manuscript is suitable for publication in eLife after appropriate revisions.

1) The dynamic recruitment of other stress granule components to OptoGranules should be characterized in more detail. It is important to determine whether they are sequentially recruited to OptoGranules.

The manner in which individual constituents are recruited to stress granules remains poorly defined, although it is clear than many mRNAs and associated RNA-binding proteins are “recruited” simultaneously in bulk because they are part of mRNPs that constitute the primary content of stress granules. Other proteins likely participate in the initial phase transition that drives stress granule assembly, and thus are also “recruited” from the outset. Indeed, dynamic imaging in Figure 1G shows simultaneous recruitment of TIA1 and G3BP1 to stress granules presumably for this reason. Yet, there are >400 distinct protein constituents and >1800 distinct RNAs that have been reported in stress granules. As the reviewer suggests, some constituents are sequentially recruited (which we take to mean that there is a temporal delay in their recruitment after a microscopically visible stress granule is evident). For example, we have demonstrated delayed recruitment of the ubiquitin-binding proteins p62/SQSTM1 and VCP, and this is preceded by the appearance of ubiquitin signal in OptoGranules (Figures 3G-I and 4H-I). The clear implication of this finding is that a specific post-translational modification results in the subsequent recruitment of constituents that were not initially part of an RNP and we are anxious to learn how common this is. Chemical modifications of RNA or protein may be a general mechanism contributing to both delayed recruitment of constituents or time-dependent maturation of stress granules (as shown by reduced dynamics in mature stress granules in new Figure 3—figure supplement 1C-D). The OptoGranule system provides a tool to address these and many other fundamental questions about the molecular mechanism underlying RNP granule assembly in general, stress granule assembly in particular, and the relationship of stress granules to a wide variety of biological functions. These questions go beyond the scope of this initial report, which aims to illustrate (1) proof of concept that optically driven aggregation of a key scaffolding element can seed assembly of a complete membrane-less organelle, and (2) that protracted stress granule assembly is cytotoxic and recapitulates features of a specific neurodegenerative disease.

2) The authors showed that the formation of FUS-, TDP-43- or TIA1-based OptoDroplets does not recapitulate the formation of stress granules. OptoDroplets do not colocalize with G3BP1-GFP and PABP. Do OptoDroplets contain other components of SGs such as VCP, p62 and OPTN? Mutations in these ALS disease genes cause accumulation of SGs. Does mutant FUS, TDP-43 or TIA1 induce SG formation in this system?

No, as shown in new Figure 1—figure supplement 4D-E, J OptoDroplets formed from light-induced aggregation of TDP-43, FUS, or TIA1 do not recruit or colocalize with p62/SQSTM1, VCP, or OPTN, just as they do not recruit canonical stress granule constituents. This is an important point and speaks to a larger question addressed partially in this manuscript but more explicitly in a companion manuscript currently under review (Yang, Mathieu et al., in review). Please note, this manuscript has been made available to eLife for assessment by editors and reviewers. Quoting from this companion manuscript:

“RNP granules are complex structures composed of hundreds of RNAs and proteins. Although it has become evident as a general principle that RNP granule assembly likely reflects cooperative protein-protein, protein-RNA, and RNA-RNA interactions between the many constituents of these structures, the precise interactions required for specific types of RNP granules are almost entirely unknown. Moreover, the underlying mechanism(s) that permit distinct RNP granule identities to be established and maintained are largely enigmatic. For example, nuclear speckles and Cajal bodies can be clearly distinguished from one another by morphology, subcellular localization, constituents, and function. A similar distinction is evident for cytoplasmic P bodies and stress granules. Given that these biomolecular condensates share common principles of assembly, are built from highly similar (and sometimes overlapping) constituent RNA molecules and proteins, and remain in dynamic equilibrium with a shared milieu, how do these structures establish and maintain distinct identities?”

In brief, the answer to this question is that RNP granule assembly is initiated by a limited number of scaffolding molecules and cannot be recapitulated by enforced phase transition of any random constituent. For stress granules, a whole-genome screen identified G3BP as a uniquely essential scaffolding factor in initiating assembly and maintaining identity (Yang, Mathieu et al., in review). This scaffolding protein is distinct from other protein components of stress granules (e.g., TDP-43, FUS, TIA1), which we classify as “client” proteins. This is why optically induced phase separation of G3BP1, an essential scaffold for stress granules, initiates assembly of a complex organelle, whereas optically induced aggregation of other proteins or fragments, such as client proteins TDP-43, FUS, or TIA1, does not.

OptoDroplets (e.g., condensates formed by client proteins) also differ from OptoGranules (e.g., complex granules formed by scaffold proteins) also provide different advantages for experimental purposes. The former offers a generalizable approach to monitor the biophysical phase transition properties of proteins in cells and correlate those with behavior in reconstituted biochemical systems. The latter builds upon the experimental foundation of the OptoDroplet system to seed the formation of a specific complex membrane-less organelle by using optogenetic oligomerization of a specific, essential scaffolding protein. Thus, OptoGranules can be used to test specific hypotheses regarding the assembly, kinetics, and maturation of specific types of complex organelles.

Importantly, the OptoGranule system requires knowledge of both the identity of the critical scaffolding elements and how these elements contribute to assembly. In this case, we used our prior knowledge of G3BP1 and the mechanism of stress granule assembly to rationally design the seed for a stress granule. This approach is also likely to be generalizable as the identities of essential scaffolding proteins are identified for a variety of RNP granules.

To answer the reviewer’s related question regarding whether exogenous overexpression of mutant FUS, TDP-43, or TIA1 induces stress granule formation in this system, we show in new Figure 1—figure supplement 1B that overexpression of mutant FUS, TDP-43, or TIA1 induces stress granule formation in Opto-G3BP1 cell lines, as expected.

Minor Comments:

In Figure 1B, enlarged images showing the disassembly of granules could be presented. Discrete granules are hard to see over high expression background.

This is a good suggestion. We have now added enlarged images to expanded Figure 1B.

Reviewer #2:

The paper by Zhang et al. describes the formation of Optogranules induced by blue light. These Optogranules consist of G3BP linked to a light-sensitive CRY2/PHR domain. It is demonstrated that the Optogranules contain polyadenylated mRNAs and stress granule markers (in contrast to the Optodroplets formed based on FUS, TDP-43 and TIA1). Apart from the characterization of the Optogranules, repetitive stimulation of cells with blue light induces cell death. This also leads to a change in the composition of the Optogranules as, amongst others, phospho-TDP43 and ubiquitin stain positive in these Optogranules. In general, this is an interesting paper and most of the experiments are convincingly performed. However, there are a few important issues that need to be addressed and that will further strengthen the conclusions of the paper.

Major comments

– A major concern is that at least some of the data presented in this manuscript are very qualitative in nature. A lot of what is presented is based on co-stainings of a few cells and colocalisation in (part of) one cell. Despite the fact that these are most likely typical examples, one always worries that there could be a selection bias and that stainings are more likely to be selected if these are in accordance with what one expects. With the data provided, it is impossible to judge whether for instance the maturation of the droplets into droplets that are positive for phospho-TDP-43 and ubiquitin, as well as for other markers, is a valid observation. These changes are nicely shown in a schematic overview in Figure 3E and Figure 4D. However, it is not clear on how many cells/droplets this is based and whether there was a real time-dependent quantification underlying these data. Especially Figure 4 suffers from this lack of quantification. Although images in panels e-h are representative of 3 independent experiments, a clear indication of the% of Optogranules which colocalise with pTDP-43, ubiquitin, P62 etc. and how this changes with time is crucial.

Yes, quantitative information was collected in the course of conducting the presented experiments. This quantitative data, with accompanying statistical analyses, has now been added to the figures. With reference to the reviewer’s specific comments, we call attention to new Figure 3I and Figure 4I, which show quantification of stress granule markers over time.

A brief, but not unimportant note: OptoGranules do not “consist of G3BP linked to a light- sensitive CRY2/PHR domain.” In fact, simply tagging G3BP1 with CRY2 does not produce a fusion protein capable of efficiently producing stress granules in response to optical induction. For the system to work, one must replace the native dimerization element in G3BP with an optically inducible multimerization element. Moreover, OptoGranules are not merely droplets of G3BP1. Rather, enforced phase separation of G3BP1 initiates a cascade of assembly that results in the formation of a full-fledged, complex RNP granule that is indistinguishable from an endogenous stress granule. This is because G3BP1 is the essential protein scaffold of stress granules.

– Stress granules are thought to be transient structures, forming rapidly in response to stress. Although the authors demonstrate that Optogranules form rapidly in response to blue light, in seconds or minutes (Figure 1B, Figure 1G), it is unclear why the authors switch from an approx. 5 min induction to a 6 h induction paradigm (Figure 1H to 1J) when demonstrating recruitment of known stress granule proteins. Are these other stress granule proteins only recruited in response to sustained assembly of opto-G3BP1? The authors should look at earlier time points. The same induction paradigm is also used in Figure 2.

We used two different blue light sources depending on the experimental design and readout. Specifically, for live imaging experiments, in which stress granule dynamics were monitored in real time, including experiments with intermittent activation, we used a photoactivation laser tuned to 455 or 488 nm, which has a powerful energy density (~2.5 MW/cm2for one-time activation or > ~4.5 W/cm2 for repeated activations) in a defined region of interest. However, this approach allows only a few cells to be examined at one time. For experiments requiring larger numbers of cells and therefore necessitating a broader field of illumination, we switched to a blue-light LED array (37°C, 5% CO2, in a humidified incubator), which had a much lower energy density (~2 mW/cm2) and induced OptoGranule formation over a longer time frame. This approach was used for experiments in which cells were fixed and stained for subsequent quantitative assessment. Importantly, in both experimental approaches the recruitment of stress granule components matched the kinetics of OptoGranule assembly. We point the reviewer to Figure 1G, Supplementary Video 3, Figures 3F-3H, and Figures 4E-4F, in which we assessed recruitment of stress granule markers at earlier time points (1-4 minutes and 1-2 hours post-induction) compared to the 6-hour time point shown in Figures 1H-1J and Figures 2C-E (now Figures 2E-G). Specific laser powers and energy densities are now consistently described in the figure legends, and we have added clarification in the main text to signal when we use each of the two light sources.

– It is not so clear whether it is indeed the change over time of the composition of the Optogranules after repetitive stimulation with blue light that is responsible for the induction of the cell death. Some additional experiments should be performed to clarify this issue. Is the dynamics of the formation and disassembly of Optogranules changing over time? It should also be investigated whether there is an effect of repetitive stimulation of the cells on the physicochemical properties of the stress granules. How is fluorescence for instance recovering after photobleaching?

Yes, importantly, we see evidence of maturation of granules such that their dynamics diminish with time. We believe that this may relate to the evolution of pathological inclusions. We have quantified this data and now present these results in new Figure 3—figure supplement 1C and 1D.

Regarding the reviewer’s question about “whether it is indeed the change over time of the composition of the OptoGranules after repetitive stimulation with blue light that is responsible for the induction of the cell death,” there was a clear correlation between repetitive induction of OptoGranules and cell death, but the mechanism of that cell death is unknown at this point. We believe that cell death is related to the OptoGranules because (to the extent possible) we have eliminated the confounding elements of exogenous stressors to induce granules, controlled for misexpression of fluorescently tagged proteins, and controlled for blue light exposure. Whether death relates to the composition of the granules is an interesting suggestion, but remains speculative.

– The added value of the iPSC related experiments is not so clear. It should be clarified in more detail in which sense the Optogranules are different in these cells in comparison to the Optogranules in the U2OS cells. At present, the overall impression is that what is concluded from these experiments is very similar (identical) to what was observed in the U2OS cells. If so, one wonders how the described process could lead to selective neuronal death.

We wanted to document the phenomenology of OptoGranule assembly and evolution in two different cell types, one of which has direct relevance to disease. Indeed, the results are qualitatively the same in U2OS cells and the iPSC-derived neurons, although within the “chronic persistent” paradigm, the neurons (Figure 4C) showed cell death much sooner than the U2OS cells (Figure 3C). With respect to cell type-specific vulnerability, we do not currently have sufficient evidence to conclude that neurons have increased vulnerability to repetitive stimulation of stress granules. It should be noted that aberrant stress granules are also linked to non-neuronal cell pathology, such as is observed in muscle diseases.

Minor comments:

– The quality of some of the figures seems suboptimal (could be due to the conversion to a pdf). One clear example is the first figure illustrating the formation of Optogranules. While it is clear in the movie, it is much less clear to observe the individual droplets in Figure 1B.

We have optimized the images by reverting to the original high-resolution image files, including those shown in Figure 1B.

– It is indicated that the Optocontrol construct also forms a modest amount of nuclear and cytoplasmic clusters. It is not clear what the identity of these clusters is. Can this be determined and discussed in more detail?

We used two different Opto-Control constructs in this paper; one (“Opto- Control”) is a fusion protein of mCherry and wild-type CRY2, and the other (“Opto-Control (olig)”) is a fusion protein of mCherry and a mutant form of CRY2 (CRY2-olig) that forms abundant CRY2 clusters upon activation.

Like many proteins containing mCherry, the Opto-Control fusion protein undergoes a modest amount of nonspecific aggregation that is related to its degree of expression. Importantly, these clusters are negative for stress granule markers, including >10 proteins and polyA RNA (Figure 1H-J and data not shown). Furthermore, we affinity purified this protein and found by mass spectrometry that it does not associate with any stress granule proteins (data not shown).

To further challenge the negative results obtained with Opto-Control, we used Opto-Control (olig) to aggravate the aggregation of the fusion protein. The aggregates formed by Opto-Control (olig) were poorly dynamic by FRAP (new Figure 1—figure supplement 1D-F) and were negative for stress granule markers (new Figure 1—figure supplement 1C).

– No Opto-control is provided for the experiment in Figure 1G.

We now show the control experiment in new Figure 1—figure supplement 1C.

– Figure 1—figure supplement 2: The length of time that cells were exposed to blue light is not stated. Was this the same 6 h induction used in Figure 1?

In the resubmission, these images have now been incorporated into Figure 1—figure supplement 4. As detailed in the figure legend, cells were imaged after different time periods of blue light exposure, as appropriate. Images capturing live-cell GFP-G3BP1 fluorescence (panels B, C, I) were captured immediately after a 5-msec pulse by a blue-light laser. Images of cells that were fixed and stained for stress granule markers were captured after 2 hours (panels F, G) and 5 hours (panels D, E, J) of blue-light LED exposure depending on the time required for each marker to accumulate in OptoGranules.

– Figure 2A and 2B, quantification would be more convincing. e.g.% of cells with stress granules plotted over time after induction. The experiment should also be controlled using the Opto-control construct.

As noted above, quantitative information was collected in the course of conducting the experiments presented. With regard to the reviewer’s specific comments, we call attention to new Figures 2B and 2D.

– Figure 2C and D: It is concluded that the Optogranule assembly is independent of the regulation by eIF2alpha. This important observation should be discussed in more detail.

This is an important point that we now discuss more explicitly in the manuscript. Stress granule assembly may be initiated in response to a wide variety of stimuli, including viral infection, oxidative stress, heat shock, and proteasome inhibition. Recent studies have provided substantial insight into the molecular basis of stress granule assembly. Often, stress granule assembly is initiated through an accumulation of uncoated RNA in the cytoplasm. This can occur when stress signaling culminates in phosphorylation of the translation factor eIF2α, which inhibits translation initiation. Subsequent disassembly of translating polysomes and concomitant accumulation of uncoated, non-translating mRNAs favor stress granule assembly.

Alternatively, stress granule assembly may be initiated by oligomerization of the scaffolding protein G3BP, which bypasses the need for eIF2α phosphorylation. In brief, we have learned that stress granule assembly is driven by phase transition of G3BP with RNAs that have certain features (long, single-stranded, and limited secondary structure) (Yang, Mathieu et al., in review). When the collective protein-protein, protein-RNA, and RNA-RNA interactions breach a critical threshold, they undergo phase separation and initiate stress granule assembly. There are two ways to reach this threshold. The first and most common way is RNA-driven, as described above, and is based on increasing the concentration of RNA via inhibition of translation via phosphorylation of eIF2α. The second way to reach the critical threshold for phase transition is protein-driven, wherein oligomerization of G3BP increases valency for RNA binding. This latter mechanism is exploited in this manuscript, where oligomerization is forced through a CRY2- mediated interaction. As anticipated, this mechanism of stress granule assembly does require polysome disassembly, but does not involve the upstream step of phosphorylation of eIF2α.

– Figure 2E: Not clear whether the same blot was reprobed or whether different blots are shown for phospho-eIF2alpha and eIF2alpha. Why is the eIF2alpha at the top (and not in the middle) of the part of the blot that is shown?

In this figure panel (now Figure 2G) the same membrane was reprobed sequentially using antibodies corresponding to different species. The full membrane blotting data with serial antibodies are now shown in new Figure 2—figure supplement 1. Because the actin signal appears so closely above the eIF2α signal, the final cropped blot shows the eIF2α bands at the top of the cropped image. Methodological details have now been added to the figure legend.

– All stress granule components that were studied colocalised with the Optogranules. One obvious candidate that is missing in this long list is FUS (Results section). Was FUS present in these Optogranules?

Yes, FUS is present in OptoGranules, as now shown in new Figure 1—figure supplement 2G.

– Figure 3A: What is the effect of continuous blue light on the U2OS cells?

As shown in new Figure 3B, there is background toxicity associated with chronic exposure to blue light, which is unchanged by expression of Opto-Control. There is a significant increase in toxicity when cells express Opto-G3BP1, which we interpret as stress granule-dependent toxicity. Because of background toxicity associated with chronic exposure to blue light, we designed the “intermittent activation” paradigm to minimize the total dosage of light exposure, as described in the manuscript text.

– Figure 3C and D: From the Kaplan-Meier plots one can estimate that approximately 10-15 cells are followed after induction of the Optogranule formation. How were these cells selected and how many were selected in the three different independent experiments.

For the experiments shown in Figures 3C and 3D, we used live imaging to monitor stress granule dynamics in real time. To accomplish this, we used a 445-nm imaging laser and 60x Plan Apo 1.40NA oil objective, which provides a limited field of view. Opto- G3BP1 expression levels were measured using Prairie View software and cells with equivalent levels of Opto-G3BP1 expression were activated by blue-light laser. All activated cells were included in the analysis. All details are included in the figure legends (Figure 3C: n = 26 for Opto-Control and n = 28 for Opto-G3BP1; Figure 3D: n = 7 for Opto-Control and n = 10 for Opto-G3BP1).

– Figure 3C and D: Is there a statistical difference between the cell death induced by the induction of chronic persistent granules or after induction of chronic intermittent granules?

We found no statistically significant difference in the amount of cell death caused by the induction of chronic persistent granules compared to that caused by induction of chronic intermittent granules. These results are now shown in new Figure 3—figure supplement 1A. However, it should be noted that in the chronic persistent stress granule paradigm, the cells are exposed to much more blue light. Indeed, this is why we developed the chronic intermittent paradigm to minimize blue light exposure.

– Figure 3: On the Y-axis of panel c and d, the numbers are missing. It is also not clear whether the blue boxes are based on a quantification or whether these boxes represent what is expected (should be specified in the legend).

As now clarified in the legend, the left panels are schematics that represent the design of the light induction paradigm (blue boxes) and an idealized graph of the consequent cellular response (red line). Quantitative data is presented in the right panels.

– Figure 4: It is unclear whether persistent induction of Optogranules causes increased phosphorylation of TDP-43 or simply recruitment of a population which is already present in the cell. The authors should quantify the total levels of phospho-TDP-43 before and after chronic induction of Optogranule assembly to determine whether levels are increased.

Either of these mechanisms could account for the accumulation of phospho- TDP-43 in stress granules and our experiment does not permit us to make a distinction between them. Regrettably, although the amount of phospho-TDP-43 in cells can be detected on a cell-to- cell basis by immunofluorescence, this is not detectable by immunoblot.

– More details should be provided on the nature/quality of the neurons that are differentiated from the iPSCs. Are these cortical neurons? How pure are these neuronal cultures? Are these neurons electrically active?

For our study, we adapted the protocol published in Zhang et al., 2013, which produces cortical neurons, a cell type relevant to ALS/FTD. In the original Zhang et al. paper, the authors demonstrate that human iPSCs can be converted into electrically active functional neurons with nearly 100% yield and purity in 2 weeks using this protocol. To confirm that we successfully replicated the protocol of Zhang et al., we performed digital PCR to quantitatively analyze expression of the pan-neuronal marker MAP2, the pluripotent stem cell marker OCT4, the excitatory cortical neuron markers BRN2 and FOXG1, and the synapsin marker SYN1. The results confirmed the cortical neuron identity of our cells, as now shown in new Figure 4—figure supplement 1A and B.

Additional data files and statistical comments:

It is not always clear whether the correct statistics is used. One example is Figure 3B. A Student t-test doesn't seem to be the correct way to evaluate whether these differences are statistically different. Moreover, as these are box plots, it seems unlikely that the variation is indicated as standard deviations (s.d.) as is indicated in the figure legend.

We have examined the use of statistical tests throughout the manuscript and confirmed that the appropriate tests were used. In Figure 3B (note, this graph has been replaced with updated results that include parental U2OS cells), we now show the results as analyzed by two-way ANOVA, and have corrected the figure legend to reflect the fact that the variation is indicated as min to max.

Reviewer #3:

Very interesting paper – extremely easy to read and parse. Important for field, enjoyed reading, lots of interesting insights.

Some comments:

* It is hard to assess the degree of recruitment of different factors without any quantification (i.e. just from pictures). For example, it is not clear to be that there is bona fide p62 recruitment in neurons (Figure 4H). If this were a normal review I would insist this must be quantified to some degree (e.g. pixel mutual information using an intensity threshold as a binary mask, given intensities are hard to interpret).

Quantitative information was collected in the course of conducting the presented experiments. This quantitative data, with accompanying statistical analysis, has now been added to the figures. With reference to the reviewer’s specific comments, we call attention to new Figure 3I and Figure 4I, which show quantification of stress granule markers over time. For concerns relating to colocalization of p62/SQSTM1, we have now added line scans as new Figure 4—figure supplement 1E to illustrate colocalized signals.

* There are three distinct modes of illumination: continuous (Figure 3A), chronic persistent (Figure 3C) and chronic intermittent (Figure 3D). It is difficult to determine which is used in which experiment. I would strongly suggest standardizing this and ensuring each experiment is clearly labelled regarding which regime is used. Without this interpreting the data (for the reader) becomes difficult.

Indeed, there are three distinct induction paradigms used in this study, each with its advantages and disadvantages. For each light-based experiment, the corresponding induction paradigm is now clearly stated in the figure legend.

* The OptoXXX language used is a little confusing. In the Shin et al. paper, OptoDroplets refers to the general system of a Cry2 domain fused to something:

"Here, we introduce an optogenetic platform that uses light to activate IDR-mediated phase transitions in living cells. We use this 'optoDroplet' system to study condensed phases driven by the IDRs of various RNP body proteins"

Here, OptoGranules refer to the physical cellular assemblies (to distinguish them from stress granules – which makes semantic sense) and OptoG3BP1 is an example of an OptoDroplet construct that contains G3BP1. The fact that the OptoDroplet work is not used to introduce the technology is odd. The results determined here are of significant biological relevance and interest, but the approach is fundamentally the OptoDroplet platform applied to a different protein. The fact that OptoDroplets are only introduced once the OptoGranule system has been described:

'These results contrast with observations made with light-induced aggregation of so-called "OptoDroplets," which nicely…'

gives the impression that this is a different approach system, which is not the case (Figure 1A from this paper and 1A from Shin et al. are essentially interchangeable), and comes across as a little disingenuous. This was a general sentiment I heard from various places when the original preprint went up. It is surprising to me, because all of the exciting results pertain to the biology, not to the method, so it's unclear why the approach is introduced without basically saying "Here we extended the OptoDroplet system to examine the role of G3BP1 in nucleating stress granules…" or something to this effect.

We thank the reviewer for this frank comment. We coined the term “OptoGranule” with the intention of telegraphing that this structure extends and builds upon the approaches and observations described in Shin et al. for the “OptoDroplet.” Scientific advancements nearly always build upon prior scientific achievements, and it is appropriate (and polite) to acknowledge these prior influences. Optical induction of protein aggregation in live cells is a strategy that has been extensively employed. From our perspective, this is not the exciting and fundamental advance presented in Shin et al. Rather, these authors extend and build upon this prior work as a means to control and monitor intracellular phase transitions. As such, the OptoDroplet system is a valuable tool to study the biophysical phenomenon of phase transition and to delineate the roles of specific domains (particularly intrinsically disordered regions, or IDRs) in the formation of condensed phases.

The OptoGranule system further extends and builds upon this work by adapting the OptoDroplet approach to exploit recent insights into (1) the mechanism of stress granule assembly and (2) the distinct roles of clients and scaffolds in initiating assembly and maintaining specific RNP granule identity. As described above, the development of OptoGranules was informed by our identification of G3BP as a uniquely essential central scaffold protein for stress granules, in contrast to TIA1, TDP-43, FUS, and many others, which are client proteins (Yang, Mathieu et al., in review). Please note, this manuscript has been made available for assessment by the editors and reviewers. In the present manuscript we show that enforced phase separation of client proteins (TIA1, TDP-43, and FUS) using CRY2 generates OptoDroplets, which are relatively homogenous intracellular condensates, thereby confirming the results of Shin et al., but we also demonstrate that these are not stress granules. This makes sense since client proteins often reside in multiple biomolecular condensates with distinct identities. In contrast, enforced phase separation of a scaffold protein initiates the cascade of events that seeds the assembly of a full- fledged, complex stress granule, which we term an OptoGranule. Thus, an important takeaway from this work is the critical role of specific scaffolding elements in establishing and maintaining the identity of specific biomolecular condensates.

We stress that the distinction between “droplets” and “granules” is more than semantic. In part this distinction derives from our observation that Opto-TDP-43, Opto-FUS, and Opto-TIA1 form structures that do not recruit stress granule constituents, whereas those formed by Opto-G3BP1 appear to reconstitute the complex composition of an RNP granule. The second distinction is more subtle: droplets formed by Opto-TDP-43, Opto-FUS, and Opto-TIA1 have their biophysical origin in CRY2 oligomerization that presumably forces the IDRs of these proteins to self-associate and initiate a phase transition. In contrast, activation of Opto-G3BP1 forms granules because CRY2-based multimerization (specifically via the replaced NTF2L domain) increases the valency of G3BP, permitting it to engage with another scaffolding element (i.e., a class of RNAs), and these interactions create a seed that subsequently undergoes a phase transition that mediates subsequent further assembly of a stress granule.

Minor Comments:

* It would be useful to draw the schematic (Figure 1A) with the domains proportional to their number of amino acids

* Cry2+mCherry = ~840 amino acids (96 kDa), while NTF2 = 142 amino acids (16 kDa)

* This, of course, may be impractical, in which case simply including the regional size in number of amino acids would be sufficient

To the extent practical given the limitations of the figure, we have addressed this suggestion by adding amino acid numbering to the schematic in Figure 1A.

* Is the absence of SGs in response to the double G3BP1/2 knockout a true absence of stress granules, or an absence of assemblies with G3BP1/Tia1/PAB1 markers – have other markers been checked?

This is an important point that we have fully explored (Yang, Mathieu et al., in review). We performed a genome-wide screen that identified G3BP as a uniquely essential factor in stress granule assembly. In follow-up studies, we created 23 individual cell lines in which putatively essential factors for stress granule assembly (among them G3BP) were knocked out using CRISPR-Cas9. Surprisingly, among these 23 cell lines, we found that G3BP1/2 double knockout cells were the only cell line that failed to form stress granules in response to arsenite. To confirm this result, we stained G3BP1/2 dKO cells for 21 different stress granule markers (G3BP1, G3BP2, caprin 1, PRRC2C, TIA1, USP10, ATXN2, CSDE1, eIF3η, PABP, TAF15, TRIM25, YB1, YTHDF1, YTHDF2, YTHDF3, TIAR, TDP-43, eIF4G, ataxin 2, and DDX3X, as well as polyA RNA), none of which accumulated into granules after arsenite treatment. We have now added data for TIAR and TDP-43 in new Figure 1—figure supplement 3A, bottom right panel.

* "…insinuate into stress granules and other membrane-less organelles" – not sure insinuate has an appropriate meaning here? 'Infiltrate' perhaps?

Although “insinuate” and “infiltrate” are often used interchangeably, we prefer “insinuate” here to evoke an underhanded and sinister infiltration that corrupts the organelle from within.

* Figure 1—figure supplement 1B is the same as part of Figure 1A?

Figure 1—figure supplement 1B was not the same as part of Figure 1A: it showed the design of the Opto-G3BP2 (rather than the Opto-G3BP1) construct. The point is now moot as we have removed Figure 1—figure supplement 1B.

* "Opto-Control expression remained diffuse, with a modest amount of nuclear and cytoplasmic clusters (Figure 1B and Supplementary Video 1)." – the text is intriguing, though it wasn't obviously clear to me where these cytoplasmic clusters are in Figure 1B? But assuming you do see some level of clusters, why is an obligate dimer able to lead to any degree of cluster formation? I would have expected dimers to be far far below the resolution limit such that monomer/dimer Opto-Control should be equally diffuse

As described in the response to Reviewer 1 above, we used two different Opto-Control constructs in this paper; one (“Opto-Control”) is a fusion protein of mCherry and wild-type CRY2, and the other (“Opto-Control (olig)”) is a fusion protein of mCherry and a mutant form of CRY2 (CRY2-olig) that forms abundant CRY2 clusters upon activation.

Like many proteins containing mCherry, the Opto-Control fusion protein undergoes a modest amount of nonspecific aggregation that is related to its degree of expression. Importantly, these clusters are negative for stress granule markers, including >10 proteins and polyA RNA (Figure 1H-J and data not shown). Furthermore, we affinity purified this protein and found by mass spectrometry that it does not associate with any stress granule proteins (data not shown).

To further challenge the negative results obtained with Opto-Control, we used Opto-Control (olig) to aggravate the aggregation of the fusion protein. The aggregates formed by Opto-Control (olig) were negative for stress granule markers (new Figure 1—figure supplement 1C) and poorly dynamic by FRAP (new Figure 1—figure supplement 1D-F).

* When the OptoControl is off it appears to partition into the nucleus (Figure 1H, 1I, 1J) but when activated it is strongly excluded. Both monomeric and dimeric version should be larger than the threshold size for free permeability into the nucleus sans an NLS, so it’s not clear how/why light should be changing the distribution – some explanation of this would be useful (i.e. does this imply there are additional un-characterized responses to blue-light stimulation?).

We don’t know, but this effect could be related to a report (Pathak et al., Nucleic Acids Res, 2017; PMID 28431041) that CRY2-mCherry shows minor protein redistribution from the nucleus to the cytoplasm following blue light stimulation. It is possible that light-induced CRY2 cluster formation may block or slow nuclear import of cytosolic and newly synthesized protein, leading to accumulation of protein in the cytosol.

* Are the expression levels of OptoG3BP1 comparable to endogenous G3BP1? I realize expression is clearly a tunable parameter as addressed in Figure 2, so it would be useful, as a reference, to mention the expression levels of endogenous protein here.

We selected Opto-G3BP1 expression levels that were comparable to endogenous G3PB1, as shown in new Figure 1—figure supplement 1A.

* "Expression of Opto-constructs using full-length TDP-43 or FUS [CRY2PHR-mCherry-TDP-43(FL); CRY2PHR-mCherry-TDP-43(FL)] did not produce cytoplasmic clusters with blue light activation" (minor point – I believe the second instance here should be CRY2PHR-mCherry-FUS(FL))

We have now corrected this.

* This is a very interesting result for two reasons

* 1) It’s not clear to me why FL-FUS OptoDroplets should not form assemblies, especially given recent reports that FL FUS assemblies much more readily than the LCD alone. Any thoughts on this in the discussion would, I think, be very useful. [1]

This is a major point of this paper. The difference relates to the distinct roles of clients and scaffolds in initiating assembly and maintaining specific RNP granule identity. This point is explored above and now made more plain in the manuscript text.

* 2) Recent work has shown that the NTD of TDP43 forms dimers that are necessary for phase separation in full-length TDP-43. In agreement with this, the CRY2 dimerization domain appears able to replace this N-terminal domain and give rise to droplets, HOWEVER, if the N-terminal domain is present (i.e. in CRY2PHR-mCherry-TDP-43(FL)) droplet formation is suppressed – any possible mechanism here would be useful to address – specifically, how does the ADDITION of a dimerization domain between CRY2 and the C-terminal portion of TPD43 suppress assembly?

* These questions are directly related to the comparison of other optoDroplet constructs

To be clear, we do not claim that CRY2PHR-mCherry-TDP-43(FL) does not form droplets; rather, we claim that this fusion protein does not form stress granules. Indeed, this is the very distinction between OptoDroplets (phase separation of a selected protein) versus OptoGranules (a cascade of events, including polysome disassembly, that leads to assembly of a stress granule). As the reviewer notes, we did observe that CRY2PHR-mCherry-TDP-43(FL) forms puncta in the nucleus, which corresponds to the normal localization of TDP-43 and is consistent with the presence of an NLS in the NTD (new Figure 1—figure supplement 4G).

Upon activation, these puncta are indeed less prominent for unclear reasons. We speculate that the presence of two dimerization domains (CRY2 and NTD) leads to tighter intermolecular interaction between any two TDP-43 molecules and this tight interaction makes TDP-43 unfavorable for weak multivalent interactions that are favorable for LLPS.

* Not sure how to interpret the Opto-G3BP1 vs G3BP1-GFP RNA binding data? Naively from the description of the RNA binding assay I would have expected 1) cross-linking to cause G3BP1 in stress granules to extensively cross-link with local RNAs, while under non-stress/non OptoGranule inducing conditions there would be minimal RNA cross-linking and 2) for Opto-G3BP1 and G3BP1-GFP to be similar. Instead, the data appear to show that you get extensive and essentially identical RNA binding under stressed and non-stressed conditions, and that Opto-G3BP1 and G3BP1-GFP have different RNA binding profiles. Similarly, not sure how to interpret the western blot associated with 2b – it would be useful to explicitly annotate what the bands are. This is almost certainly just a limitation of my understanding of the experimental setup, but it seems at least plausible others might also be confused…

The purpose of this experiment was to show that Opto-G3BP1 binds RNA to a similar extent as WT G3BP1. Indeed, the total amount of RNA bound by G3BP before and after stress is unchanged when assessed by CLIP (cross-linking immunoprecipitation). What is not revealed by this experiment, however, is that the types of RNA species bound by G3BP1 are shifted by stress, and this shift appears to be important in initiating stress granule assembly.

These results are elaborated in Yang, Mathieu et al. (in review) and are out of context here, so we have deleted these results from this manuscript.

* In the protein name SQSTM1 is used, while in Figure 3 p62 is used – this may confusing for people unfamiliar with the protein, so I'd suggest a consistent naming scheme

We now use SQSTM1 uniformly throughout the manuscript.

* I found the mCherry vs. mRuby optoG3BP1 section confusing on the first read, as it was initially unclear why both would be needed. I would suggest splitting this into a 'first we used mRuby-optoG3BP1…', then once this has been completed, explain why an inducible system is needed and then introduce the inducible mCherry variant.

We have rearranged this portion of the text to increase clarity.

* Why is the pTDP-43 recruitment to SGs in neurons so much weaker than in U2OS cells? In U2OS see reasonable recruitment just 1 hour in, with robust recruitment after 2 hours. In neurons after 5 hours (4g) there is basically no co-localization with optoG3BP1, and then after 6 robust co-localization is observed.

We do not know why these differences occur. We can only point to inherent differences that must be present in the cellular properties of cortical neurons versus those of the U2OS cell line.

https://doi.org/10.7554/eLife.39578.022

Article and author information

Author details

  1. Peipei Zhang

    Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1742-1680
  2. Baochang Fan

    Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  3. Peiguo Yang

    Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  4. Jamshid Temirov

    Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, United States
    Contribution
    Data curation, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  5. James Messing

    Howard Hughes Medical Institute, Chevy Chase, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  6. Hong Joo Kim

    Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, United States
    Contribution
    Formal analysis, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9157-1612
  7. J Paul Taylor

    Howard Hughes Medical Institute, Chevy Chase, United States
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing
    For correspondence
    jpaul.taylor@stjude.org
    Competing interests
    Reviewing editor, eLife, and a consultant for Third Rock Ventures.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5794-0349

Funding

Howard Hughes Medical Institute

  • J Paul Taylor

National Institutes of Health (R35NS097974)

  • J Paul Taylor

ALS Association (18-IIA-419)

  • J Paul Taylor

St. Jude Children's Research Hospital

  • J Paul Taylor

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

Acknowledgements

We thank Natalia Nedelsky for editorial assistance. We thank Anderson Kanagaraj for assistance with DNA construct preparation and Aaron Gitler (Stanford University) for providing phospho-TDP-43 antibodies. This work was supported by funding from the Howard Hughes Medical Institute, NIH grant R35 NS097974, ALS Association grant 18-IIA-419, and St. Jude Research Collaborative on the Biology of Membrane-less Organelles to JPT. JPT is a consultant for Third Rock Ventures.

Senior Editor

  1. Huda Y Zoghbi, Texas Children's Hospital, United States

Reviewing Editor

  1. Hong Zhang, Institute of Biophysics, Chinese Academy of Sciences, China

Publication history

  1. Received: June 26, 2018
  2. Accepted: March 6, 2019
  3. Version of Record published: March 20, 2019 (version 1)
  4. Version of Record updated: April 1, 2019 (version 2)

Copyright

© 2019, Zhang et al.

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

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