Apr 142010
 
ResearchBlogging.orgAlthough we are most familiar with the circadian rhythm from its effects on our physiological state, the roots of the phenomenon lie in the molecular biology of individual cells. The circadian rhythm is the result of a transcriptional control system that regulates the levels of many different proteins in the cell with the passing of time. Not all of the proteins subject to this control have yet been catalogued, and as a result some surprising effects are still being discovered. A recent article in Proceedings of the National Academy of Sciences from the Sancar lab at UNC suggests that circadian control of a DNA repair factor may be a way to enhance the effectiveness of a chemotherapeutic agent. The article is open access, so I encourage you to open it up and read along.

Previously, the Sancar group has shown that the circadian rhythm affects DNA repair in brain cells. In that case, DNA had been damaged by UV irradiation, a lesion that had to be replaced by the excision repair mechanism. Because one of the critical factors for this kind of repair, the Xeroderma Pigmentosum A protein (XPA), undergoes a circadian oscillation, the efficiency of repair depends on the time of day at which the damage occurred. Kang et al. hypothesized that this circadian dependence could also be true for other forms of DNA damage that undergo excision repair.

This led them to cisplatin, a drug used as primary chemotherapy or part of a combinatorial regimen for several kinds of cancer. Cisplatin creates covalent bonds crosslinking DNA bases in an intra-strand or inter-strand manner. These covalent linkages make replication (and therefore mitosis) impossible, and elicit a DNA repair response. If the cell cannot clear the crosslink, it will either die by apoptosis, or if the apoptotic response is suppressed, fail to produce viable daughter cells. Either way, the growth of the tumor is suppressed. The excision-repair pathway is the only mechanism of clearing this kind of DNA damage, so Kang et al. thought that there might be a robust circadian dependence. In order to test this idea, they carried out experiments using extracts from mouse liver and testis.

Figure 1 shows the results of their experiment using liver extract. Panel C summarizes the key results (data shown in panels A and B) that XPA mRNA, XPA protein, and excision repair efficiency are correlated with the dark/light cycle the mice are experiencing, with the highest levels of protein and repair occurring in the late afternoon, and the lowest levels in the very early morning (around 5 AM). Panel E shows a comparison of excision repair between normal mice and ones that have been genetically modified to lack cryptochrome, a critical circadian clock protein. In these CryDKO mice the time of day has no effect on the efficiency of repair, and as panel F shows, they also do not have the daily fluctuation in XPA mRNA and protein levels. These results suggest that circadian control of XPA expression levels dictates repair efficiency in liver tissues — as panel D shows, addition of exogenous XPA protein can recover the excision repair activity. However, there was no detectable circadian dependence for excision repair activity in testis, as Figure 2 shows using similar experiments.

Circadian control of XPA activity is possible because the protein doesn’t last very long in the cell. Figure 3 shows experiments using two inhibitors: cycloheximide (CHX), which prevents protein synthesis, and MG132, which prevents protein degradation by the proteasome. The gel in panel A shows that in two different types of cells, CHX treatment caused XPA protein to disappear over a period of three hours, in contrast to the control protein actin, which was unaffected. Addition of MG132 caused XPA to accumulate with time, although actin levels were again constant. The fairly rapid degradation of XPA protein means that the overall quantity of that protein in a cell will be highly dependent on the concentration of its mRNA transcript. That is, you can only have high XPA levels if there’s a lot of mRNA so ribosomes can continue to produce it. Circadian control of transcription is therefore able to regulate protein concentration. The authors hypothesize that this tight circadian control may have developed to prevent deleterious effects of non-specific DNA repair activity during times when there is no chance of UV insult, although there is no specific evidence to support this conjecture presently.

The MG132 experiment indicates that XPA is degraded by ubiquitin ligation and subsequent destruction in the proteasome. Figures 4 and 5 show a variety of evidence indicating that this process is mediated by the ubiquitin ligase HERC2. The experiments in figure 4 establish that HERC2 binds to XPA (panels A and B) and colocalizes with it in the cell (panels C and D). The gels in Figure 5 show that when HERC2 levels in the cell are knocked down by RNA inhibition using siRNA specific for that protein, CHX treatment does not cause XPA to degrade. These facts indicate that HERC2 is the ubiquitin ligase for XPA. The direct effect of HERC2 activity on the repair of cisplatin DNA damage is shown by figure 6. Here, cells were treated with cisplatin and HERC2 siRNA. The left side of panel A shows the clearance of cisplatin adducts from A549 cells over time (the right side shows the total DNA). As you can see, addition of HERC2 siRNA allows for more rapid clearance of the adduct, with a particularly dramatic effect at low dosage.

Unfortunately, due to its extreme toxicity, treating cancer cells with CHX is not a viable strategy for chemotherapy. However, knowing that the level of XPA protein in some target cells varies in a predictable way with the time of day can help doctors optimize treatments for maximum effectiveness. In particular, for cancers originating in tissues that have a strong circadian rhythm and intact XPA, early-morning treatment with cisplatin may be more effective than treatment at other times of the day. More experiments are needed before this can be formally recommended — in particular, whole-animal studies and human trials will be necessary to definitively establish the effect. If these results hold up in whole organisms, however, the circadian effect on DNA repair may become a valuable tool for optimizing some chemotherapy regimens.

Kang, T., Lindsey-Boltz, L., Reardon, J., & Sancar, A. (2010). “Circadian control of XPA and excision repair of cisplatin-DNA damage by cryptochrome and HERC2 ubiquitin ligase”. Proceedings of the National Academy of Sciences, 107 (11), 4890-4895 DOI: 10.1073/pnas.0915085107

Full Disclosure: I have previously collaborated with Aziz and his group on a research project on eukaryotic cryptochromes.

Aug 112009
 
My field-cycling article (previous post) is part of a dynamics-focused topical issue of JBNMR. In my next few science posts I’ll describe some of the other contributions.

ResearchBlogging.orgResearch into the interplay between protein structural dynamics and function is a window into important fundamental knowledge about biochemistry, but the general justification for public funding of these studies by medical agencies is that they will have the ultimate effect of improving our ability to design and optimize drugs. However, even though our ability to characterize macromolecular dynamics has increased dramatically in the past few decades, there are few, if any, cases in which this knowledge has been applied successfully to the design of therapeutic agents. In part this is because incorporating data on fluctuations into the design algorithms poses a significant challenge. It’s also true, though, that we understand only part of each system, i.e. the dynamics of the protein target, not the small molecules it binds. If dynamics studies are to make the maximum possible contribution to pharmaceutical sciences, the motions of the ligand must be characterized. In their article in Journal of Biomolecular NMR, Jeffrey Peng and students from Notre Dame attempt to address this shortcoming in the case of a substrate for the phosphorylation-directed prolyl isomerase Pin1.

Pin1 is implicated in a number of regulatory and signaling pathways, which seems strange because it doesn’t possess any intrinsic transcriptional regulation ability, nor does it covalently add or remove phosphate groups. Instead, Pin1 has an enzymatic activity that accelerates, generally without altering the relative populations, the conversion of prolines from their cis- to trans- state and vice versa. This activity is specifically targeted to prolines that are adjacent to phosphorylated serines or threonines. In addition to the catalytic domain that does this work, Pin1 possesses a WW domain that has identical specificity. Because Pin1 does not alter the balance between cis- and trans- Pro, only the rate at which one changes to the other, its role in signaling has been difficult to ascertain, although there is intense interest in this area.

You don’t need to understand an entire pathway to design an effective inhibitor. What you do need to understand is the relationship between specific chemical groups and binding affinity. Getting that knowledge can be very difficult if the proposed drug is flexible. In that case, refinement methods that focus only on the particular chemical groups rather than their dynamic properties could go badly astray. Unfortunately, the dynamics of protein-bound drug molecules are difficult to measure. Their proton signals are likely to be swamped by the protein, and small molecules are often difficult to label with isotopes convenient for NMR. Peng et al. propose to address this by studying 13C relaxation at natural abundance.

A little less than 99% of the world’s carbon is in the form of NMR-inactive 12C, which is a problem for NMR because carbon is very abundant in proteins and drugs. Of the rest, most (about 1% of all carbon) is dipolar, NMR-detectable 13C, which is usually not enough to accomplish anything in terms of protein NMR. As a result, NMR researchers typically adopt the strategy of expressing their proteins using bacteria grown in media containing 13C6 D-glucose. Such enrichment of drug molecules probably could not be carried out for pharmaceutical research due to the cost and the limited availability of properly labeled reagents. Fortunately, advances such as magnets stronger than 17 T and cryoprobes make sensitive detection of natural-abundance 13C a plausible approach. Because natural-abundance measurements also simplify the experiments and analysis considerably, Peng et al. adopt this approach in their study.

Peng et al. measure μs-ms fluctuations in a 10-residue peptide in the presence and absence of Pin1. Keeping in mind that such motions can only be detected when they are associated with a change of chemical shift, it is reasonable that no such motions are detected when the peptide is all by itself. In the presence of Pin1, however, methyl groups on phospho-Thr 5 and Val 7 experience some kind of chemical exchange process on the order of several 100 /s (at 278 K), as does a methylene group in Pro 6.

Peng et al. rationalize their observations with reference to a previously-determined structure of the Pin1 WW domain in complex with this peptide (explore it at the PDB). As you can see from the lowest-energy member of this NMR ensemble (left), the residues where they detect these fluctuations in the methyls and methylenes are those that are most involved in the binding interaction. The WW domain is represented as blue ribbons, while the peptide is shown as sticks down at the bottom. That the Pro and pThr form part of the interface is unsurprising, as they constitute the specific binding sequence, while the Val side chain appears to be in position to make some hydrophobic contacts. Everything makes sense, but that doesn’t mean it’s telling us what we want to know.

The structure above shows us the interaction of the peptide with the WW domain, while what we’re really interested in getting at is the catalytic domain. Using an exchange spectroscopy experiment, Peng et al. determined that the ms dynamics they were observing probably reflected the binding of the peptide to the WW domain. To avoid this interaction, they created an artificial Pin1 that contained only the catalytic domain, and found that this also caused chemical exchange in the methyls and methylenes. Cross-checking against the exchange spectroscopy rates suggested that the ms dynamics in this case reflect the result of Pin1 catalytic activity, namely the interconversion from cis to trans and vice versa.

Unfortunately, this experiment did not report the most desired data, i.e. the dynamics of the ligand on the enzyme. On-enzyme fluctuations certainly contribute to the exchange experienced by the ligand, but because the on-enzyme population is so small (at most 2.5% of ligand) this would only be detectable in the case of an extremely large change in chemical shift. In principle one could deconvolute the dynamics from a partial-occupancy system where 50% or more of the ligand is bound to enzyme, but reliably fitting all the parameters for a two-state chemical exchange system from CPMG data is an already-dicey proposition. Fitting a four-state process from data like these is unlikely to be practical. So, in order to observe on-enzyme dynamics the drug of interest will need be saturated with its target protein, which would require millimolar protein concentrations for most ligands. Under those conditions, the spectra will also contain significant signal from the protein. The 70% deuteration used in this experiment, combined with 13C depletion, will probably be enough to suppress this, although these isotopes will increase the cost of the technique (and diminish protein yields).

Nevertheless, this paper establishes that the natural-abundance approach to measuring ligand dynamics on the µs-ms timescale is feasible. Because methylenes and methyls are common moieties in drugs and small molecules this technique may have broad applicability. Investigating the motions of small molecules bound to large proteins poses a unique problem because these systems don’t have the advantages of either small molecules (low R2) or proteins (exotic labeling schemes). The ongoing work of Peng et al. suggests that this problem is tractable, which may have positive consequences for our ability to design and optimize drugs.

Peng, J., Wilson, B., & Namanja, A. (2009). Mapping the dynamics of ligand reorganization via 13CH3 and 13CH2 relaxation dispersion at natural abundance Journal of Biomolecular NMR DOI: 10.1007/s10858-009-9349-4

 Posted by at 1:00 AM
Mar 172009
 
ResearchBlogging.orgThe observation of plaques composed primarily of amyloid-β (Aβ) peptides in the brains of Alzheimer’s patients long ago gave rise to a hypothesis that Aβ was the agent that caused the disease. The plaques themselves, composed of long, insoluble fibrils of Aβ, were believed to cause the synapse loss and nerve death characteristic of the disease, and some data supports this model. However, several experiments have suggested an alternative possibility: that the symptoms of Alzheimer’s may be attributed to soluble Aβ oligomers. In this view the fibrillar deposits may be an incidental feature of Alzheimer’s disease, or even a defense mechanism whereby the body tries to get rid of the oligomers by forcing them into insoluble aggregates. In the March 10 edition of PNAS, a team led by researchers at Massachusetts General Hospital claim to have reconciled these two models. Using fluorescence microscopy, they find that amyloid plaques are surrounded by a “halo” of Aβ oligomers that kill the surrounding synapses.

The authors of this studied used fluorescence labeling to identify plaques, oligomers, and synapses in thinly-sliced tissue sections and living brains. They performed their experiments in mice that had been genetically manipulated so as to develop amyloid plaques. When they examined the brains of live mice, Koffie et al. noticed that the fibrillar plaques were surrounded by a cloud of the oligomers, as you can see for yourself in the figure below. On the left you can see the plaque core labeled by a fluorescent dye, and the middle image shows fluorescence associated with an antibody that specifically binds to amyloid oligomers. When these images are merged, the diffuse “halo” of oligomers becomes obvious. The authors see a similar result when they perform a similar experiment using thin slices of brains.

The authors also used a fluorescent-conjugated antibody to identify elements of the post-synaptic density (PSD), so that they can identify healthy synapses in the brain. Experiments in tissue sections demonstrated that the number of healthy synapses was reduced not only right next to the plaque, but also in a region extending up to 50 µm away (a length comparable to the diameter of a human hair). Aβ oligomers are also enriched in this region, and the relative concentration of the oligomer roughly correlates with the loss of synapses. By comparing the pattern of Aβ fluorescence to that of the PSD, the authors determined that oligomers were associated with many synapses, and that interactions between PSD and Aβ oligomers resulted in decreased synapse size. The relationship between Aβ binding and reduced synapse size was also shown to hold in control mice expressing normal levels of native amyloid precursor protein.

The observation that the presence of Aβ oligomers correlates with synapse loss, and the apparent degradation of synapses by Aβ, indicates that the soluble oligomers are a significant cause of Alzheimer’s symptoms, although this study does not rule out the possibility that the plaque itself is also toxic. Even if the plaques have no immediate toxic effect, the authors propose that they serve as reservoirs, releasing synaptotoxic Aβ oligomers into the surrounding neural tissue, increasing the size of the lesions beyond the extent of the plaque itself. In this way Koffie et al. believe they have reconciled the previous models — oligomers are directly toxic, plaques release toxic oligomers, so both can serve as causative agents in Alzheimer’s disease.

If this model is accurate, it implies that Alzheimer’s disease may be quite resilient to attack. Antibodies or drugs that break up the Aβ oligomers will be effective in mitigating the synaptic damage, but as long as the plaques persist they will continue to replenish the pool of oligomers. Treatments that successfully break up the plaques will probably result in worsening symptoms due to the release of toxic oligomers as the fibrils disintegrate. These possibilities reinforce the idea that the most treatment for Alzheimer’s will involve reducing the concentration of amyloidogenic Aβ peptides to prevent them from forming plaques in the first place.

(1) Koffie, R., Meyer-Luehmann, M., Hashimoto, T., Adams, K., Mielke, M., Garcia-Alloza, M., Micheva, K., Smith, S., Kim, M., Lee, V., Hyman, B., & Spires-Jones, T. (2009). Oligomeric amyloid associates with postsynaptic densities and correlates with excitatory synapse loss near senile plaques Proceedings of the National Academy of Sciences, 106 (10), 4012-4017 DOI: 10.1073/pnas.0811698106

Aug 022008
 
ResearchBlogging.orgLoads of interesting stuff is going on in Alzheimer’s research right now. While the hot news is about a trial showing significant benefits from going after tau tangles, a recent paper in PLoS ONE continues to investigate the pathology of the amyloid-β peptide. As I’ve mentioned in previous posts, cleavage of the amyloid precursor protein to a 42-residue peptide (called Aβ1-42 in this paper) initiates the formation of peptide oligomers and eventually plaques. Recent research has indicated that these oligomers are sufficient to cause the development of Alzheimer’s disease, but the mechanism by which they do so remains uncertain. Sara Sanz-Blasco and colleagues show that Aβ oligomers disrupt calcium homeostasis in neurons, damaging the mitochondria and promoting apoptosis, and that certain NSAIDs can suppress these adverse mitochondrial effects (1). PLoS ONE is open access, so go ahead, open the article up in another window, and follow along.

Although the appearance of plaques and neuronal death are classic hallmarks of Alzheimer’s pathology, the relationship between these features is not well understood. For instance, it is possible the plaques themselves kill neurons or impair neural function. However, it seems equally likely that the appearance of plaques and the death of neurons are two distinct effects with a single cause. This view is supported by the oligomer toxicity study, but that study fails to resolve the question of exactly how Aβ oligomers kill neurons. Previous work has associated Aβ with derangement of cellular calcium (Ca2+) management — a 2005 paper by Demuro et al. (2) showed that soluble Aβ induced an increase in intracellular Ca2+ in a neuroblastoma cell line. Sanz-Blasco et al. therefore decided to directly test whether Aβ oligomers were increasing Ca2+ levels in neurons, and specifically in mitochondria. In order to do this last bit they used a low-affinity aequorin targeted specifically to mitochondria.

Allow me digress… to many of my readers that probably sounds like a terrible idea. If you’re trying to detect a particular chemical in the cell, it seems like the best thing to do would be to get a high-affinity binding partner. And if figuring out whether there is any calcium in the mitochondria is what you want to do, then a high-affinity detector makes sense. However, when you’re using a small amount of a sensor to detect changes in the concentration of a large amount of ligand, a low-affinity sensor is what you want.

To see why, take a look at the graph on the right. This is just a rough calculation based on a situation where the detector is at a concentration of 100 µM and the concentration of its ligand (that you’re trying to detect) changes from 10 mM to 100 mM. Note that the concentration of the detector is at most 1% that of the ligand. If the dissociation constant KD of this complex is 1 mM (blue) (a lower KD means higher affinity), then the detector is almost saturated when you start, and the percentage occupied doesn’t change very much over the course of the experiment. This means that it will be very difficult to tell the difference between, say, 50 mM ligand and 100 mM ligand, because that amounts to a signal difference of 1% of the maximum response. The situation gets a little better if the KD is 10 mM (green). The lowest affinity detector here (KD = 50 mM, red) actually does the best job of distinguishing between 50 mM and 100 mM ligand, because the difference in response amounts to 17% of the total dynamic range. Ideally, you want to tune the KD of your detector in such a way that its response to changes in ligand concentration is large and linear over the range you are likely to be observing. For the last detector, this range lies between 10 and 40 mM of ligand, so that would likely be the ideal range to investigate with it.

The precise numbers are different in the present paper, but the principle is the same. The affinity you want in your detector will depend on what you are trying to detect and the circumstances under which you are trying to detect it. In this case, the researchers are trying to measure changes in calcium ions over a fairly wide range, which have a pretty high concentration in mitochondria, and they’re doing it using a luminescent protein, which isn’t very concentrated. As a result, a relatively low-affinity detection system is best.

So, what did they find? The results in Figure 1 show that Aβ oligomers and fragments cause an influx of calcium into the cytoplasm of cultured neurons, but preparations of Aβ fibrils did not cause this effect. Moreover, exposure of the cells to Aβ oligomers caused a clear influx of calcium into the mitochondria (Figure 3). This is a problem for a cell because Ca2+ overload in mitochondria can cause programmed cell death, or apoptosis. Using the classic TUNEL assay, the authors of this study showed that the Aβ oligomers caused apoptosis. In addition, they showed that treatment with the oligomers caused the release of mitochondrial cytochrome c (a step in the apoptotic pathway) and that the addition of cyclosporin A, which inhibits the release of proteins from the mitochondrion, blocked cell death (Figure 4). Together, these pieces of evidence support the idea that Aβ-induced Ca2+ influx into the mitochondria activates the apoptotic cascade, leading to neuronal death. These results are consistent with a very cool study published this week in Neuron (3) showing that amyloid plaques correlated with high neuronal Ca2+ levels in vivo (in live mice).

On its own this is pretty interesting, but Sanz-Blasco et al. push it a bit further. Because they had shown previously that some NSAIDs prevent mitochondrial Ca2+ uptake in a cancer cell line, they decided to find out if they would work in this instance, too. As you can see from Figure 6, the three NSAIDs tested kept the mitochondria calcium-free, even if the cells were treated with Aβ oligomers. NSAIDs also prevented cytochrome c release and cell death (Figure 8).

Some readers may recall that Kukar et al. showed that certain NSAIDs prevent oligomerization of Aβ1-42, hinting at a possible explanation of these results. However, the controls performed by Sanz-Blasco et al. show that under the conditions of these experiments the NSAIDs they used have no effect on cytosolic Ca2+ concentrations (Figure 7). If it is amyloid oligomers that let Ca2+ through plasma membranes, then this would appear to rule out structural disruption as a mechanism. Instead, Sanz-Blasco et al. propose that these NSAIDs specifically alter the polarity of the mitochondrial membrane in such a way as to prevent Ca2+ uptake.

If this is true, then NSAIDs may be able to perform a double-whammy on Alzheimer’s disease. On the one hand, they appear to be capable of altering Aβ cleavage patterns to reduce the formation of toxic oligomeric precursors. In addition, they appear to have an ability to block mitochondrial breakdown and subsequent apoptosis directly. While this is encouraging, and speaks to the value of pursuing refinements of existing NSAIDs as possible Alzheimer’s treatments, this experiment doesn’t necessarily prove any therapeutic value. Even if the neurons are saved from death, the calcium flood may impair their function to such a degree that their continued survival doesn’t matter. Only clinical trials and further research can firmly establish whether current or optimized NSAIDs can provide significant protection against Alzheimer’s disease.

1. Sara Sanz-Blasco, Ruth A. Valero, Ignacio Rodríguez-Crespo, Carlos Villalobos, Lucía Núñez (2008). Mitochondrial Ca2+ Overload Underlies Aβ Oligomers Neurotoxicity Providing an Unexpected Mechanism of Neuroprotection by NSAIDs PLoS ONE, 3 (7), 0-0 DOI: 10.1371/journal.pone.0002718 OPEN ACCESS

2. A. Demuro, E. Mina, R. Kayed, S.C. Milton, I. Parker, C.G. Glabe (2005). Calcium Dysregulation and Membrane Disruption as a Ubiquitous Neurotoxic Mechanism of Soluble Amyloid Oligomers Journal of Biological Chemistry, 280 (17), 17294-17300 DOI: 10.1074/jbc.M500997200 OPEN ACCESS

3. K Kuchibotla, S Goldman, C Lattarulo, H Wu, B Hyman, B Backsai (2008). Aβ Plaques Lead to Aberrant Regulation of Calcium Homeostasis In Vivo Resulting in Structural and Functional Disruption of Neuronal Networks Neuron, 59 (2), 214-225 DOI: 10.1016/j.neuron.2008.06.008