Connexin43 interacts with βarrestin: a pre-requisite for osteoblast survival induced by parathyroid hormone

Parathyroid hormone (PTH) promotes osteoblast survival through a mechanism that depends on cAMP-mediated signaling downstream of the G protein-coupled receptor PTHR1. We present evidence herein that PTH-induced survival signaling is impaired in cells lacking connexin43 (Cx43). Thus, expression of functional Cx43 dominant negative proteins or Cx43 knock-down abolished the expression of cAMP-target genes and anti-apoptosis induced by PTH in osteoblastic cells. In contrast, cells lacking Cx43 were still responsive to the stable cAMP analog dibutyril-cAMP. PTH survival signaling was rescued by transfecting wild type Cx43 or a truncated dominant negative mutant of βarrestin, a PTHR1-interacting molecule that limits cAMP signaling. On the other hand, Cx43 mutants lacking the cytoplasmic domain (Cx43(Δ245)) or unable to be phosphorylated at serine 368 (Cx43(S368A)), a residue crucial for Cx43 trafficking and function, failed to restore the anti-apoptotic effect of PTH in Cx43-deficient cells. In addition, overexpression of wild type βarrestin abrogated PTH survival signaling in Cx43-expressing cells. Moreover, βarrestin physically associated in vivo to wild type Cx43 and to a lesser extent to Cx43(S368A) ; and this association and the phosphorylation of Cx43 in serine 368 were reduced by PTH. Furthermore, induction of Cx43(S368) phosphorylation or overexpression of wild type Cx43, but not Cx43(Δ245) or Cx43(S368A) , reduced the interaction between βarrestin and the PTHR1. These studies demonstrate that βarrestin is a novel Cx43-interacting protein and suggest that, by sequestering βarrestin, Cx43 facilitates cAMP signaling, thereby exerting a permissive role on osteoblast survival induced by PTH.     

Synthesis and biological evaluation of glycogen synthase kinase 3 (GSK-3) inhibitors: an fast and atom efficient access to 1-aryl-3-benzylureas

The glycogen synthase kinase 3 (GSK-3) is implicated in multiple cellular processes and has been linked to the pathogenesis of Alzheimer's disease (AD). In the course of our research topic we synthesized a library of potent GSK-3 inhibitors. We utilized the urea scaffold present in the potent and highly selective GSK-3 inhibitor AR-A014418 (AstraZeneca). This moiety suits both (a) a convergent approach utilizing readily accessible building blocks and (b) a divergent approach based on a microwave heating assisted Suzuki coupling. We established a chromatography-free purification method to generate products with sufficient purity for the biological assays. The structure-activity relationship of the library provided the rationale for the synthesis of the benzothiazolylurea 66 (IC(50)=140 nM) and the pyridylurea 62 (IC(50)=98 nM), which displayed two to threefold enhanced activity versus the reference compound 18 (AR-A014418: IC(50)=330 nM) in our assays.     

Epistasis increases the rate of conditionally neutral substitution in an adapting population

Kimura observed that the rate of neutral substitution should equal the neutral mutation rate. This classic result is central to our understanding of molecular evolution, and it continues to influence phylogenetics, genomics, and the interpretation of evolution experiments. By demonstrating that neutral mutations substitute at a rate independent of population size and selection at linked sites, Kimura provided an influential justification for the idea of a molecular clock and emphasized the importance of genetic drift in shaping molecular evolution. But when epistasis among sites is common, as numerous empirical studies suggest, do neutral mutations substitute according to Kimura''s expectation? Here we study simulated, asexual populations of RNA molecules, and we observe that conditionally neutral mutations—i.e., mutations that do not alter the fitness of the individual in which they arise, but that may alter the fitness effects of subsequent mutations—substitute much more often than expected while a population is adapting. We quantify these effects using a simple population-genetic model that elucidates how the substitution rate at conditionally neutral sites depends on the population size, mutation rate, strength of selection, and prevalence of epistasis. We discuss the implications of these results for our understanding of the molecular clock, and for the interpretation of molecular variation in laboratory and natural populations.KIMURA''S observation that the rate of substitution at a neutral site should equal the neutral mutation rate is one of the most elegant and widely applied results in population genetics (Kimura 1968; Kimura and Ota 1971; Bromham and Penny 2003; Hughes 2008; Nei et al. 2010). This theory performs well for sites in a genome that can be classified as unconditionally neutral: that is, sites at which the fitness effects of mutations are negligible in any environment, and in combination with any genetic background. But what does neutral theory predict about the fate of a mutation that is known to be neutral only in the genetic background in which it arose? Such mutations may interact epistatically with subsequent mutations at other loci and are thus called conditionally neutral. In light of recent studies supporting a constructive role for such epistatic neutral variation in adaptive evolution (Schuster and Fontana 1999; Depristo et al. 2005; Koelle et al. 2006; Amitai et al. 2007; Cowperthwaite and Meyers 2007; Wagner 2008a; Bloom and Arnold 2009; Draghi et al. 2010), we ask whether Kimura''s foundational result extends to conditionally neutral mutations.To understand the generality of Kimura''s result, it is helpful to consider an informal derivation. Imagine an idealized population of N haploid individuals, one of which will eventually be the ancestor of the future population. If unconditionally neutral mutations occur at rate μ per replication, then on average Nμ mutations will arise in the population each generation. Because these mutations can never affect fitness, they cannot affect the eventual fate of the lineages in which they arise. Therefore, each unconditionally neutral mutation will arise in the eventual common ancestor with probability 1/N; otherwise, it will be lost. The average rate of neutral substitution, k, therefore, equals the rate of (unconditionally) neutral mutation times the fixation probability of each mutant:(1)The reasoning behind Equation 1 is compelling, and many studies have argued that this result holds for sexual and asexual species, for neutral mutations linked to positively or negatively selected sites, and for populations of varying sizes (Kimura and Ota 1971; Birky and Walsh 1988; Gillespie 2000; Bromham and Penny 2003). As a result, the rate of substitution at neutral sites is now viewed as one of the most robust and well-understood features of molecular evolution. Extensions to the neutral theory have mainly focused on the apparent overdispersion of neutral substitutions (Gillespie 1986, 1993; Takahata 1987; Bastolla et al. 1999, 2002, 2003; Cutler 2000; Wilke 2004; Bloom et al. 2007; Raval 2007). With the exception of a few studies that predict small deviations in models with lethal mutations and stabilizing selection (Bastolla et al. 1999; Bloom et al. 2007), most work has confirmed or, more often, tacitly assumed that Equation 1 accurately describes the mean substitution rate. These studies have largely ignored the impact of conditionally neutral mutations: mutations that are neutral on the genetic background in which they arise, but that may alter the fitness effects of subsequent mutations. If neutral mutations have epistatic interactions of this sort, then it is unclear whether Kimura''s equation describes their substitution rate.A diverse array of recent computational and empirical studies has demonstrated the importance of neutral mutations with epistatic effects (reviewed in Wagner 2008a). Evolutionary simulations with RNA folding algorithms (Huynen 1996; Huynen et al. 1996; Fontana and Schuster 1998; Ancel and Fontana 2000; Wagner 2008b) and model gene networks (Bergman and Siegal 2003; Ciliberti et al. 2007) indicate that neutral changes may often be prerequisites for adaptive substitutions and that the interactions between neutral and adaptive changes can lead to complex dynamics of phenotypic evolution; theoretical developments have generalized and expanded these results (van Nimwegen and Crutchfield 2000; Lenski et al. 2006; Wagner 2008a,b; Weissman et al. 2009; Draghi et al. 2010). Additional evidence comes from laboratory evolution experiments with proteins, in which apparently neutral mutations permit future adaptations by changing thermodynamic stability, codon usage, or promiscuous protein–ligand interactions (Depristo et al. 2005; Bloom et al. 2006; Amitai et al. 2007; Cambray and Mazel 2008; Bloom and Arnold 2009). The epistastic effects of nearly neutral mutations can even explain the evolution of consequential innovations, such as adaptive expansion into a new niche (Blount et al. 2008), the sudden escape of a pathogen from population immunity (Koelle et al. 2006; van Nimwegen 2006; Kryazhimskiy et al. 2011) or susceptibility to a drug (Bloom et al. 2010; Kryazhimskiy et al. 2011).If some neutral mutations can facilitate future adaptation through epistatic interactions, selection might drive these neutral mutations to fixation by hitchhiking—that is, by linkage to subsequent beneficial mutations. However, other neutral mutations will impede future adaptive changes, and fixation of these neutral mutations would be disfavored by selection. In each case, the effects of a mutation on an individual''s evolvability—that is, its capacity for adaptation—causes its probability of fixation to be larger or smaller than that of an unconditionally neutral mutation. Naively, one might expect that conditionally neutral mutations would be no more likely to enhance evolvability than to diminish it. Consequently, the effects of evolvability on the fixation of these mutations might average out, and Equation 1 might accurately describe the substitution rate of epistatic neutral mutations. Here we show that this naive expectation is incorrect. Instead, “neutral epistasis” in an asexual, adapting population causes a significant elevation of the substitution rate at conditionally neutral sites, compared to Kimura''s classical expectation for unconditionally neutral sites. We first demonstrate these departures from the conventional substitution rate in simulated populations of replicating RNA molecules, and we confirm that the substitution rate is caused by the epistatic effects of neutral mutations. We then explore a simple population-genetic model that quantifies how epistasis, population size and mutation rate, and selection coefficients jointly determine the substitution rate at conditionally neutral sites in adapting populations. Finally, we discuss the implications of these results for the molecular clock and for the inference of evolutionary processes in natural and laboratory populations of nonrecombining organisms and chromosomes.     

Elucidating substrate and inhibitor binding sites on the surface of GSK-3β and the refinement of a competitive inhibitor

A molecular understanding of substrate recognition of protein kinases provides an important basis for the development of substrate competitive inhibitors. Here, we explored substrate recognition and competitive inhibition of glycogen synthase kinase (GSK)-3β using molecular and computational tools. In previous work, we described Gln89 and Asn95 within GSK-3β as important substrates binding sites. Here, we show that the cavity bordered by loop 89-QDKRFKN-95, located in the vicinity of the GSK-3β catalytic core, is a promiscuous substrate binding subsite. Mutations within this segment highlighted Phe93 as an additional essential contact residue for substrates' recognition. However, unlike Gln89 and Asn95, Phe93 was also important for the binding of our previously described substrate competitive inhibitor, L803 [KEAPPAPPQS(p)P], and its cell-permeable variant L803-mts. The effects of the substitution of charged or polar residues within L803 further suggested that binding to GSK-3β is governed by hydrophobic interactions. Our computational model of GSK-3β bound to L803 was in agreement with the experimental data. It revealed L803 binding with a hydrophobic surface patch and identified interactions between Pro8 (L803) and Phe93 (GSK-3β). Computational modeling of new L803 variants predicted that inhibition would be strengthened by adding contacts with Phe93 or by increasing the hydrophobic content of the peptide. Indeed, the newly designed L803 variants showed improved inhibition. Our study identified different and overlapping elements in GSK-3β substrate and inhibitor recognition and provides a novel example for model-based rational design of substrate competitive inhibitors for GSK-3.     

Human nature, cultural diversity and evolutionary theory

Incorporating culture into an expanded theory of evolution will provide the foundation for a universal account of human diversity. Two requirements must be met. The first is to see learning as an extension of the processes of evolution. The second is to understand that there are specific components of human culture, viz. higher order knowledge structures and social constructions, which give rise to culture as invented knowledge. These components, which are products of psychological processes and mechanisms, make human culture different from the forms of shared knowledge observed in other species. One serious difficulty for such an expanded theory is that social constructions may not add to the fitness of all humans exposed to them. This may be because human culture has existed for only a relatively short time in evolutionary terms. Or it may be that, as some maintain, adaptation is a limited, even a flawed, aspect of evolutionary theory.     

Assessing the determinants of evolutionary rates in the presence of noise

Although protein sequences are known to evolve at vastly different rates, little is known about what determines their rate of evolution. However, a recent study using principal component regression (PCR) has concluded that evolutionary rates in yeast are primarily governed by a single determinant related to translation frequency. Here, we demonstrate that noise in biological data can confound PCRs, leading to spurious conclusions. When equalizing noise levels across 7 predictor variables used in previous studies, we find no evidence that protein evolution is dominated by a single determinant. Our results indicate that a variety of factors--including expression level, gene dispensability, and protein-protein interactions--may independently affect evolutionary rates in yeast. More accurate measurements or more sophisticated statistical techniques will be required to determine which one, if any, of these factors dominates protein evolution.     

THE INEVITABILITY OF UNCONDITIONALLY DELETERIOUS SUBSTITUTIONS DURING ADAPTATION

Studies on the genetics of adaptation from new mutations typically neglect the possibility that a deleterious mutation might fix. Nonetheless, here we show that, in many regimes, the first mutation to fix is most often deleterious, even when fitness is expected to increase in the long term. In particular, we prove that this phenomenon occurs under weak mutation for any house‐of‐cards model with an equilibrium distribution. We find that the same qualitative results hold under Fisher's geometric model. We also provide a simple intuition for the surprising prevalence of unconditionally deleterious substitutions during early adaptation. Importantly, the phenomenon we describe occurs on fitness landscapes without any local maxima and is therefore distinct from “valley crossing.” Our results imply that the common practice of ignoring deleterious substitutions leads to qualitatively incorrect predictions in many regimes. Our results also have implications for the substitution process at equilibrium and for the response to a sudden decrease in population size.     

Structure and age jointly influence rates of protein evolution

What factors determine a protein's rate of evolution are actively debated. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group - including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate. Additionally, younger proteins, despite being less designable, tend to evolve faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution.     

Quantitative assessment of whole-body tumor burden in adult patients with neurofibromatosis

Purpose

Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis are at risk for multiple nerve sheath tumors and premature mortality. Traditional magnetic resonance imaging (MRI) has limited ability to assess disease burden accurately. The aim of this study was to establish an international cohort of patients with quantified whole-body internal tumor burden and to correlate tumor burden with clinical features of disease.

Methods

We determined the number, volume, and distribution of internal nerve sheath tumors in patients using whole-body MRI (WBMRI) and three-dimensional computerized volumetry. We quantified the distribution of tumor volume across body regions and used unsupervised cluster analysis to group patients based on tumor distribution. We correlated the presence and volume of internal tumors with disease-related and demographic factors.

Results

WBMRI identified 1286 tumors in 145/247 patients (59%). Schwannomatosis patients had the highest prevalence of tumors (P = 0.03), but NF1 patients had the highest median tumor volume (P = 0.02). Tumor volume was unevenly distributed across body regions with overrepresentation of the head/neck and pelvis. Risk factors for internal nerve sheath tumors included decreasing numbers of café-au-lait macules in NF1 patients (P = 0.003) and history of skeletal abnormalities in NF2 patients (P = 0.09). Risk factors for higher tumor volume included female gender (P = 0.05) and increasing subcutaneous neurofibromas (P = 0.03) in NF1 patients, absence of cutaneous schwannomas in NF2 patients (P = 0.06), and increasing age in schwannomatosis patients (p = 0.10).

Conclusion

WBMRI provides a comprehensive phenotype of neurofibromatosis patients, identifies distinct anatomic subgroups, and provides the basis for investigating molecular biomarkers that correlate with unique disease manifestations.