Mutations in fam20b and xylt1 Reveal That Cartilage Matrix Controls Timing of Endochondral Ossification by Inhibiting Chondrocyte Maturation

Differentiating cells interact with their extracellular environment over time. Chondrocytes embed themselves in a proteoglycan (PG)-rich matrix, then undergo a developmental transition, termed “maturation,” when they express ihh to induce bone in the overlying tissue, the perichondrium. Here, we ask whether PGs regulate interactions between chondrocytes and perichondrium, using zebrafish mutants to reveal that cartilage PGs inhibit chondrocyte maturation, which ultimately dictates the timing of perichondral bone development. In a mutagenesis screen, we isolated a class of mutants with decreased cartilage matrix and increased perichondral bone. Positional cloning identified lesions in two genes, fam20b and xylosyltransferase1 (xylt1), both of which encode PG synthesis enzymes. Mutants failed to produce wild-type levels of chondroitin sulfate PGs, which are normally abundant in cartilage matrix, and initiated perichondral bone formation earlier than their wild-type siblings. Primary chondrocyte defects might induce the bone phenotype secondarily, because mutant chondrocytes precociously initiated maturation, showing increased and early expression of such markers as runx2b, collagen type 10a1, and ihh co-orthologs, and ihha mutation suppressed early perichondral bone in PG mutants. Ultrastructural analyses demonstrated aberrant matrix organization and also early cellular features of chondrocyte hypertrophy in mutants. Refining previous in vitro reports, which demonstrated that fam20b and xylt1 were involved in PG synthesis, our in vivo analyses reveal that these genes function in cartilage matrix production and ultimately regulate the timing of skeletal development

A mechanistic model of infection: why duration and intensity of contacts should be included in models of disease spread

<p>Abstract</p> <p>Background</p> <p>Mathematical models and simulations of disease spread often assume a constant per-contact transmission probability. This assumption ignores the heterogeneity in transmission probabilities, e.g. due to the varying intensity and duration of potentially contagious contacts. Ignoring such heterogeneities might lead to erroneous conclusions from simulation results. In this paper, we show how a mechanistic model of disease transmission differs from this commonly used assumption of a constant per-contact transmission probability.</p> <p>Methods</p> <p>We present an exposure-based, mechanistic model of disease transmission that reflects heterogeneities in contact duration and intensity. Based on empirical contact data, we calculate the expected number of secondary cases induced by an infector (i) for the mechanistic model and (ii) under the classical assumption of a constant per-contact transmission probability. The results of both approaches are compared for different basic reproduction numbers <it>R</it>₀.</p> <p>Results</p> <p>The outcomes of the mechanistic model differ significantly from those of the assumption of a constant per-contact transmission probability. In particular, cases with many different contacts have much lower expected numbers of secondary cases when using the mechanistic model instead of the common assumption. This is due to the fact that the proportion of long, intensive contacts decreases in the contact dataset with an increasing total number of contacts.</p> <p>Conclusion</p> <p>The importance of highly connected individuals, so-called super-spreaders, for disease spread seems to be overestimated when a constant per-contact transmission probability is assumed. This holds particularly for diseases with low basic reproduction numbers. Simulations of disease spread should weight contacts by duration and intensity.</p

Infectious Disease Modeling of Social Contagion in Networks

Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for ‘automatic’ (or ‘spontaneous’) non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2 per year and increases by 0.5 percentage points for each obese social contact. The rate of recovering from obesity is 4 per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviors, health states, ideas or diseases with reservoirs.National Institutes of Health (U.S.) (grant R01GM078986)National Science Foundation (U.S.)Bill & Melinda Gates FoundationTempleton FoundationNational Institute on Aging (grant P01 AG031093)Framingham Heart Study (contract number N01-HC-25195

Linkage between fitness of yeast cells and adenylate kinase catalysis

Enzymes have evolved with highly specific values of their catalytic parameters kcat and KM. This poses fundamental biological questions about the selection pressures responsible for evolutionary tuning of these parameters. Here we are address these questions for the enzyme adenylate kinase (Adk) in eukaryotic yeast cells. A plasmid shuffling system was developed to allow quantification of relative fitness (calculated from growth rates) of yeast in response to perturbations of Adk activity introduced through mutations. Biophysical characterization verified that all variants studied were properly folded and that the mutations did not cause any substantial differences to thermal stability. We found that cytosolic Adk is essential for yeast viability in our strain background and that viability could not be restored with a catalytically dead, although properly folded Adk variant. There exist a massive overcapacity of Adk catalytic activity and only 12% of the wild type kcat is required for optimal growth at the stress condition 20°C. In summary, the approach developed here has provided new insights into the evolutionary tuning of kcat for Adk in a eukaryotic organism. The developed methodology may also become useful for uncovering new aspects of active site dynamics and also in enzyme design since a large library of enzyme variants can be screened rapidly by identifying viable colonies

Detecting Clusters of Mutations

Positive selection for protein function can lead to multiple mutations within a small stretch of DNA, i.e., to a cluster of mutations. Recently, Wagner proposed a method to detect such mutation clusters. His method, however, did not take into account that residues with high solvent accessibility are inherently more variable than residues with low solvent accessibility. Here, we propose a new algorithm to detect clustered evolution. Our algorithm controls for different substitution probabilities at buried and exposed sites in the tertiary protein structure, and uses random permutations to calculate accurate P values for inferred clusters. We apply the algorithm to genomes of bacteria, fly, and mammals, and find several clusters of mutations in functionally important regions of proteins. Surprisingly, clustered evolution is a relatively rare phenomenon. Only between 2% and 10% of the genes we analyze contain a statistically significant mutation cluster. We also find that not controlling for solvent accessibility leads to an excess of clusters in terminal and solvent-exposed regions of proteins. Our algorithm provides a novel method to identify functionally relevant divergence between groups of species. Moreover, it could also be useful to detect artifacts in automatically assembled genomes

Early effects of parathyroid hormone on bisphosphonate/steroid-associated compromised osseous wound healing

Summary: Administration of intermittent parathyroid hormone (PTH) promoted healing of tibial osseous defects and tooth extraction wounds and prevented the development of necrotic lesions in rats on a combined bisphosphonate and steroid regimen. Introduction: Osteonecrosis of the jaw (ONJ) has emerged in association with antiresorptive therapies. The pathophysiology of ONJ is unknown and no established cure currently exists. Our objective was to determine the effect of intermittent PTH administration on early osseous healing in the jaw and long bones of rats receiving bisphosphonate and steroid treatment. Methods: Ovariectomized rats received the combination therapy of alendronate and dexamethasone (ALN/DEX) for 12 weeks. Osseous wounds were created in the jaw and tibia. PTH was administered intermittently and healing at 2 weeks post-op was compared between the jaw and tibia by microcomputed tomography and histomorphometric analyses. Results: ALN/DEX treatment was associated with necrotic open wounds in the jaw but had no negative effects on healing and promoted bone fill in tibial defects. PTH therapy prevented the development of necrotic lesions in the jaw and promoted healing of the tibial defects. PTH therapy was associated with the promotion of osteocyte survival in osseous wounds both in the jaw and tibia. Conclusions: Wound healing was impaired in the jaw in rats on a combined bisphosphonate and steroid regimen, and PTH therapy rescued necrotic lesions. These findings suggest that PTH therapy could be utilized to prevent ONJ from occurring in patients on combination antiresorptive and steroid therapy