Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods. Intra-protein communication has recently attracted an increasing interest from the scientific community, because of its important functional consequences: allostery and signalling. Unravelling how information is processed and transferred within a protein structure requires the study of the dynamical effects of, for instance, binding events, which may be captured experimentally by NMR relaxation experiments. Given the complexity of this experimental analysis, computational approaches, often based on molecular dynamics simulations, have been proposed for predicting these dynamical effects, using protein structural information as input. We examine here the accuracy of these predictors in the context of a well-studied domain, i.e. the second PSD95/Disc-large/ZO-1 domain (or PDZ domain) of PTP1e, and compare it to our approach that combines Monte-Carlo sampling of the conformational space of the side-chains and an information theoretical analysis. The results we discuss in this manuscript show clearly that the latter method provides very accurate predictions when compared to the experimental results, and has a better predictive quality compared to other computational approaches. The predictions, which are consistent between closely related structures, and the global network perspective provided by this approach, improve our understanding of intra-protein communication and allostery in these domains. PDZ (PSD95/Disc-large/ZO-1) domains In order to understand and predict the nature of such intra-protein communication, structural and dynamical data regarding proteins or domains in their major states are necessary. In this sense, the PDZ data gathered by Andrew Lee and colleagues The dynamical hPDZ2 data also provides a unique validation set for computational methods that aim to predict intra-domain information exchange from either structural or sequence-related information. Kong and Karplus Using the publically available structural data on hPDZ2 To determine the residues throughout the hPDZ2 structure affected by peptide binding, we quantify the change in conformational coupling between residue side-chains within the major states of the domain, i.e. the bound and unbound states Our analysis of these ΔMI values focuses first on the changes in the conformational couplings of methyl-group containing residues, as these results can directly be compared to the experimental data BS) residues L18, I20, V22, V26, V30 and L78 (predicting 6 out of 6 residues), as well as the majority of residues in the two distal surfaces identified in Examining the sub-matrix in Interestingly, additional methyl-group containing residues are identified by our method, located in either BS , DS1 (T77) or DS2 (V37) see . Others informative group. This informative group covers the strongest dynamical effects induced by peptide binding over the entire domain.Together with the set of methyl-group containing residues, our information theoretical approach identifies at the same time a number of non-methyl-group containing residues, which may have an important role in the intra-protein communication of hPDZ2. For example, residue H71, which has been extensively explored in the context of the evolutionary conserved network of energetically-coupled residues To clearly visualize the informative group, we created a network of residue interactions including only those pairwise local interactions that have non-random ΔMI see  from theThe clustering analysis on the ΔMI matrix visualized in Figure S1 in positives (P) or negatives (N) on the basis of the experimentally determined dynamical data reported in t, required by the clustering method that we used to identify the informative group  curves see  and comproup see . A high Our predictions deliver significantly better results in terms of the area under the ROC curves (AUC), when compared to the curves derived for both the random and betweenness-centrality models see . In caseThe difference between the all-residue and methyl-residue informative groups at low levels of FPR and TPR originates from the higher rank given by the first predictor to true negative residues T77 and I35  for the methyl side-chain matrix of dynamical changes, and 2 = t0.027 (TPR = 0.64 and FPR = 0.18) for the entire matrix of dynamical changes , which cannot be considered significant. The ROC curve for this combined predictor is reported in Figure S3 in t as derived for the hPDZ domain (vide ante).Given the encouraging quality of our predictions on hPDZ2, we decided to analyze the equivalent PDZ domain of the mouse homolog PTP-BL (subsequently denoted as mPDZ2). This domain has a 94% sequence identity with hPDZ2, differing mostly in a few of amino acids along the β1–β2 and the β3-α1 linkers network of dynamical changes can be predicted from the publically available structures, showing strong overlap with the experimental data The I35V mutant, which did not show any dynamical role in Hence, next to the already strong overlap with the experimental results in In addition, other predictive approaches, including the work described in Although the predictive accuracy of our method is clearly better than those provided by the null models and the other computational methods, our approach also suffers from a specific limitation, as it is unable to predict the dynamical effects of alanine residues from only the side-chain dynamics. The small side-chains of alanine residues are conformationally invariant and thus show a uniform distribution corresponding to a single conformation, which implies no uncertainty associated to the outcome of the corresponding random variable. Consequently, this results in zero entropy values and hence zero mutual information shared with the other residues in the domain. To test the impact of this issue, we also calculated the ROC curves excluding the alanine residues from the quality assessment . This adUsing the best predictive threshold for the network of dynamics changes in hPDZ2, we also determined the network of dynamical changes for the mouse variant of this domain. We show in the alignment of Figure S6 in t to extract the informative group from the matrix of dynamical changes, which was optimized for hPDZ2. Clearly, in order to establish an optimal threshold for t, it should have been determined on the basis of a number of independent datasets of different proteins. Currently, we cannot exclude that the value t selected here may add or exclude certain residues unwillingly. Nevertheless, our results show clearly that the dynamic regions within the core of both hPDZ2 and mPDZ2 are almost equivalent.Eight methyl-group bearing residues, four for each domain, characterize the differences between the two variants see : four reOne particular difference between both domains is the amount of positive and negative changes, visualized by red and blue links, respectively, in Finally, even though for hPDZ2 our approach has a higher accuracy than the other methods, great care must be exercised in generalizing the conclusions since only one complete data set is available. To further evaluate and improve all current methods additional NMR data sets, containing both structural and dynamical information, are required. Only then we can assess if these methods are capable of assisting biological research in understanding the mechanisms of both intra-protein communication and allostery.The human variant of the PDZ2 bound and unbound forms, used in this paper, correspond to NMR PDB structures 1D5G To sample the conformational space of each side-chain, we need to identify a fine-grained alphabet of side-chain conformations. As explained before in detail This fine-grained dihedral angles dataset supplies a high-resolution enumeration of the side-chain conformational space for every residue in the structure. This position-specific alphabet covers the conformational space of the residue side-chain over all backbones, ensuring in this manner that all acceptable conformations can be visited during the sampling process. Once the alphabet is determined, we sample the conformational space of every side-chain relative to a particular backbone conformation using Monte-Carlo Sampling with Metropolis Criterion.p as given by the formula: Each Monte-Carlo process takes one backbone extracted from the NMR ensemble as input, alters the side-chain conformations towards other favourable states present in the alphabet, and stores at regular intervals (every 1000 iterations) the conformational state of the entire domain. The FoldX force field determines whether a certain change in conformational state is favourable by calculating its free energy change ΔG. The Metropolis criterion states that this change is accepted with a probability Prior to the actual sampling, the process first executes an energy minimization phase, to ensure that the sampling commences from a low-energy state. In order to collect many data points we ran the Monte-Carlo sampling process many times in parallel using the same backbone starting conformation, combining the results into one file when all processes were finished. In our simulations we recorded, for each ensemble, 751500 domain conformations.The sampling procedure is applied to the ensembles in the two states (bound and unbound). Each one of the sets of sampled conformations is composed of side-chain configuration distributions of each residue in the domain. Therefore, each residue corresponds to a random variable, and its realizations correspond to the side-chain conformations the residue takes. The mutual information between two of these distributions quantifies the amount of dependency (or information transfer) between side-chain movements of two residues, details discussed in A and B, the mutual information I is computed as I = H(A)+H(B)−H, where H(A) and H(B) are the Shannon's entropy and H is the joint entropy between A and B, defined as follows:Given two discrete random variables We look at the changes in dynamical couplings upon a binding event by computing the absolute difference in mutual information between the two states: −12), smoothing out the probability distribution. This new data was then discretized using the fixed frequency discretization method Since the original method, discussed in The MI values computed from the sampled distributions, which were close to those expected for the randomized distributions (i.e. close to zero) of each residue pair, were filtered out of the matrix, since they were considered of no relevance for the major information flows throughout the structure.t. Every time a new cluster is created, the algorithm alternates between “add” and “remove” steps until the cluster stabilizes. High affinity residues are added to the current clique and low affinity ones are removed. The affinity of a residue ir with respect to a clique C is defined as Given the matrix of dynamical changes, we applied the Cluster Affinity Search Technique (CAST) We built the network of residue contacts starting from the crystal structures of hPDZ2 in the two states. An edge between two vertices (residues) is added if the two residues have at least one pair of atoms at a distance less than or equal to 5 Å in the crystal structure. The resulting networks show small-world properties The measure of node betweenness-centrality proposed in t and computing False Positive Rate (FPR) and Sensitivity or True Positive Rate (TPR) levels. FPR and TPR are computed comparing the predictions of a computational approach with the residue labeling based on experimental results reported in ROC curves give a picture of the overall performance of a predictor, which is not dependent on the chosen discrimination threshold. We drew ROC curves by varying the threshold α atoms from their centroid and we took it as a measure of backbone flexibility. We then calculated the differences in flexibility between the bound and the unbound state. We computed z-scores of these differences and we highlighted, in Backbone variations are computed starting from the two NMR ensembles of the domain in the two states. After superposing all structures in the NMR ensemble, by using the MUSTANG structural alignment algorithm i in the ranking produced by our side-chain dynamics based predictor, and ir results from the weighted sum of the ranking positions. The final rank of predictions is obtained by sorting the residues according to the resulting ir, while breaking ties at random. The ROC curve of the resulting predictor is reported in Figure S3 in α = 1.5 and β = 1 by giving a 50% more importance to the side-chain dynamics information with respect to the backbone one.The results of the two predictors, one based on the change in MI shared between residue side-chains and the other based on the change in backbone flexibility, were combined by taking the two ranks of the residues, in the following way:Text S1Supporting information: Accurate prediction of the dynamical changes within the second PDZ domain of PTP1e. The text contains additional information, figures and tables related to the manuscript.(PDF)Click here for additional data file.


Liopholis kintorei from Central Australia, constructs an elaborate multi-tunnelled burrow that can be continuously occupied for up to 7 years. Multiple generations participate in construction and maintenance of burrows. Parental assignments based on DNA analysis show that immature individuals within the same burrow were mostly full siblings, even when several age cohorts were present. Parents were always captured at burrows containing their offspring, and females were only detected breeding with the same male both within- and across seasons. Consequently, the individual investments made to construct or maintain a burrow system benefit their own offspring, or siblings, over several breeding seasons.Constructing a home to protect offspring while they mature is common in many vertebrate groups, but has not previously been reported in lizards. Here we provide the first example of a lizard that constructs a long-term home for family members, and a rare case of lizards behaving cooperatively. The great desert skink,  Cooperative behaviour and social aggregations are relatively common in many animal groups, but rare in lizards, a large and otherwise behaviourally diverse group Egernia and Liopholis genera have kin-based sociality, a trait that is considered pleisomorphic to the group Xantusia vigilisLiopholis and Egernia genera, species that form long-term groups tend to aggregate in pre-existing retreat sites, mostly rock crevices Liopholis kintorei constructs and maintains an interconnected network of tunnels within which it aggregates Liopholis kintorei is viviparous with 1–7 offspring produced annually Several lizard species belonging to the closely allied Here we evaluate the longevity of these burrow systems, whether multiple individuals construct and share tunnels, the relatedness among group members and their dispersal characteristics. Because kin-based sociality is an ancestral trait Adult and immature individuals use, share and maintain more than one tunnel in the system. This was directly observed and was evident from fresh tracks left by different sized individuals at tunnel openings. Tunnels are mostly excavated and maintained by adults and immature lizards contribute small ‘pop’ holes to the network. These are too narrow to be maintained by adult individuals. On average, only 6% of tunnels within a burrow system became disused each year. From the first record of the 26 burrow systems, the average (± s.d.) period of continuous occupancy in years is 4.04±1.43 , each ofPolygynous males were detected with 40% of the male parents siring offspring to different females, and these were each located in different burrow clusters (separated by 18–179 meters). Juveniles from a single breeding season that were assigned the same mother show an absence of multiple paternity, and all females for which more than one age cohort of offspring were identified had bred with the same male across more than one breeding season. Only a single female was located in a different burrow system to one of its offspring (67 meters separate). As a consequence, groups of immature lizards only contained full siblings in 18 of 24 burrow systems where more than one immature lizard was sampled, and 12 of these contained siblings of more than one age cohort . A low lLiopholis kintorei cooperates to construct a burrow system that houses close kin  and therefore have less choice when it comes to the location of their housing but still live in large kin-based social groups L. kintorei may influence aspects of their sociality. For example, it would be of interest to explore whether the proximity and longevity of termite colonies are associated with group sizes of L. kintorei and the length of time for which they occupy their tunnel systems.In mole rats the food-aridity hypothesis proposes that less rainfall is associated with increasing sociality because food resources become patchier L. kintorei, which, given the few examples of sociality in lizards, would also seem to explain its rarity.The construction and maintenance of a long-term family home occurs in many other taxa, in vertebrates there are examples from most phyla, though it appears most prevalent in birds and mammals ru – Kata Tjuta National Park, Northern Territory, Australia. From 1999 to 2009 monitoring was carried out once a year between September and April when lizards are most active. Monitoring consisted of searching for new burrow systems and inspecting all previously located burrow systems. For each burrow system the number of entrances and spatial organisation were recorded. Activity levels were noted by recording track activity and the presence of any fresh adult and immature lizard scats in their latrine area. Thirty hours of observations were carried out September to December 1996 within a raised hide located 8 meters from a burrow system containing an adult pair and 4 immature lizards. During this time burrowing activity, lizard locations and interactions were recorded. Trapping was undertaken during the summer activity periods at spatially discrete burrow systems distributed across 45 km2. Tissue biopsies were taken from the tail tips of 31 adult and 89 juveniles, with groups of individuals  sampled from 26 burrow systems. Sexing of adult individuals was carried out by visual appraisal. All methods involving L. kintorei were carried out in accordance with a protocol considered and approved by Parks Australia and the Macquarie University Ethics Committee under the Animal Research Authority 2008/025.The study was conducted at UluTotal DNA was extracted from 120 tissue samples using a salting-out protocol The maximum likelihood method of CERVUS 3.0.3 and COLONY 2.0.0.1 were used to assign parents to offspring


Activation of cGMP synthesis leads to vasodilation, and is an important mechanism in clinical treatment of angina, heart failure, and severe peripheral and pulmonary hypertension. The nitric oxide-responsive sGC (soluble guanylate cyclase) has been the target of recent drug discovery efforts. The present review surveys recent data on the structure and regulation of sGC, and the prospects of new avenues for therapeutic intervention. Nucleotide cyclases generate two of the most important intracellular messengers, cAMP and cGMP. cGMP causes vasodilation by relaxing vascular smooth muscle cells. It is also involved in reducing platelet aggregation, in neuronal transmission, in vision and in cancer –3. cGMP 2+ channels and phosphodiesterases) to eventually cause muscle relaxation and vasodilation.cGMP in animal cells is generated by two classes of GCs (guanylate cyclases): sGC (soluble GC) and pGC [membrane-spanning (particulate) GC]. sGC is the receptor for nitric oxide (NO). pGCs are transmembrane receptors activated by the peptide natriuretic factors ANF  and BNF (brain natriuretic factor). NO acts in a paracrine manner, secreted by endothelial cells in response to hypoxia and/or mechanical stimuli, and activating sGC in adjacent smooth muscle cells. ANF and BNF are secreted from the heart atrium and brain respectively, and act systemically on ANF receptors. Upon hormone binding, the GC of the intracellular domains is activated, leading to increased cGMP levels. cGMP then activates downstream effectors , derive from ancestral enzymes consisting of homodimers of catalytic domains; they have evolved into fusion proteins with regulatory or membrane-anchoring domains . ACs incThe catalytic core of sGC is composed of two homologous domains. The active site lies at the interface between the two domains. Ligand binding and catalysis require the precise alignment of residues from both subunits; this is very sensitive to relative motion of the subunits as well as to local changes, which underlie the modes of allosteric regulation. We have reported recently a crystal structure of the catalytic domain of human sGC . Structu(i)The isolated catalytic domains of both α and β subunits can form stable homodimers, both of which are enzymatically inactive. When mixed at high concentrations, the subunits can exchange to form heterodimers, which are active even in the absence of NO. Crystal structures were obtained for both the α–β heterodimer and homodimers of the β catalytic domain . The dim(ii)The two subunits are arranged as a wreath-like head-to-tail dimer B. This a(iii)The crystal structure of the heterodimer is in an inactive conformation: the active-site residues from the two subunits are misaligned, and the cavity that should contain the substrate is not formed.(iv)It is possible to model an active conformation by aligning the α and β subunits separately with the two subdomains of an active AC structure. This entails a 26° rigid-body rotation of the α subunit C. In thi(v)The question arises whether the inactive conformation of the catalytic subunits seen in the crystal ever exists in the context of the full-length protein. The catalytic domains are linked directly to an upstream CC domain, which is expected to be quite rigid. As seen in The studies of the catalytic domains have revealed the following features.Other regions of sGC have been crystallized successfully. The CC region preceding the catalytic domain of the β subunit has been crystallized as a four-helix antiparallel bundle . The autManduca sexta was published recently [The structure of a PAS domain of sGC from the moth recently . Althougrecently . This en105) on the distal face of the haem group. This leads to structural changes in helix αF that contains His105, which are thought to be critical in transducing the signals to the catalytic domain. The important role of this region of the HNOX domain in cyclase activation is supported by mutagenesis and by hydrogen–deuterium exchange analysis [Finally, HNOX domains of sGC have not been crystallized, but structures of highly homologous domains from cyanobacteria have been solved –20. Thesanalysis –24.in trans by adding large concentrations of the purified regulatory domain [in trans is not relieved by NO [110) reportedly led to a modest increase in the basal (i.e. NO-independent) cyclase activity of the full-length protein [in trans resulted in localized changes in hydrogen accessibility in the catalytic domains of both the α and β subunits, primarily in the ‘front’ side; this footprint is consistent with the HNOX/PAS domains blocking substrate entry to the active site. Notably, when comparing the hydrogen–deuterium exchange pattern of the isolated catalytic domains with the full-length protein , the footprint on the β subunit is shifted, indicating a difference in the interaction interface.The simplest regulatory scheme for sGC envisions inherently active catalytic domains which are inhibited by the N-terminal domains in the absence of NO. NO binding to the haem causes a structural change in the HNOX domain which is allosterically transmitted to the catalytic domain, leading to relief of inhibition. Support for this scheme comes from the observation that the isolated catalytic domains of α1 and β1, when mixed, exhibited concentration-dependent cyclase activity; this activity could be inhibited y domain . A proteed by NO . Further protein . Another protein ,26. A th105. However, this is not the whole mechanism, as binding of a single molecule of NO leads to only a modest activation, which is enhanced severalfold by binding of additional NO molecule(s) to lower-affinity sites [The primary activation switch of sGC is the binding of NO to a sixth co-ordination site of the haem iron in the HNOX domain of the β subunit and subsequent breaking of the bond to Histy sites ,27–29; tThe development of drugs that allosterically activate sGC was initiated following the serendipitous discovery of YC-1, which can stimulate cyclase activity 30–40-fold in the absence of NO, but can also synergize with NO. Activation by YC-1 required the presence of Fe(II)-haem. Extensive efforts to improve the potency, selectivity and pharmacological properties led to the development of two classes of sGC modulators ,30. The 105 bond and additional covalent and conformational changes in the HNOX domain, which are transmitted to the catalytic domains through a combination of direct contacts and other long-range interactions. The enzyme may be inactivated by oxidation, nitrosylation (sylation D and haesylation E. AllostKm. Interestingly, this implies a non-equivalence between the two nucleotide-binding sites [We now turn to allosteric effects at the level of the isolated catalytic domain. In pGC, the dependence of the cyclase activity on GTP concentration shows a sigmoidal curve with a Hill coefficient of 1.5. This is taken as evidence of co-operative binding to two sites, probably the catalytic and the pseudosymmetry sites. ATP acts as an activator of cyclase activity; in the presence of ANF, ATP converts the GTP dependence into a Hill coefficient near 1, and decreases the ng sites . There mng sites ,34.It is instructive to compare the situation with ACs in which the catalytic core is composed of two subdomains within a single polypeptide. The plant diterpene forskolin is a signal-independent activator of AC, which binds in the pseudosymmetry site. It may work by stabilizing the association of the two subdomains; indeed, all crystal structures of mammalian ACs contain forskolin analogues in the pseudosymmetric site. As we do not know the structure in the absence of forskolin, it is possible that the drug not only stabilizes the complex, but also favours a subset of possible conformations of the dimer.As for sGC, ATP and 2′-substituted analogues have been found to inhibit GC activity, at physiological concentrations of ATP ,35. InhiThe pharmacology of cardiovascular diseases is extremely complex, reflecting the need to modulate different components of the system in a specific temporal and spatial manner, and interact with endogenous regulators which are patient-specific. There is no doubt that sGC is an attractive target for cardiovascular disorders, ranging from angina and heart failure to peripheral and pulmonary hypertension ,38. Even


Nature has shaped the make up of proteins since their appearance,  Nature has come up with an enormous variety of protein three-dimensional structures, each of which is thought to be optimized for its specific function. A fundamental biological endeavor is to uncover the driving evolutionary forces for discovering and optimizing new folds. A long-standing hypothesis is that fold evolution obeys constraints to properly fold into native structure. We here test this hypothesis by analyzing trends of proteins to fold fast during evolution. Using phylogenomic and structural analyses, we observe an overall decrease in folding times between  The catalog of naturally occurring protein structures Here we propose that foldability is a constraint that crucially contributes to evolutionary history. Optimization of foldability during evolution could explain the existence of a folding funnel The balance between the need for new structural designs and functions in evolution and the physical requirements imposing pressure on folding has remained elusive. The increasing number of organisms with completely sequenced genomes and experimentally acquired models of protein structures, combined with new techniques to study the folding behavior of proteins now open new avenues of inquiry. A common approach for such studies has been the use of molecular simulations such as lattice or coarse-grained techniques, which are efficient enough to scan sequence space. Simulations generally involve an algorithm that mimics the evolutionary accumulation of mutations. This allows to monitor how proteins are selected and evolve towards specific features that are optimized, including those linked to folding, structure and function Here, we reveal evolutionary patterns of foldability by mapping the SMCO and thus the folding time onto timelines derived from phylogenomic trees of domain structures . RemarkaTo trace protein folding in evolution, we determined the SMCO of protein domain structures at the Family (F) level of structural organization. proteins , and alsproteins . Similarproteins . Remarkaproteins . As an aAs suggested by the decrease in SMCO, during evolution, domains diminish long-range and favor short-range interactions, thereby becoming more strongly connected locally. This picture was further corroborated by an analogous analysis of evolutionary trend in tightness, measured by shortest paths in the network of protein contacts the SMCO . Our resIn contrast, we observed an increase in SMCO between  present . Thus, tGiven the observed overall evolutionary speed-up of protein folding, we would expect a late evolutionary appearance of so-called downhill proteins, which feature ultra-short folding times on the microsecond scale. We annotated 11 downhill folders The length of the amino acid chain has been reported to influence the folding kinetics of a protein, with longer chains folding more slowly We next eliminated the effect of domain size on the evolutionary trends observed in folding rate to analyze factors other than domain size. To this end, we dissected our dataset according to the amino acid chain length. This analysis was done with all data set , and holdata set , S8. As After the “big bang”, the SMCO and thus foldability showed a overall increase in evolution , in agreSecondary structure composition is another factor reported to have an influence on folding kinetics Interestingly, we here observe a specialization of protein classes, with all-in level . Why shoProtein aggregation damages cellular components and can lead to a variety of neuronal diseases Here, we confirm the hypothesis that foldability exerts a constraint in the evolution of protein domain structures, as we find a tendency of proteins to on average fold faster than their structural ancestors. As expected, shortening of protein chain length during evolution is an important factor leading to faster folding. However, the exclusion of this protein-size effect preserved the trend of decreasing folding times. Thus, faster folding is not a side effect of chain shortening, but likely acts as an evolutionary constraint in itself. An alternative reason for the decrease of folding times in evolution is the need of proteins for flexibility in order to optimize their function such as enzymatic catalysis or allosteric regulation Evolutionary constraints on folding are apparently not uniformly imposed onto the full repertoire of protein structures and during the entire protein history. Instead, our analysis revealed a bimodal evolutionary pattern, with folding speed increasing and decreasing before and after Finally, we revealed striking evolutionary diversity in protein folding when comparing all-analysis . We hereAn important experimental study by Baker and colleagues We end by noting that we cannot exclude overlooking effects on folding times from cooperative folding. These could influence trends of folding times. The SMCO is known to show high correlations with folding times only for single-domain proteins A most parsimonious phylogenomic tree of F domain structures was reconstructed from a structural genomic census of 3,513 Fs (defined according to SCOP 1.73) in the proteomes of 989 organisms  with genomes that have been completely sequenced http://www.cathdb.info/download), and removed the PDB chains with two or more CATH domains or NMR structures or obsolete PDB entries. We then eliminated redundancy using the PISCES webserver (http://dunbrack.fccc.edu/PISCES.php) As a measure for the folding time of each protein architecture, we evaluated the size modified contact order (SMCO) of domains indexed in the SCOP database. We used the ASTRAL repositories to download the 92,470 three-dimensional structures classified in SCOP 1.73. The phylogenomic tree was built at the F level on the basis of the same protein structures, i.e. the 1.73 SCOP version. We note that the SMCO calculations are based on single protein domains from SCOP, while many proteins consist of multiple domains. Some studies showed that interactions between domains might affect folding  in SMCO  as those in SMCO .We calculated the average SMCO for each F and SF, and mapped these averages, 3,513 of them for F, and 1,915 for SF, onto timelines derived from corresponding phylogenomic trees. Average SMCO of each F or SF as a function of node distance showed non-linear dependencies that were therefore analyzed using LOESS  Figure S1Size Modified Contact Order (SMCO) versus approximate domain age (Gya) a) of domains belonging to the same SF, and b) of domains with less than 95% identity, and c) of domains belonging to the same F. In a) and b), a polynomial regression is shown as black solid line. In c) a linear regression for 3.8 to 1.5 Gya and 1.5 Gya to today was used. The gray area indicates the 95% confidence interval.(TIF)Click here for additional data file.Figure S2Evolutionary changes for an experimental dataset (TIF)Click here for additional data file.Figure S3Change in length and foldability during evolution on the SF level using TrEMBL database a) Size Modified Contact Order (SMCO) versus approximative SF domain age in billion of years (Gya). Each data point represents a single domain from the TrEMBL database. b) Average amino-acid chain length for single domains versus SF domain age in Gya. The solid line shows a linear regression, and the dashed line the 95% confidence interval.(TIF)Click here for additional data file.Figure S4Change in length and foldability during evolution on the F level using TrEMBL database a) Size Modified Contact Order (SMCO) versus approximative F domain age in billion of years (Gya). Each data point represents a single domain from the TrEMBL database. b) Average amino-acid chain length for single domains versus F domain age in Gya. The solid line shows a linear regression, and the dashed line the 95% confidence interval.(TIF)Click here for additional data file.Figure S5Tigthness versus approximate domain age (Gya). A polynomial regression is shown as black solid line. The gray area indicates the 95% confidence interval.(TIF)Click here for additional data file.Figure S6Size Modified Contact Order (SMCO) versus folding rate for 87 proteins with experimentally known folding rates (TIF)Click here for additional data file.Figure S7Distribution of domain length for domains at the 95% similarity appearing a) 3.8-(TIF)Click here for additional data file.Figure S8Distribution of domain length for domains at the 40% similarity appearing a) 3.8-(TIF)Click here for additional data file.Figure S9Percentages of all domains at the 95% similarity with a positive (blue), negative (yellow), and insignificant (green) (TIF)Click here for additional data file.Figure S10Percentages of all domains at the 40% similarity with a positive (blue), negative (yellow), and insignificant (green) (TIF)Click here for additional data file.Figure S11Change in length and foldability during evolution for single domains a) Size Modified Contact Order (SMCO) versus approximate domain age (Gya) for single domains. In a) and b), a polynomial regression is shown as black solid line. The gray area indicates the 95% confidence interval. In comparaison to the data shown in (TIF)Click here for additional data file.Figure S12Average SMCO for the four fold classes according to their secondary structure: all-(TIF)Click here for additional data file.


Drosophila corepressor required by numerous DNA-binding repressors, many of which are distributed in gradients and provide positional information during development. Gro contains well-conserved domains at its N- and C-termini, and a poorly conserved central region that includes the GP, CcN, and SP domains. All lethal point mutations in gro map to the conserved regions, leading to speculation that the unconserved central domains are dispensable. However, our sequence analysis suggests that the central domains are disordered leading us to suspect that the lack of lethal mutations in this region reflects a lack of order rather than an absence of essential functions. In support of this conclusion, genomic rescue experiments with Gro deletion variants demonstrate that the GP and CcN domains are required for viability. Misexpression assays using these same deletion variants show that the SP domain prevents unrestrained and promiscuous repression by Gro, while the GP and CcN domains are indispensable for repression. Deletion of the GP domain leads to loss of nuclear import, while deletion of the CcN domain leads to complete loss of repression. Changes in Gro activity levels reset the threshold concentrations at which graded repressors silence target gene expression. We conclude that co-regulators such as Gro are not simply permissive components of the repression machinery, but cooperate with graded DNA-binding factors in setting borders of gene expression. We suspect that disorder in the Gro central domains may provide the flexibility that allows this region to mediate multiple interactions required for repression.Groucho (Gro) is a  Drosophila Groucho (Gro) and its orthologs in other metazoans lack DNA-binding domains and are recruited to the template by numerous DNA-binding repressor proteins including HES family repressors, Engrailed, Dorsal, Capicua (Cic), and Brinker (Brk) As corepressors, Many of the DNA binding repressors through which Gro acts, including Dorsal, Cic, and Brk, are distributed in concentration gradients that provide positional information along developmental axes. A graded factor is able to subdivide fields of developing cells because different target promoters respond to different threshold concentrations of the factor and are therefore expressed in domains with differing borders. Previous efforts to understand how target promoters can respond to different concentrations of DNA binding transcription factors have usually focused on the role of the DNA binding factors themselves, with particular attention to such parameters as binding site affinity, cooperative binding to DNA, synergy and antagonism between DNA bound factors, etc. Gro/TLE family members are characterized by a conserved N-terminal domain (the Q domain), a variable middle region that can be subdivided into GP, CcN, and SP domains, and a conserved C-terminal WD-repeat domain The roles of the conserved Q and WD-repeat domains are well studied. The Q domain is required for Gro homo-oligomerization, and point mutations within this domain that disrupt self-association also interfere with Gro-mediated repression Less is known about the poorly conserved central region. This region, along with the Q domain, mediates binding of Gro to hypoacetylated histone N-terminal tails A model for Gro-mediated repression that incorporates some of the above-described biochemical functions of its domains is as follows: Once Gro is recruited via interactions with repressors, its ability to self-associate and to bind histone tails allows it to polymerize along the template establishing a transcriptionally silent domain In this study, we examined the roles of the unconserved Gro central domains in Gro-mediated repression and pattern formation by analyzing multiple Gro deletion variants lacking one or more of the central domains. Our findings indicate that the SP region has a negative role in repression and helps to determine target gene specificity, while the GP and CcN domains are required for repression and viability, thus challenging the notion that essential function and evolutionary conservation go hand in hand. Our studies also indicate that development requires the correct balance between positively and negatively acting Gro domains as excess Gro activity results in the inappropriate resetting of repressor concentration thresholds sufficient to mediate repression. This implies that ubiquitous co-regulators such as Gro may actively cooperate with graded DNA-binding transcription factors in setting the boundaries of developmental domains. Our findings further suggest that such factors cannot be neglected in efforts to predict the targets of DNA binding transcription factors and to predict how such targets will respond to developmental cues.The lack of conservation in the Gro central region suggests that this region might not be highly ordered. To explore this idea, we analyzed the Gro amino acid sequence using well-established algorithms for predicting protein disorder To test the idea that the lack of lethal point mutations in the central domains reflects disorder (and therefore an ability to tolerate single amino acid changes) rather than a lack of function, we set out to examine both the recessive and dominant phenotypes associated with transgenes encoding Gro deletion variants lacking one or more of the central domains . Since tWT). The His-tagged protein was immobilized on Ni-NTA beads and co-immobilization of the 35S-labeled untagged internal deletion variants was assessed by SDS-PAGE followed by autoradiography. Immobilization of the untagged variants was completely dependent on the presence of His-GroNWT (compare lanes 1 and 2), while full length Gro and all the internal deletion variants bound His-GroNWT with comparable efficiency (lanes 2–6). The specificity of the assay was demonstrated by the results obtained with His-GroN40/89D and His-GroN38/87D. Both of these double mutants contain amino acid substitutions in the Q domain coiled-coil motifs required for self-association. In accord with previous findings, the mutations in His-GroN40/89D do not inhibit self-association (lane 7), while the mutations in His-GroN38/87D do (lane 8) In the self-association assays , full-leIn the GST-Brk pull down assays , in vitrThus, we conclude that deletion of the central domains does not interfere with the essential functions of the conserved Q and WD-repeat domains in self-association and repressor binding. Therefore, any effects of these deletions on repression most likely reflect roles of the internal domains in other biochemical interactions essential for repression.WT), or Gro deletion variants lacking the GP, CcN, or SP domains  in a vector containing the bacterial attachment site (attB) for bacteriophage phiC31. These were then introduced into the fly germ line by site-specific integration into a second chromosome phiC31 attachment site (attP) WT is approximately 10 kb in length and includes the gro transcription unit as well as flanking sequences reaching to the neighboring genes both upstream and downstream of the gro transcription unit , a second copy of the transgene resulted in complete lethality.To determine if the central domains are required for viability, we generated genomic constructs encoding full-length Gro . Although the construct encoding GroΔSP gave some rescue, this rescue was ∼5 to 8-fold less efficient than rescue by the wild-type transgene (ΔCR because preliminary misexpression experiments (see the following section) strongly suggested that this construct would lead to dominant lethality.To assess the recessive phenotypes of the deletion variants, the transgenes encoding Groo allele . In cont alleles , stronglransgene . We did In conclusion, the central domains appear to have essential roles in Gro function strongly suggesting that their apparent immutability is a reflection of their disorder. To explore the functions of the central domains further, we have examined the effects of misexpression of the deletion variants in two different developmental contexts: the embryo and the wing disc.WT, GroΔGP, GroΔCcN, GroΔSP, and GroΔCR. qRT-PCR analysis of the transcripts in 0–3 hour embryos encoding the maternally expressed Gro variants indicates that all five variants are overexpressed by ∼4-fold relative to endogenous Gro , twist (twi), dpp, and snail (sna), the Hairy target fushi tarazu (ftz), and the Cic targets huckebein (hkb) and tailless (tll), and apparent activation of the Tll target knirps (kni) , overexpression of active Gro variants would be expected to reduce expression of Gro targets to levels below those seen in wild-type embryos. In accord with this expectation, overexpression of GroΔGP overexpression has essentially no effect on Gro target gene expression. The CcN domain is also critical for repression as GroΔCcN overexpression leads to no repression of Gro targets and, in at least one case (dpp), results in significant activation of a Gro target. Similarly, overexpression of GroΔCR  leads to no repression of Gro targets and, in several cases , leads to significant activation of these targets. Thus, GroΔCcN and GroΔCR may function as dominant negatives, presumably through the formation of mixed oligomers with endogenous wild-type Gro.The qRT-PCR assays indicate that the GP domain is critical for Gro-mediated repression, since, consistent with the genomic rescue experiments, GroΔSP variant resulted in significantly higher levels of repression than overexpression of GroWT, indicating that the SP domain has a negative regulatory function, and explaining the incomplete rescue by GroΔSP. The relative importance of the SP domain appears to be target dependent. For example, deletion of the SP domain increases repression of Cic targets hkb and tll by a factor of ∼2, while deletion of the SP domain increases repression of the Hairy target ftz by a factor of more than 6.Overexpression of the Grokni functions as a control to show that repression due to Gro overexpression is specific for Gro targets. kni is not a direct Gro target, but rather it is a target for repression by Tll. Therefore, overexpression of Gro indirectly activates kni by directly repressing tll. The effects of the other deletion variants on kni expression are consistent with the effects of these variants on tll expression with the exception of GroΔSP, which unexpectedly acts to repress both tll and kni. One possible explanation for this paradox is that SP domain deletion leads to a loss of Gro specificity, turning Gro into a promiscuous repressor of genes that it does not normally repress. To explore this possibility further, we looked at two additional genes not expected to be Gro targets. Genome-wide chromatin immunoprecipitation analysis in embryos (manuscript in preparation) indicates that Gro is absent from the Rpt3 and cinnamon (cin) loci suggesting that these genes are not likely to be Gro repression targets. As predicted, overexpression of GroWT, GroΔGP, GroΔCcN, and GroΔCR results in no change in Rpt3 and cin transcript levels. In contrast, overexpression of GroΔSP results in ∼3-fold repression of both these genes  and vestigial (vg) at the anterior and posterior edges of the developing wing. As a result, misexpression of Gro in the wing disc results in ectopic repression of a lacZ reporter under the control of a vg cis-regulatory module termed the vg quadrant (vgQ) enhancer vgQ-lacZ expression domain.To determine if the above conclusions are applicable in another developmental system, we examined the effect of misexpressing the Gro variants in the developing wing. Anteroposterior (a/p) patterning of the wing imaginal disc requires the Gro-dependent repressor Brk, which silences the expression of genes such as WT or GroΔSP in wing discs results in vgQ-lacZ repression  leads to wing blistering due to inappropriate repression of Gro targets (ΔCR (and to a lesser extent GroΔCcN) results in wing scalloping and supernumerary wing bristles, which are wing phenotypes reminiscent of those that result from reductions in Notch signaling  suggests that these variants are able to associate normally with endogenous Gro in vivo via a properly folded Q domain. Finally, our finding that deletion of the GP, CcN, and SP domain deletions each result in different phenotypes (see below) is inconsistent with the idea that the only role of these domains is to maintain the spacing between the Q and WD-repeat domains.gro gene dosage as we have shown that flies bearing, one, two, or three copies of the gro gene are viable, while a fourth copy results in a loss of viability.Many of the repressors that interact with Gro  are distributed in concentration gradients and repress target genes in a concentration dependent manner to direct the formation of multiple distinct domains of gene expression How can we account for the sensitivity of transcription factor gradient threshold responses to Gro activity levels? One possibility is that the assembly of a transcriptionally silent domain is a highly cooperative process that involves the spreading of Gro across a large chromosomal region. A cooperative process of this type might well be highly sensitive to the concentration of active Gro.ΔSP represses normal Gro targets as well as genes not normally targeted by Gro such as cin and Rpt3, and therefore a normal function of the SP domain may be to safeguard against promiscuous repression. It could do so, for example, by limiting the ability of Gro to spread along chromatin. If phosphorylation of the SP domain further limits spreading, this would explain how this modification could attenuate repression The SP domain apparently functions to keep Gro activity in check as deletion of this domain results in increased repression of Gro targets, decreased target gene specificity (and therefore promiscuous repression), and severely weakened rescue activity. The role of the SP domain in specificity is completely unanticipated since Gro is not a DNA binding protein and therefore would not be expected to have a role in the selection of target genes. However, Gro is capable of binding to chromatin nonspecifically through interactions with histones Both gain and loss-of-function experiments demonstrate that the GP and CcN domains are essential for Gro function in vivo. Previous studies have suggested that the GP domain is required for the binding of Gro to the histone deacetylase Rpd3 and that Rpd3 function is required for Gro-mediated repression Our findings show that although the CcN domain contains a sequence with similarity to a canonical NLS, this domain is not required for nuclear import. This is consistent with previous studies in S2 cells showing that deletion of the putative nuclear localization signal in the CcN domain did not lead to relocalization of the bulk of the Gro to the cytoplasm, whereas deletion of the entire central region did Drosophila Gro and its vertebrate orthologs. This lack of conservation suggests that these domains might not be highly ordered and therefore might be resistant to inactivation by single amino acid changes, a suggestion that is supported by our analysis of the Gro amino acid sequence.Previous studies identifying lethal alleles of Gro failed to turn up mutations that mapped to the central domains A large fraction of proteins, especially in higher eukaryotes, are thought to contain disordered domains subject to rapid evolution. Many proteins with profound significance to human disease, such as the tumor suppressor p53, contain such domains Drosophila Gro and its mammalian orthologs While the central region in Gro family proteins undergo rapid sequence evolution, their functions are often conserved even when the sequence conservation is hard to recognize. For example, the GP domain appears to be responsible for Rpd3/HDAC1 binding both in hkb and tll are more sensitive to increases in GroWT levels than ftz. In contrast, the effect of deleting the SP domain is much more dramatic for ftz than it is for hkb and tll. This may reflect gene specific differences in the mechanism of repression that are intrinsic to the structure of the regulatory region of the gene.Previous studies suggest that Gro may repress transcription by multiple mechanisms including histone deacetylase-dependent and histone deacetylase-independent mechanisms (see introduction). In accord with this idea, some of the findings presented here suggest that the mechanism of Gro-mediated repression may be target gene specific. For example, we show that In conclusion, it seems that the Gro central domains, although not well conserved, have essential roles in Gro-mediated repression and in the regulation of development. A full understanding of the mechanisms of repression by Gro will require the identification and characterization of the many proteins that are likely to interact with the Gro central region and a determination of the roles of these partner proteins in repression. At least some of these partners may well be target gene specific.The plasmids encoding the Gro central domain deletion variants were generated using pET17b-Gro as a template for PCR WT, GroΔGP, GroΔCcN, GroΔSP, and GroΔCR and that also contained 5′ NotI and 3′BamHI restriction sites were inserted into the pUASP transformation vector To generate transgenic UAS constructs that can be expressed in somatic and germ line cells, PCR fragments encoding GroWT, GroΔGP, GroΔCcN, GroΔSP, and GroΔCR with an N-terminal FLAG tag (DYKDDDDK) and containing 5′ XhoI and 3′ SpeI restriction sites were inserted into the S2 cell expression acceptor vector pMK33-BD To generate S2 cell expression constructs, PCR fragments encoding Grogro-containing fragment from the right arm of chromosome 3  was created using the attP-attB-P[acman] recombineering system gro 10 kb).A Gro genomic rescue construct bearing a 10,000 bp ΔGP, GroΔCcN, GroΔSP, we used attB-P(acman)-gro 10 kb as a PCR template. Primers used to generate these rescue constructs are given in To generate genomic rescue constructs encoding the Gro central domain deletions GroDisorder probability in Gro was predicted using the PONDR-FIT™ and FoldIndex© algorithms gro mutant alleles, MB12gro (a strong hypomorph) or MB36gro (a null) TM3 and a rescue construct balanced over CyO were examined to determine the fraction that were homozygous for the gro mutant allele. The expected ratio for 100% rescue is one-third gro/gro to two-thirds gro/TM3 progeny.The progeny of flies containing one of two lethal Mat-Gal4 cross were placed in 40 ul of SDS-PAGE sample buffer , mashed, and boiled. Samples were analyzed by 8% SDS-PAGE and probed with either a 1∶500 dilution of mouse anti-Gro monoclonal antibody (Hybridoma Bank) or a 1∶10,000 dilution of mouse anti-tubulin monoclonal antibody (Sigma) using the Millipore dry blot method. Blots were subsequently incubated with a 1∶10,000 dilution of secondary antibody conjugated to horseradish peroxidase  and signal was detected by enhanced chemiluminescence (ECL) with SuperSignal West Pico substrates (Pierce). To examine Gro expression in wing discs, forty third instar wing imaginal discs from the progeny of a pUASP-Gro×Ser-Gal4 cross were placed into 30 ul of SDS-PAGE sample buffer. Samples were processed and analyzed as described for the embryo immunoblots.To examine Gro expression in embryo, 50 embryos produced by the female progeny of a pUASP-Gro×ΔGP, pET17b-GroΔCcN, pET17b-GroΔSP, pET17b-GroΔCR were used to express the Gro central domain deletion variants. pET3c-His-tagged N-terminal Gro (2–194) wild-type, Gro (2–194) 40/89, and Gro (2–194) 38/87 35S]-methionine. 10% of the translation product was reserved for analysis of the input, while the remaining 90% was diluted into binding buffer  and incubated with Nickel-Nitrilotriacetate (Ni-NTA) beads (QIAGEN) overnight at 4°C. Beads were then washed extensively with binding buffer. Proteins bound to the beads were eluted with SDS-PAGE sample buffer. Samples and reserved input material were analyzed by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and autoradiography.pET17b-Gro 35S]-methionine using the TNT T7 coupled reticulocyte lysate system (Promega). In vitro translated Gro variants were incubated overnight with GST fusion proteins immobilized on glutathione beads at 4°C in HEMNK buffer . Following binding, the beads were washed extensively with HEMNK buffer. Proteins were eluted in SDS-PAGE sample buffer and the eluates, as well as the 10% reserved input material, were resolved by 8% SDS-PAGE and visualized by autoradiography. GST-Brk fusion proteins were expressed with pGEX-5x-1-Brk(441–589) GST-histone tail fusion proteins were expressed in bacteria and purified as described previously using plasmids pGEX-2T-H3, pGEX-2T-H4, and pGEX-2T-control Mat-Gal4 virgin females were crossed with transgenic males containing UASp constructs encoding Gro deletion variants or with control 1118w males and incubated at 25°C. Embryos were collected from F1 females for 3 hours and placed at 25°C for 24 hours to allow completion of embryonic development and cuticle deposition. Cuticles were prepared as described previously Ser-Gal4 virgin females were crossed with transgenic males containing UAS constructs encoding Gro deletion variants or with control 1118w males and incubated at 25°C. Shortly after eclosion, adult wings from the F1 generation were dissected from the flies, washed in methanol, and mounted in 70% glycerol. Adult wings were imaged on a Zeiss Axioscope microscope in brightfield with a 4× objective.4 were stained with 1∶250 diluted mouse anti-FLAG antibodies (Sigma), and wing discs expressing Myc-tagged Gro variants were stained with 1∶400 diluted mouse anti-Myc antibodies (Santa Cruz Biotechnology). Secondary antibodies were goat anti-mouse conjugated with Alexa Fluor 568 (Molecular Probes). DNA was stained with 1 ug/ml DAPI. Confocal images of S2 cells and imaginal discs were obtained on a TCS SPE confocal laser-scanning microscope  using the 100× and 20× objectives, respectively.For subcellular localization of Gro variants, S2 cells stably transformed with the pMK33 vectors encoding the FLAG tagged Gro variants and induced with 0.5 mM CuSOMat-Gal4 virgin females were crossed with transgenic males containing UAS constructs encoding Gro deletion variants or with control 1118w males and incubated at 25°C. Embryos containing maternally overexpressed Gro deletion variants were subjected to multiplex fluorescence in situ hybridization (FISH) as described previously hkb antisense RNA probe, Biotin-16-UTP (BIO) labeled tll antisense RNA probe, and Fluorescein-12-UTP (FITC) labeled sna antisense RNA probes (Roche). Primary antibodies were 1∶300 diluted sheep anti-DIG and 1∶500 diluted mouse anti-FITC. Secondary antibodies were 1∶400 diluted donkey anti-sheep conjugated to Alexa Fluor 555, 1∶400 diluted rabbit anti-mouse conjugated to Alexa Fluor 633, and 1∶400 diluted anti-BIO conjugated to Alexa Fluor 488 (Molecular Probes). Embryos were mounted with ProLong Gold antifade reagent and DAPI (Invitrogen) and images were obtained on a TCS SPE confocal laser-scanning microscope  using a 20× objective.12–18 primer (Invitrogen), M-MLV Reverse Transcriptase (Invitrogen), and RNaseOUT (Invitrogen). cDNA was then diluted 10-fold and added to a 3.6 uM mixture of primer pairs and 2× FastStart SYBR Green mix (Roche). cDNA levels were quantified by qPCR using an Opticon Monitor 3 system (Bio-Rad) and normalized to RpL32 gro, zen, twi, dpp, ftz, hkb, tll, sna, kni, Rpt3, and cin are given in RNA was isolated from 0–3 hour embryos containing maternally overexpressed Gro deletion variants using Trizol reagent (Invitrogen), subjected to RQ1 DNase treatment (Promega), and repurified by repeating the Trizol and phenol-chloroform extractions followed by isopropanol precipitation. 3 ug of RNA was used to make cDNA with an oligo(dT)Table S1Primers used to generate Gro constructs.(DOC)Click here for additional data file.Table S2Primers used for qRT-PCR.(DOC)Click here for additional data file.


Amyloid fibril formation is associated with a range of neurodegenerative diseases in humans, including Alzheimer’s, Parkinson’s, and prion diseases. In yeast, amyloid underlies several non-Mendelian phenotypes referred to as yeast prions. Mechanism of amyloid formation is critical for a complete understanding of the yeast prion phenomenon and human amyloid-related diseases. Ure2 protein is the basis of yeast prion [URE3]. The Ure2p prion domain is largely disordered. Residual structures, if any, in the disordered region may play an important role in the aggregation process. Studies of Ure2p prion domain are complicated by its high aggregation propensity, which results in a mixture of monomer and aggregates in solution. Previously we have developed a solid-support electron paramagnetic resonance (EPR) approach to address this problem and have identified a structured state for the Alzheimer’s amyloid-β monomer. Here we use solid-support EPR to study the structure of Ure2p prion domain. EPR spectra of Ure2p prion domain with spin labels at every fifth residue from position 10 to position 75 show similar residue mobility profile for denaturing and native buffers after accounting for the effect of solution viscosity. These results suggest that Ure2p prion domain adopts a completely disordered structure in the native buffer. A completely disordered Ure2p prion domain implies that the amyloid formation of Ure2p, and likely other Q/N-rich yeast prion proteins, is primarily driven by inter-molecular interactions. Formation of amyloid fibrils and oligomeric intermediates is associated with a wide range of human disorders, including Alzheimer’s disease, prion diseases, and type II diabetes One complication for studying the residual structure of intrinsically disordered amyloid proteins is that these proteins are aggregation-prone, resulting in the rapid formation of a mixture of monomers and aggregated species. When monomers and aggregates coexist in the sample, it is difficult to distinguish the residual structure in the monomer from the aggregate. To address this problem, we have developed a solid-support EPR approach Saccharomyces cerevisiae. The normal function of Ure2 protein is to suppress the protein expression involved in the uptake of poor nitrogen sources when a good nitrogen source is present. At the prion state [URE3], Ure2 protein is sequestered in the aggregated form, allowing the expression of nitrogen catabolism genes for poor nitrogen sources even in the presence of a good nitrogen source. The full-length Ure2 protein is 354-residue long, and consists of an N-terminal prion domain (∼90 residues) and a C-terminal functional domain Ure2 is the protein whose aggregated form is responsible for the prion [URE3] in yeast Many other yeast prion proteins have also been identified In this work, we have introduced a spin label named R1, one at a time, at every 5th residue from position 10 to position 75 of the Ure2p prion domain. To identify residual structures in Ure2p prion domain, we compared the spin label mobility in 7 M guanidine hydrochloride (GdnHCl) and in phosphate buffered saline (PBS). It has been suggested that most proteins under strong denaturing conditions adopt random coil structures 1–89-M. The full sequence of Ure2p1–89-M is shown in 3 M−1 cm−1The construct of Ure2p prion domain was kindly provided by Dr. Susan Lindquist (Massachusetts Institute of Technology). This construct contains the Ure2p prion domain (residues 1–89) and the M domain (residues 125−253) of yeast prion protein Sup35 fused at the C-terminus For spin labeling, dithiothreitol was added to protein solution to a final concentration of 10 mM and was allowed to incubate at room temperature for 20 minutes to break any disulfide bonds, and then the sample was buffer exchanged to the labeling buffer  with a HiTrap desalting column . MTSSL, , was added at 10× molar excess immediately after dithiothreitol treatment and incubated at room temperature for 1 hour.Spin-labeled proteins  directly from labeling reaction were mixed with 100 µl of agarose beads slurry charged with nickel (Agarose Bead Technologies) and the mixture was incubated at room temperature on a nutating mixer for 1 h to allow binding. The beads were then washed three times with 500 µl of GdnHCl buffer . To switch to PBS or PBS with 24% (w/w) glycerol, the beads were washed three times with either PBS buffer , or PBS-G buffer .A D72C mutation was introduced to the cysteine-free pseudo-wild-type T4L, which contains the substitutions C54T and C97A To evaluate if tethering on agarose beads disrupts protein structure, single cysteine mutants covering residues 114–127 of T4L were used for spin labeling and then tethered on agarose beads. These mutants have been described previously EPR measurements were performed at X-band frequency on a Bruker EMX spectrometer equipped with the ER 4102ST cavity. A modulation frequency of 100 kHz was used. Measurements were performed at 20 mW microwave power at room temperature. Modulation amplitude was optimized to each individual spectrum (∼1 G). For each sample, approximately 20 µL of beads slurry was loaded into glass capillaries (VitroCom) sealed at one end. EPR spectra in each figure panel were normalized to the same number of spins.A and g were initially set as xxA = 6.2, yyA = 5.9, zzA = 37.0, and xxg = 2.0078, yyg = 2.0058, zzg = 2.0023, which were determined previously for R1 Spectral simulations were performed using a LabVIEW  interface 1–89-M spectra, two parameters were allowed to vary: isotropic rotational diffusion constant (R), and A0 . Here A0 is used as a variable parameter to account for the effect of solvent polarity on A0, but varying A0 does not affect R. Rotational correlation time (τ) was calculated from τ = 1/(6R). One and two component fits were performed. We found that using two spectral components did not significantly improve the fit, and the parameters of the two components often converge to one set of values. Therefore, we concluded that there is only one spectral component in all the simulated spectra as indicated in the text. Values of τ obtained from simulation are plotted in the figures.For simulation of the Ure2pz-axis anisotropy as previously reported R, A0, and an order parameter (S) were allowed to vary. For the unfolded state, R and A0 were used as variable parameters.For simulation of the T4L spectra, an anisotropic motional model was used for the folded state and an isotropic motion was used for the unfolded state. For anisotropic simulations, diffusion tilt angles were fixed to  =  for 1–89-M, contains the M domain of yeast prion protein Sup35p at the C-terminus 1–89-M is tethered on nickel-charged agarose beads via a His-tag at the C-terminus of the Sup35p M domain. As a result, the Sup35p M domain serves as a long linker between Ure2p prion domain and the agarose beads. Previous studies have shown that the yeast prion state [PSI+] is maintained by swapping the Sup35p Q/N-rich region with the Q/N-rich region of another yeast prion protein New1p or with a polyQ sequence, suggesting that there are no specific interactions between the Sup35p M domain and the prion domain in vitro studies. The general agreement between in vivo prion assays without the Sup35p M domain and in vitro aggregation assays with the Sup35p M domain further suggests that the Sup35p M domain has no specific interactions with various yeast prion domains, including Ure2p 1–89-M forms amyloid fibrils that are similar to the isolated Ure2p prion domain 1–89-M may reveal potential nucleating structures for the fibril formation.The construct of Ure2p prion domain, Ure2p1–89-M under two conditions: a strong denaturing condition with 7 M GdnHCl and a native condition with PBS buffer. The PBS condition is achieved by switching from 7 M GdnHCl to PBS buffer, and therefore a refolding process may have occurred. The EPR spectra in 7 M GdnHCl serve as a reference state for a completely disordered structure 1–89-M adopts a structured state in PBS, the structured state will lead to a decrease in the protein intrinsic dynamics on the picosecond to nanosecond timescale. Decrease in protein dynamics will then lead to decreased spin label mobility and can be detected with EPR.To study the structure of Ure2p prion domain, we performed EPR studies of spin-labeled Ure2ph) and the center field (c) lines, h/c ratio, as a measure of spin label mobility. The h/c ratio of simulated spectra changes more than 2 fold when the correlation time changes from 0.3 to 0.9 ns, providing a sensitive measure of spin label mobility in the sub-nanosecond range  are shown in h/c ratio plot shows that Ure2p1–89-M has higher mobility in PBS than in GdnHCl  glycerol, which has similar viscosity as 7 M GdnHCl The disordered structure of tethered Ure2p prion domain is unlikely to be an artifact resulting from tethering on agarose beads. Previous studies have shown that tethering of proteins on a solid support generally does not perturb protein structure 1–89-M mutants: S40R1 and N55R1. Even though Ure2p prion domain in the absence of solid support will aggregate and will give rise to more complex EPR spectra, the h/c ratio analysis will be dominated by the mobile spectral component, which represents the disordered structure. 1–89-M S40R1 and N55R1. The h/c ratios show that the untethered Ure2p prion domain has higher mobility in PBS than in 7 M GdnHCl  to a native buffer (PBS) after accounting for the solution viscosity  Ribbon diagram of T4 lysozyme structure (PDB entry 2IGC) with the Cα atoms of residues 114–127 shown as spheres. (B) EPR spectra of tethered T4 lysozyme with spin labels introduced at indicated positions. The measurement of center line width (δ) from the EPR spectrum is shown in red. (C) Plot of inverse center line width versus residue positions. The data for untethered T4 lysozyme were published previously  and are reproduced here for comparison. Note that the mobility patterns for the tethered and untethered T4 lysozyme are very similar, suggesting that tethering on solid support does not disrupt T4 lysozyme structure.(TIF)Click here for additional data file.


Severe gastroenteritis and foodborne illness caused by Noroviruses (NoVs) during the winter are a worldwide phenomenon. Vulnerable populations including young children and elderly and immunocompromised people often require hospitalization and may die. However, no efficient vaccine for NoVs exists because of their variable genome sequences. This study investigates the infection processes in protein-protein interactions between hosts and NoVs. Protein-protein interactions were collected from related Pfam NoV domains. The related Pfam domains were accumulated incrementally from the protein domain interaction database. To examine the influence of domain intimacy, the 7 NoV domains were grouped by depth. The number of domain-domain interactions increased exponentially as the depth increased. Many protein-protein interactions were relevant; therefore, cloud techniques were used to analyze data because of their computational capacity. The infection relationship between hosts and NoVs should be used in clinical applications and drug design. Gastroenteritis and foodborne illness epidemics usually occur during the winter. In 1968, an acute gastroenteritis outbreak occurred at an elementary school in Norwalk, OH, USA . The nonThe NoV consists of a positive-sense, single-strand RNA (ssRNA) genome sequence of approximately 7.5 kb with 3 open reading frames (ORFs) –6. ORF2 The NoV structure is formed by 180 capsid protein monomers organized into 90 dimeric capsomers [Because traditional cell cultures cannot replicate NoVs , the phyHigh-throughput sequencing techniques allow several genome sequences to be investigated simultaneously. This enables the mutation tendency of diverse NoV sequences to be examined. The sequence search tool on the Pfam website was used to collect approximately 30 NoV GII genotype 4 sequences to find their corresponding Pfam domains. The 7 main families are Cacli_PP_N (PF08405), RNA helicase (PF00910), Peptidase_C37 (PF05416), RdRP_1 (PF00680), Calici_coat (PF00915), Calici_coat_C (PF08435), and RNA_capsid (PF03035). Because the P2 subdomain is associated with antigenicity by binding to histoblood group antigen receptors, the infection relationship may be hidden by the interactions of Pfam domains extracted from NoV sequences. This study attempts to distinguish the protein-protein interactions (PPIs) from the domain-domain interactions (DDIs) and to use the PPIs to determine the biological regulation of NoVs. Many PPIs are expected, requiring high-capacity computation.Cloud computing enables high-capacity computation. Cloud computing allows data to be collaboratively computed by different computer systems. Three main types of cloud computing services exist: infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). User requirements determine the type of service used. When managing many PPIs , the disSeven Pfam  domains The DOMINE database (version 2.0)  was usedThe number of domains and DDIs increases as the depth increases. The domains and interactions from Depths 1 to 9 are shown in The set of DDIs within each depth was used to locate corresponding proteins for each domain and to construct the putative PPI network. For each domain from a certain depth, all related proteins were extracted from the UniProt Knowledgebase (release 2011_07) —a compreAn attempt was made to find connections between proteins based on the DDIs and to explore their accompanying protein functions. However, the protein interaction network was too complex to identify the proteins relevant to the NoVs. It would be beneficial to retain the most common PPIs that have been verified by the expert curators of the molecular interaction database, MINT . Human pTo examine the DDI strength, the depth is defined as the distance of a domain from the previous domain. Depth 1 includes 13 domains and 12 interactions . HoweverThe DDIs in Depth 1 are illustrated using Cytoscape software  in FigurThe DDIs in Depth 2 are more complex than those from Depth 1. The 4 NoV-related domains are shown in the top-right corner of To show the complexity of the PPI network from each depth, PPI statistics and distinct proteins are listed in The PPI network from Depth 2 is shown in High-throughput genome-sequencing technologies generate vast amounts of sequence data efficiently and economically. Personalized medication could be produced by analyzing individual genome sequences. Domains are the fundamental building blocks of proteins . They plAlthough domains are smaller units than proteins, extending PPIs from the domain level is feasible. This causes 2 main problems: the vast number of protein connections from DDIs and the ability to examine available PPIs for NoVs. Data integration and relationship establishment require extremely complex computations. Cloud computing techniques are available to overcome these obstacles. Applying biological knowledge to organism specificity and infection pathways would assist in comprehending NoVs. This may help researchers develop medical therapies for NoVs. Chemical reactions in living systems are performed by proteins. Understanding protein regulation may assist with understanding disease progression. Domains are basic protein folding and evolution units; therefore, investigating internal DDI relationships is valuable. For this study, we extracted NoV-related domains from the Pfam database to investigate the biological processes during NoV infection phases.NoVs can cause acute gastroenteritis and foodborne illnesses, affecting lives and increasing health care costs. However, no efficient vaccine exists for NoVs. Exploring the regulation of PPIs extending from domains may help identify the relationship between hosts and NoVs. This information could be used in clinical applications and drug design.


Ube3a, a gene that causes Angelman syndrome (AS) when maternally deleted and is associated with autism when maternally duplicated has recently been shown to regulate monoamine synthesis in the Drosophila brain. Therefore, we examined monoamine levels in striatum, ventral midbrain, frontal cerebral cortex, cerebellar cortex and hippocampus in Ube3a deficient and Ube3a duplication animals. We found that serotonin (5HT), a monoamine affected in autism, was elevated in the striatum and cortex of AS mice. Dopamine levels were almost uniformly elevated compared to control littermates in the striatum, midbrain and frontal cortex regardless of genotype in Ube3a deficient and Ube3a duplication animals. In the duplication 15q autism mouse model, paternal but not maternal duplication animals showed a decrease in 5HT levels when compared to their wild type littermates, in accordance with previously published data. However, maternal duplication animals show no significant changes in 5HT levels throughout the brain. These abnormal monoamine levels could be responsible for many of the behavioral abnormalities observed in both AS and autism, but further investigation is required to determine if any of these changes are purely dependent on Ube3a levels in the brain.Childhood neurodevelopmental disorders like Angelman syndrome and autism may be the result of underlying defects in neuronal plasticity and ongoing problems with synaptic signaling. Some of these defects may be due to abnormal monoamine levels in different regions of the brain.  UBE3A gene expression, and maternally derived or inherited point mutations in the UBE3A gene Angelman syndrome (AS) is a severe neuro-developmental disorder with a prevalence of approximately 1 in 15,000 individuals. Characteristic features of this syndrome include developmental delays, speech impairment, ataxia, frequent inappropriate laughter and in some cases abnormal EEG patterns, seizures and microcephaly Maternal duplications of the 15q11-q13 region are clearly associated with an autism phenotype UBE3A gene within neurons UBE3A is a maternally expressed gene within neurons of multiple regions of the brain with highest expression in the hippocampus and cerebellum UBE3A gene encodes a ubiquitin E3 ligase protein called E6-associated protein (E6-AP) that is responsible for targeting proteins for ubiquitination, in some cases leading to protein degradation by the ubiquitin proteasome system Drosophila orthologue of UBE3A, called Dube3a, can regulate monoamine synthesis indirectly through the transcriptional co-activation of GTP cyclohydrolase I, the rate limiting enzyme in monoamine synthesis The underlying molecular defect in AS is a loss of expression of the human et al. generated a Ube3a deficient mouse model by knockout of exon 2 of the Ube3a gene Ube3a mice ((MUbe3a−/P+)) show learning and memory defects Ube3a deficient mice (MUbe3a+/P−)) failed to show any of these characteristics To date, several AS mouse models have been generated with various types of mutations that resemble both chromosomal and point mutations. Initially, Jiang et al. using chromosomal engineering methods to replicate the 15q duplication in a syntenic region of the mouse genome on chromosome 7p Ube3a, which is maternally expressed in neurons, the duplication is classified as either paternal or maternal duplication based on the origin of the duplicated allele. Somewhat surprising was the finding that paternal duplication animals showed impaired social interaction, as opposed to maternal duplication mice, when compared to wild type littermates Ube3a gene, thus forcing increased expression of the maternally imprinted Ube3a gene artificially, showed that indeed elevated Ube3a expression in the mouse brain is associated with autism like behaviors A murine model for 15q interstitial duplication syndrome was recently created by Nakatani Ube3a levels has a direct effect on monoamine levels in different brain regions by using both Ube3a deletion and duplication mouse models. Here we show that Ube3a may be involved in regulating some, but not all of these monoamines thereby influencing synaptic plasticity in the brain. These regional changes in monoamine levels could explain some of the behavioral abnormalities found in both mice and humans when Ube3a levels are decreased or elevated due to chromosomal abnormalities.The aim of this study was to determine if changing Ube3a deficient mice was done as described previously ad libidum. Mice between the ages of 12–15 weeks old were used for all experiments. Wild type littermates were used as controls. For all experiments, six animals were used for each genotype (n = 6), unless otherwise indicated.All mice were maintained on a C57BL/6J background and all experiments performed in accordance with guidelines approved by the University of Tennessee Health Science Center Institutional Animal Care and Use Committee (IACUC). The generation and maintenance of ortho-phosphoric acid, perchloric acid, 5-hydroxytryptamine (5HT), sodium bisulfite, triethylamine (TEA) and 3,4-dihydroxybenzylamine (DHBA) were purchased from Sigma-Aldrich . Sodium octylsulphonate (SOS) and monobasic anhydrous sodium dihydrogen phosphate used in mobile phase preparation were purchased from Fluka Chemie . HPLC grade water and acetonitrile were obtained from Fisher Scientific .HPLC-grade DA, 3,4-dihydroxyphenylacetic acid (DOPAC), epinephrine (E), ethylenediaminetetraacetic acid (EDTA), homovanillic acid (HVA), 5-hydroxyindole-3-acetic acid (HIAA), norepinephrine (NE), g for 25 min at 4°C. Supernatants were filtered through 0.22 µm pore size polyvinylidene fluoride (PVDF) syringe-driven membrane filters  and immediately frozen and stored at −80°C until the time of analysis.Mice were briefly anesthetized with aerosolized isoflurane and fresh brain samples were obtained and partitioned using a dissecting microscope. Tissue samples (approximately 0.05–0.1 g) of striatum, ventral midbrain, frontal cerebral cortex, cerebellar cortex and hippocampus were weighed and then homogenized in 100 µl of ice-cold dissolution buffer  per 10 mg wet weight. All homogenates were centrifuged at 20,000 Primary stock standard solutions were prepared by dissolving 10 mg of DA, DOPAC, E, HIAA, 5HT, HVA and NE in 25 ml of dissolution buffer. These concentrates were then divided into 1 ml aliquots, frozen, stored at −80°C and thawed prior to use at 4°C. Working standards in the ηM range were freshly prepared prior to each assay. Standard curves employed for analyte quantitation were generated with an internal standard 3,4-dihydroxybenzylamine (DHBA). The relationship between concentration and relative response was linear over two orders of magnitude (sample correlation coefficient >0.98), with an overall electrochemical sensitivity of 0.001 mA. The detection limit for all analyses was 20 ρg per injection.ortho-phosphoric acid. The mobile phase was stored at room temperature for no more than 2 days, filtered through a 0.20 µm pore size white nylon filter membrane (Millipore Corp.) and degassed under vacuum for 30 min prior to use.A stock buffer solution containing 75 mM monobasic sodium dihydrogen phosphate, 2 mM SOS, 25 µM EDTA and 100 µl of TEA was prepared in 1800 ml of HPLC grade water. To prepare the mobile phase, this solution was then mixed with 200 ml of HPLC grade acetonitrile and buffered to pH 3.0 using concentrated 18 column  with an ESA Hypersil C18 pre-column . A mobile phase flow rate of 1.25 ml/min and analysis time of 45 min was used for all experiments. System control and data acquisition/processing were performed using ESA CoulArray software (version 1.02). All samples were processed in technical triplicate with median values used for mean calculations.HPLC-EC analysis was performed with an ESA Model 5600A CoulArray® system , equipped with Shimadzu Model DGU-14A on-line degassing unit , an ESA Model 582 pump and an ESA Model 542 refrigerated autosampler. The detection system consisted of three coulometric array modules, each containing four electrochemical detector cells. Electrode potentials were selected over the range of 0 to +700 mV, with a 50 mV increment against palladium electrodes. Chromatographic separation was achieved by auto-injecting 30 µl sample aliquots at 5°C onto a MetaChem Intersil  reversed-phase C4 measurement was done as described previously 4 analysis was performed using supernatants via reverse-phase HPLC–EC as described by Howells and Hyland BHTissue samples (approximately 0.05–0.1 g) of cerebellum and hippocampus were weighed, homogenized and proteins extracted in radioimmunoprecipitation assay (RIPA) buffer. The soluble proteins were then resolved on a NuPage 4–12% Bis-Tris 1.5 mm Gel using MOPS buffer  and transferred to an Immobilon-FL PVDF membrane (Millipore). The membrane was blocked with 5% milk, 3% BSA and 0.1% Tween-20 in Phosphate Buffered Saline (PBS). α-E6-AP (Sigma-Aldrich) and α-GAPDH (Imgenex) primary antibodies were used at a concentration of 1∶1000 and 1∶2500, respectively. Infrared (IR) labeled secondary antibodies (α-Rabbit 800 and α-Goat 680) from Li-Cor  were used at a dilution of 1∶10,000. The blot was imaged and analyzed using the Odyssey Infrared Imaging System . Lanes were normalized using signals from GAPDH as the reference channel. Percentage change was calculated by dividing the normalized intensity value of each sample to that of wild type control lane intensity for E6-AP.t-test and one way ANOVA. The criterion for significance was set at p≤0.05.Statistical analysis was conducted by using Graphpad Prism. Data were analyzed by unpaired Ube3a expression. Specifically, we were interested in establishing that Ube3a levels are significantly elevated in the 7p duplication animals only when the duplicated allele is inherited maternally. In fact, our quantitative IR Western blot results indicate that when a Ube3a loss of function mutation generated by Jiang et al. is maternally inherited, there is a >80% decrease in Ube3a protein in both the cerebellum and hippocampus. Similarly, there is >75% increase in Ube3a protein in the maternal 7p duplication animals but not the paternal duplication animals in the cerebellum and hippocampus . In maternal Ube3a deficient mice, 5HT levels were significantly increased in the frontal cortex and striatum compared to wild type littermates. In paternal duplication animals, 5HT levels decreased in both of these regions significantly compared to their wild type littermates, while in maternal duplication animals there were no significant changes in 5HT levels  in both T levels Figure 2Table S1). Thus, regional DA levels appear to be sensitive to changes in Ube3a expression but are also affected by the expression of other genes in the duplicated region.Somewhat surprising was our finding that DA levels increased significantly in both deletion and duplication animals in both the striatum and midbrain Figure 3Ube3a deficient animals, DOPAC levels increased significantly in the striatum and midbrain as compared to controls. In maternal duplication animals, DOPAC levels increased in striatum and in paternal duplication animals DOPAC levels increased in cerebellum, midbrain and frontal cortex (Table S1). Thus, there is some discrepancy about how changes in Ube3a affect DOPAC levels and these results may be an artifact of the experimental procedures or may reflect the rapid metabolism of DA in these regions due to supra-physiologic - DA levels .Epinephrine increased significantly in the midbrain of maternal deletion animals, but in maternal duplication animals epinephrine showed an increase in the striatum and frontal cortex, not midbrain. Paternal duplication animals showed a significant increase in epinephrine in the cerebellum and cortex. Thus, while Ube3a can regulate DA in the midbrain, duplication of the region results in a significant increase in the frontal cortex. Norepinephrine changed significantly in maternal duplication animals within the striatal, hippocampal and cerebellar regions Figure 44). We found that increasing or decreasing Dube3a levels in the fly brain resulted in increased or decreased BH4 levels and DA levels, respectively 4 levels in the cerebellum, frontal cortex, striatum, hippocampus and midbrain of Ube3a deficient and duplication animals we found that BH4 levels did not change significantly in any region tested across all genotypes (Table S1). We did, however, notice a trend in Ube3a deficient animals suggesting that BH4 levels may decrease slightly when Ube3a levels decrease, but these changes were not consistent with the detection of significant increases in monoamines levels in Ube3a deficient animals  questions remain about how changes in Ube3a levels or other genes in the duplicated/deleted region are involved in neuronal function and behavior. For example, Ube3a deficient mice have learning and memory defects and motor abnormalities Ube3a maternal deletion mouse Although mouse models have been generated for both loss of Ube3a mice showed a significant increase in the amount of 5HT in the striatum and cortex when compared to wild type littermates and that paternal duplications of the Ube3a gene region, which do not cause increased Ube3a protein levels in the brain . The involvement of the serotonin system in autism has been well studied and reduced serotonin transporter (SERT) binding capacity in the frontal cortex has been found in autistic children We found that maternal deficient he brain Figure 11A receptor knockout mice have shown that blood 5HT levels were normal at birth, but after two weeks there was a reduction of blood 5HT levels in these animals, which eventually returned to normal levels in 5HT1A knockout adults 1A 5HT2C and 5HT7SNORD-115 gene, called MBII-52 in mice, a small nucleolar RNA which regulates the 5HT2C receptor and is expressed at two-fold higher levels in paternal duplication animals MBII-52 duplication on the 5HT2C receptor does not appear to be Ube3a dependent and warrants further investigation. The 5HT transporter (SERT), which is essential for the uptake of biogenic amine into blood platelets, can influence 5HT levels through increased uptake of 5HT or higher than normal binding levels SLC6A4) can cause an ASD phenotype Elevated levels of 5HT in the blood are often a hallmark of autism 4 through the transcriptional co-activation of GTP cyclohydrolase I, a rate limiting enzyme for monoamine biosynthesis 4 levels in any of the genotypes. In addition, gene expression studies in these brain regions did not indicate significant changes in GTP cyclohydrolase I transcript levels in any of the genotypes tested (data not shown). However, slightly decreased levels of BH4 were detected in striatum, hippocampus, midbrain and frontal cortex in Ube3a deficient mice (Table S1). Since elevated monoamine levels were found in several regions of the brain in all genotypes tested, it could be possible that BH4 levels were negatively regulated by the downstream increase in monoamine levels, thus normal BH4 levels were detected.5HT may also be a key player in synaptic development and maturation. Altered 5HT signaling is responsible for many neurodevelopmental disorders including depression, anxiety, obsessive-compulsive disorder, schizophrenia and sudden infant death syndrome. The prevailing hypothesis for the role of 5HT neurons in mental health disorders is that the genetic determinants and environmental factors influencing them can produce abnormal levels of 5HT, which in turn effect the small population of 5HT neurons disrupting the normal development of the synapses UBE3A in humans results in some AS associated phenotypes due to elevated 5HT levels since DA depletion therapy with reserpine was able to ameliorate uncontrolled myoclonus in at least one AS patient Two additional characteristic features of Angelman syndrome in humans are social seeking behavior and hyperactivity. However, these characteristics are not found in the Angelman syndrome mouse models. In fact, these animals have reduced social behavior and reduced exploratory behavior Ube3a is the causative gene in Angelman syndrome and may be contributing to 15q duplication autism, many of the features observed in the Ube3a deficient AS mouse model are not the opposite of what is observed in the Ube3a duplication autism mouse models. In other words, many of the phenotypes attributed to decreased Ube3a levels are not opposite when Ube3a levels are increased. Glutamatergic synaptic defects observed in a recent mouse model for autism due to increased Ube3a alone do not entirely reflect the inverse effects of lower levels observed in Ube3a deficient animals Ube3a deletion and duplication animals in the visual cortex and somatosensory structures et al. attributed the effects of reduced glutamatergic synaptic transmission, evolved AMPA/NMDA current ratio and reduced mEPSC amplitude in hippocampal CA1 pyramidal neurons to the degradation of ARC (activity-related cytoskeleton-associated protein), a putative Ube3a ubiquitination target known to regulate AMPA receptor trafficking et al. confirmed that increasing Ube3a levels reduced ARC protein levels but did not reverse the electrophysiological effects observed in Ube3a deficient animals Although Ube3a paternal duplication animals during developmental stages In our studies, DA levels were significantly elevated in both deletion and duplication animals in the striatum and midbrain. In the cortex, DA levels increased in both maternal deletion and paternal duplication animals. Increased DA levels have been found in Ube3a mice that have reduced Ube3a levels in neurons but there was no significant decrease in 5HT levels in Ube3a maternal duplication animals when Ube3a levels increased. However, the behavioral phenotypes seen in these two different animal models are quite similar indicating that a different mechanism may be involved in each, independent of or in addition to Ube3a regulation of 5HT levels. Increased DA levels can also influence various developmental processes in early brain developmental stages, so the changes in DA found in both animal models could have contributed to the phenotypes observed. Our study suggests that Ube3a levels can influence 5HT levels indirectly in the brain yet a role for Ube3a in monoamine synthesis in mammals remains unclear. Since Ube3a regulates a set of primarily unknown substrates it is possible that altered signaling, feedback regulation or changes in 5HT receptor levels or function could explain the changes in monoamine levels we observed. The changes in monoamine levels observed here might result from a number of defects where Ube3a is only partly responsible or where Ube3a levels must maintain a critical level during a particular developmental stage.In summary, this study demonstrates that 5HT levels increase in maternal deficient Table S1Monoamine and BH4 levels in different tissue. 5HT-5-hydroxytryptamine (serotonin), DA -dopamine, DOPAC-3,4-dihydroxyphenylacetic acid, E-epinephrine, HIAA-5-hydroxyindoleacetic acid, HVA -homovanillic acid, NE-norepinephrine, BH4-tetrahydrobiopterin. Values are means (n = 6).(PDF)Click here for additional data file.