Author response: Real-time imaging of Huntingtin aggregates diverting target search and gene transcription (2016)

Full text Figures and data Side by side Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract The presumptive altered dynamics of transient molecular interactions in vivo contributing to neurodegenerative diseases have remained elusive. Here, using single-molecule localization microscopy, we show that disease-inducing Huntingtin (mHtt) protein fragments display three distinct dynamic states in living cells – 1) fast diffusion, 2) dynamic clustering and 3) stable aggregation. Large, stable aggregates of mHtt exclude chromatin and form 'sticky' decoy traps that impede target search processes of key regulators involved in neurological disorders. Functional domain mapping based on super-resolution imaging reveals an unexpected role of aromatic amino acids in promoting protein-mHtt aggregate interactions. Genome-wide expression analysis and numerical simulation experiments suggest mHtt aggregates reduce transcription factor target site sampling frequency and impair critical gene expression programs in striatal neurons. Together, our results provide insights into how mHtt dynamically forms aggregates and disrupts the finely-balanced gene control mechanisms in neuronal cells. https://doi.org/10.7554/eLife.17056.001 eLife digest Huntington's disease belongs to a group of human genetic disorders in which faulty proteins cause nerve cells to progressively die. All proteins are made from building blocks called amino acids, and these diseases are collectively called PolyQ expansion diseases because the faulty proteins usually have an abnormally long stretch that contains many repeats of an amino acid called glutamine. The stretches of glutamines make these mutant proteins stick to each other, which means that they aggregate in the diseased cells. Researchers have proposed several mechanisms to explain how aggregates of one such mutant protein, called mutant Huntingtin (mHtt), might contribute to Huntington's disease. One possibility is that mHtt accumulates in the nucleus of the cell – which houses most of the cell’s DNA – and interferes with the proteins that are required to switch genes on or off. Preventing these gene regulatory proteins from carrying out their role could disrupt the normal pattern of gene activity. However, working out if this is the case would require researchers being able to follow how mHtt forms aggregates and interferes with normal processes in living cells. Li et al. have now used high-resolution, high-speed microscopy to directly track the movement of individual mHtt proteins in living mouse cells in real time. The analysis showed that PolyQ protein fragments of mHtt behaved in three distinct ways – they diffused, briefly clustered or stably aggregated. Large stable aggregates of mHtt created decoy-like traps that interfered with the behavior of the gene regulatory proteins. Using computer-aided simulations, Li et al. then showed that that these molecular traps make the proteins take much longer to find their true target genes. Further studies in nerve cells suggested that this phenomenon disrupted the normal pattern of gene activity. Next, Li et al. also used the live cell imaging system to look at which gene regulatory proteins were sequestered in the mHtt aggregates. This approach identified proteins that are important regulators involved in a number of neurological disorders. These proteins included some with long stretches of glutamines and unexpectedly others in which the glutamines were interspersed with other amino acids. Aggregates of mHtt therefore appear to affect a much broader range of proteins than previously thought. Together, the results provide insight into how mHtt forms aggregates and disrupts the finely balanced mechanisms that control gene activity in nerve cells. Future studies could explore the general principles that determine which proteins interact with mHtt aggregates. This could help reveal the faulty processes that underlie Huntington's disease and other neurodegenerative disorders. https://doi.org/10.7554/eLife.17056.002 Introduction Poly-glutamine (PolyQ) expansion in proteins is associated with multiple neuro- and muscle- degenerative diseases such as Huntington’s disease (HD), X-linked spinobulbar muscular atrophy (SBMA) and various spinocerebellar ataxias (SCA1, 2, 3, 6, 7 and 17) (reviewed in [Blum et al., 2013; Mohan et al., 2014]). In HD, a single mutant Huntingtin allele with PolyQ tracts greater than 37 glutamines leads to selective cell death in the striatum and certain regions of the cortex, causing muscle coordination and cognitive defects (Group, 1993; Ross and Tabrizi, 2011). It has been widely observed that extended PolyQ tracts facilitate the formation of protein aggregates in the cytoplasm and nucleus of diseased cells (Bates, 2003; DiFiglia et al., 1997; Huang et al., 2015). Previous FRAP, FCS and in vitro super-resolution imaging provides significant insights into mHtt aggregate formation (Cheng et al., 2013; Duim et al., 2014; Kim et al., 2002; Park et al., 2012; Sahl et al., 2012; Wustner et al., 2012). However, the dynamics of aggregate formation or how the resulting 'plaques' might influence essential molecular transactions that disrupt gene expression programs have not been investigated at the single-molecule level in living cells. Since the original discovery of mHtt aggregates in the nucleus and cytoplasm of HD cells, the relevance of these aggregates or plaques to disease pathology has been under vigorous debate (DiFiglia et al., 1997; Scherzinger et al., 1997; Woerner et al., 2016). Currently, several mechanisms have been proposed to explain how mHtt aggregates might contribute to disease states. Interestingly, it was shown that the formation of PolyQ aggregates can in some instances, protect cells from apoptosis in short-term cell culture experiments (Saudou et al., 1998; Taylor et al., 2003). Specifically, it was proposed that soluble fragments or oligomers of mHtt are more toxic than mHtt aggregates. Stable self-aggregation of mHtt monomers was postulated to neutralize prion protein interacting surfaces and protect cells from prion induced damage (Arrasate et al., 2004; Saudou et al., 1998; Slow et al., 2005). However, this model does not address the long-term effect of mhtt aggregates in striatal cells nor does it exonerate mHtt aggregates from potentially contributing to the disease state. For example, myriad studies have reported the toxicity of aggregates in vivo (Labbadia and Morimoto, 2013; Michalik and Van Broeckhoven, 2003; Williams and Paulson, 2008; Woerner et al., 2016). Without methods to directly observe and measure biochemical reactions and molecular interactions in living cells, it is challenging to gain mechanistic insights that may help resolve these controversies. With recent advances in imaging and chemical dye development (reviewed in [Liu et al., 2015]), it has become possible to detect and track individual protein molecules in single living cells (Abrahamsson et al., 2013; Chen et al., 2014a, 2014b; Elf et al., 2007; Gebhardt et al., 2013; Grimm et al., 2015; Hager et al., 2009; Izeddin et al., 2014; Liu et al., 2014; Mazza et al., 2012; Mueller et al., 2013). Decoding the complex behavior of single molecules enables us to measure molecular kinetics at a fundamental level that is often obscured in ensemble experiments. Specifically, the rapidly emerging high-resolution fast image acquisition platforms provide a means for visualizing and measuring the in vivo behavior of dynamically regulated molecular binding events. It also becomes possible to generate 3D molecular interaction maps in living mammalian cells and elucidate local diffusion patterns in the highly heterogeneous sub-cellular environment (Chen et al., 2014a, 2014b; Izeddin et al., 2014; Liu et al., 2014). Here, using HD as the model, we devised a molecular imaging system to quantify the formation of protein structures and measure the real-time dynamics and behavior of PolyQ-rich proteins. First, with live-cell PALM and FRAP experiments, we compared gross structures and diffusion dynamics of wild-type (Htt-25Q) versus disease-inducing mutant (mHtt-94Q) Htt protein fragments. Interestingly, soluble fractions of wild-type Htt-25Q and mutant Htt-94Q display similar rapid diffusion kinetics. Strikingly, both Htt-25Q and mHtt-94Q protein fragments also form small, diffraction-limited clusters in live cells. These clusters are highly dynamic and resolve quickly (mean lifetime < 10~20 s). However, the mutant Htt-94Q protein also forms much larger highly stable aggregates (FRAP recovery lifetime > 45 min). Two-color super resolution imaging reveals that mHtt aggregates exclude chromatin and selectively interact with a set of neurological disease-related factors (Foxp2, TBP, Sp1 and wild-type Huntingtin). Fine domain mapping experiments suggest that continuous PolyQ tracts contribute to but are not necessary for binding to mHtt aggregates. Notably, we found that aromatic amino acids enabled proteins with sparse glutamines to bind mHtt aggregates. Single-molecule tracking and numerical simulation experiments suggest that mHtt aggregates act as large decoy traps in the cell, efficiently slowing down target search kinetics and decreasing target site sampling frequencies. Consistent with this model, unbiased genomic screens showed that elevating Sp1 levels in HD-affected striatal cells partially restored the expression of Sp1 dependent target genes. Sp1 target site occupancies are also significantly decreased in HD-affected cells. These findings provide new insights into potential Huntington’s disease mechanisms and reveal the role of mHtt aggregates in disrupting key dynamic biological processes in living cells. Results Live-cell Htt dynamics To establish a cellular imaging system for HD and evaluate the effects of PolyQ expansion on Htt protein dynamics, we fused disease-inducing Huntingtin protein exon 1 fragment (mHtt-94Q) (Rubinsztein, 2002; Yamamoto et al., 2000) and its wild-type counterpart (Htt-25Q) (Krobitsch and Lindquist, 2000) to a monomeric photo-switchable protein (mEOS3.2 (Zhang et al., 2012); w/o nuclear localization signal - NLS). We stably expressed each fragment in mouse embryonic stem (ES) cells or STHdh striatal cells (Trettel et al., 2000). Epi-fluorescence live imaging revealed that 8~15% of the mHtt-94Q cells (27 of 234 cells) contain large visible sub-cellular aggregates while the majority (123 of 125 cells) of Htt-25Q cells show a relatively homogeneous intracellular distribution (Figure 1—figure supplement 1A). To measure Htt protein dynamics, we next performed live-cell imaging experiments by stochastically switching the mEOS3.2 moiety to the red-shifted state and tracking single-molecule movement of the activated molecules (sptPALM) (Manley et al., 2008). This technique allowed us to generate high-density single-molecule trajectories separated by stochastic activation times. As expected, ensemble whole-cell diffusion and velocity analysis reveals that a much larger fraction of mHtt-94Q molecules show slower and more compact diffusion kinetics compared to Htt-25Q controls (Figure 1B, Figure 1—figure supplement 1B and C), suggesting that mHtt-94Q is on average significantly less mobile. High-density trajectories generated with sptPALM also allows reconstruction of high-resolution sub-cellular diffusion maps (Figure 1A, middle and bottom panels). Interestingly, both mean square displacement (MSD) and Bayesian inference-based diffusion maps show that the slow mHtt-94Q species were mainly concentrated around aggregates, while mHtt-94Q molecules in other regions remain fast moving. Consistent with these observations, fluorescence recovery after photo-bleaching (FRAP) experiments within non-aggregate containing regions show full recoveries within 1 s (Figure 1—figure supplement 1E, Video 1 and 2), confirming that a portion of mHtt-94Q molecules can remain in a mobile, dynamic, and soluble state. These results are consistent with previous FRAP and FCS experiments showing fast diffusing and aggregate states of mHtt protein (Cheng et al., 2013; Kim et al., 2002; Park et al., 2012; Wustner et al., 2012). Figure 1 with 1 supplement see all Download asset Open asset mHtt protein displays three distinct states in living cells. (A) Top, localization map of live-cell PALM data set for the indicated Htt fragment. The PALM data were recorded at 20 ms per frame using imaging conditions specified in Materials and methods. Diffraction-limited Htt-25Q aggregates are indicated by square boxes (White). Middle, reconstructed single-molecule trajectories reflecting sub-cellular molecular diffusion. Each trajectory is color-colored using the diffusion coefficient calculated by the linear regression of the MSD curve with a R2 > 0.9. 2000 trajectories are shown for the Htt-25Q condition. Twice as many trajectories are shown for the mHtt-94Q condition to ensure relatively equal sampling and representation in regions without mHtt-94Q aggregates. Bottom, diffusion map calculated by a Bayesian inference- based method (El Beheiry et al., 2015). Trajectories with minimal 2 connected localizations were considered in this analysis. Each pixel in the image is color-coded with the most probable diffusion coefficient for that pixel calculated by InferenceMap. Scale bars, 2 µm. (B) Histogram of diffusion coefficients calculated same as in the middle panel of (A) for the indicated condition. Htt-25Q, 7266 trajectories; mHtt-94Q, 19,975 trajectories. N = 6 cells. (C) The temporal history of localizations in each selected region: vertical line (Black) indicates the frame from which the localization is detected. The blue trend line represents the cumulative distribution function of the total localizations detected before a given frame number. Three representative regions are shown for each condition. The images above each plot are sliding-window localization maps from Video 3, showing the temporal dynamics of Htt protein from each category. t indicates when the cluster/aggregate is clearly visible. Scale bars, 2 µm https://doi.org/10.7554/eLife.17056.003 Video 1 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg FRAP experiments in mHtt aggregate negative (left) and positive (right) cells. The time lapse confocal imaging interval for the aggregate negative cell is 0.5 s. That for the aggregate positive cell is 8 s. https://doi.org/10.7554/eLife.17056.005 Video 2 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg FRAP experiments in mHtt aggregate negative (left) and positive (right) cells performed in the same field of view, showing that laser power is sufficient for bleaching. The fluorescence recovery in cells with soluble mHtt-94Q is rapid, while that at aggregate regions is much slower. https://doi.org/10.7554/eLife.17056.006 Interestingly, reconstructed molecular density maps from single molecule localization experiments reveal that even Htt-25Q fragments can form small protein polymers or clusters in live cells (Figure 1A, white box). These very small clusters are below the diffraction-limit (50~100 nm) and cannot be adequately resolved by conventional imaging methods. Temporal localization history and sliding window analysis (Figure 1C and Figure 1—figure supplement 1D; Videos 3 and 4 ) suggest that protein molecules in these clusters display relatively fast association/dissociation dynamics. Specifically, time-counting PALM analysis (tcPALM) (Cisse et al., 2013) reveal that these small clusters form in temporal bursts (~10–20 s) (Figure 1C), while localization detections in control regions with similar molecular densities show no such apparent bursting behaviors (Figure 1—figure supplement 1D). Localization maps for mHtt-94Q cells are more complex. Both small clusters and large aggregates can be detected (Figure 1A and Video 3). Interestingly, localization detections in small mHtt-94Q clusters display similar bursting kinetics as Htt-25Q clusters (Figure 1C and Video 4). By contrast, the localizations of large mHtt-94Q aggregates distribute relatively evenly over time, suggesting a much greater structural stability (Figure 1C; Video 3 and 4). Consistent with this observation, FRAP experiments over longer time-scales found little molecular exchange occurring at large mHtt-94Q aggregates (FRAP recovery lifetime > 45 min, See Materials and methods for calculation details) (Figure 1—figure supplement 1F, Video 1 and Video 2). Taken together, our results suggest that there are likely at least three distinct states for Htt proteins in living cells: 1) rapidly diffusing, 2) short-lived dynamic clustering and 3) very stable aggregates formed only by the Gln-expanded mutant protein but not the wild-type Htt. It is likely that PolyQ expansion tilts the kinetic balance of mHtt from a dynamic clustering state to an aggregated state, akin to recently described protein dynamic polymer/phase transitions associated with ALS/FTD neurodegenerative disorders (Kato et al., 2012; Molliex et al., 2015; Murakami et al., 2015; Nott et al., 2015; Patel et al., 2015; Xiang et al., 2015). These results also support previous in vitro super-resolution imaging experiment showing that there are likely distinct Htt aggregate species for seeding and polymerization states (Duim et al., 2014; Sahl et al., 2015; 2012). Video 3 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Sliding-window representation for live-cell PALM datasets of Htt-25Q (Left) and mHtt-94Q (Right). PALM Imaging is performed with a rate of 50 Hz. In each frame, single-molecule localizations from adjacent 1000 frames were pooled and plotted. The interval for the sliding window is 0.5 s (25 frames). https://doi.org/10.7554/eLife.17056.007 Video 4 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Zoom-In view of indicated types (Left) of region from Video 3, showing distinct local molecular dynamics. https://doi.org/10.7554/eLife.17056.008 mHtt aggregates exclude chromatin Dysregulation of transcription has been extensively implicated in the pathological processes of HD for decades (Dunah et al., 2002; Kumar et al., 2014; Mohan et al., 2014; Nucifora et al., 2001; Paul et al., 2014). Although altered chromatin structures have been reported in diseased cells (Labbadia et al., 2011), ultra-fine chromatin structure and genome organization have not been extensively investigated. To address this, we labeled chromatin by stably expressing H2B-HaloTag in the mHtt-94Q cells. To avoid biases introduced by individual imaging techniques, we imaged the samples with two-color 3D live-cell structured illumination imaging, Airyscan imaging and single-molecule localization microscopy. All these experiments showed consistent results that intensities of H2B staining were dramatically depleted in regions of mHtt aggregates (Figure 2A and Figure 2—figure supplement 1A; Video 5), suggesting that these 'inclusion bodies' likely exclude chromatin. We note here that the size and shape of mHtt aggregates varies significantly in the cell. Thus, to quantify exclusion or recruitment by mHtt aggregates in an unbiased manner, we used a size-normalized, averaging based analysis method. Briefly, we rescale each mHtt-aggregate containing region to have a diameter of 100 pixels (Figure 2B). Then, an intensity map was generated by averaging multiple mHtt aggregate regions obtained across different cells. The center-to-peripheral radial grayscale intensity curve is then calculated by each circular pixel increment for both channels (Figure 2C and D). For molecular structures (such as H2B) that are excluded by mHtt aggregates, the intensity curve resembles the mirror-image of the curve for for mHtt (Figure 2D, Figure 2—figure supplement 1B and C). We note that the commonly-used DNA dye DAPI mHtt aggregates (Figure 2—figure supplement suggesting that DAPI fluorescence might not be an for genome localization and organization in this Figure 2 with 1 supplement see all Download asset Open asset mHtt aggregates exclude chromatin. (A) Top, live-cell 3D imaging of chromatin and mHtt aggregates See Video for 3D Bottom, Airyscan imaging of cells with the same two-color (B) pixel fluorescence intensity maps for mHtt aggregate containing regions as in The intensity maps for regions in the H2B are in the bottom (C) maps for different regions shown in (B) are and for each The mean radial intensity trend line for each is calculated as the function of the from the (C) to the intensities are as the function of the for mHtt-94Q and H2B regions from 8 cells. Scale bars, 2 µm Video Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Live-cell 3D imaging with cells expressing H2B-HaloTag and In the in the are 3 by a 3D mHtt aggregates impede target search of proteins containing long continuous PolyQ tracts One pathological of HD is selective cell death in the striatum and certain regions of the et al., et al., 2014). Since Htt is widely expressed in different in the it how mutant Htt selective cell death in striatal et al., Interestingly, it was shown that long PolyQ containing proteins such as wild-type Htt and binding protein are in the mHtt aggregates et al., 2002; et al., To we could these results in our live cell imaging we expressed exon 1 fragment in cells with mHtt aggregates. Htt-25Q protein becomes significantly sequestered in the mHtt aggregates in both cells and striatal cells (Figure and Figure supplement Next, we the PolyQ in the wild-type Htt fragment and found no recruitment of the fragment to mHtt aggregates (Figure suggesting that the PolyQ is likely required for the As to TBP, we found that the PolyQ containing domain but not the DNA binding domain of is selectively in mHtt aggregates (Figure suggesting that recruitment of to mHtt aggregates also the PolyQ containing these results are consistent with previous studies using different cell et al., 2002; et al., suggesting that mechanisms these interactions are likely not Figure 3 with 1 supplement see all Download asset Open asset mHtt aggregates interact with Htt-25Q, and PolyQ containing (A) Airyscan images showing of and domain with at mHtt aggregate regions (B) of in Htt-25Q or PolyQ in and the recruitment of these factors to mHtt aggregates. (C) intensity as in Figure for mHtt-94Q and (C) or regions from cells. Scale bars, 2 µm To new mHtt aggregate interacting factors and to the of a PolyQ is a for recruitment by mHtt aggregates, we next PolyQ containing proteins and identified a PolyQ containing transcription (Figure supplement is a transcription factor shown to be important for and system development et al., 2002; et al., 2008; et al., 2001; et al., et al., 2003). of both of the gene in et al., 2005). in the in the striatum display and suggesting that is important for the development of et al., These are in HD et al., et al., Ross and Tabrizi, Slow et al., 2003). We found that for the full the PolyQ containing fragment but not the DNA binding domain with mHtt aggregates (Figure and Figure supplement Taken together, these results suggest that recruitment of these factors to mHtt aggregates likely PolyQ containing and cellular by these important transcription factors are also likely by the of mHtt aggregates. of the critical role of in HD-affected region and our findings also an possibility that might be one of the essential for the selective effects of HD on striatal for amino acids are required for aggregate interactions Although our recent unbiased for long continuous PolyQ containing transcription factors not the human multiple studies previously implicated the of this regulatory protein in Interestingly, studies showed that over expression of Sp1 and of its can mutant Htt induced gene expression defects (Dunah et al., and mHtt fragments activation in vitro et al., 2005). These results suggested that Sp1 might also interact with mHtt protein aggregates in living cells. To this we performed live-cell 3D imaging experiments. Interestingly, we observed Sp1 binding even to mHtt aggregates (Figure supplement 1A). Live-cell single-molecule tracking revealed that Sp1 directly to mHtt aggregates (Figure and Video and that full Sp1 is selectively in mHtt aggregate regions (Figure and Figure supplement These results are because Sp1 is for there are no continuous PolyQ tracts in the Sp1 protein To the amino acid of Sp1 for this we separated the transcription activation domain from the DNA binding domain The Sp1 showed interactions with mHtt aggregates while the was excluded from mHtt aggregates (Figure and D). To down the interaction we performed a of experiments (Figure supplement 1) and identified a Sp1 fragment with that the interaction with mHtt (Figure this fragment to allowed us to its selective recruitment to mHtt aggregates (Figure and D). a control fragment from Sp1 - also for glutamines to interact with mHtt aggregates (Figure and D). revealed that the only apparent these fragments is the of three aromatic amino acids interspersed the of Sp1 (Figure of these three aromatic amino acids to or even the of the fragment to interact with mHtt aggregates (Figure three amino acids in the Sp1 - fragment to this fragment to bind mHtt aggregates (Figure and D). These results suggest that interspersed aromatic amino acids are likely critical for Sp1 to interact with mHtt aggregates while stretches of PolyQ