Distinctive functions of membrane type 1 matrix-metalloprotease (MT1-MMP or MMP-14) in lung and submandibular gland development are independent of its role in pro-MMP-2 activation

Membrane type 1-matrix metalloprotease (MT1-MMP or MMP-14) is a major activator of pro-MMP-2 and is essential for skeletal development. We show here that it is required for branching morphogenesis of the submandibular gland but not the lung. Instead, in the lung, it is essential for postnatal development of alveolar septae. Lung development in Mmp14-/- mice is arrested at the prealveolar stage with compensatory hyperinflation of immature saccules. Mmp2-/- mice lacked comparable defects in the lung and submandibular gland, suggesting that MT1-MMP acts via mechanisms independent of pro-MMP-2 activation. Since the developmental defects in the lung are first manifest around the time of initial vascularization (E16.5), we investigated the behavior of pulmonary endothelial cells from Mmp14+/+ and Mmp14-/- mice. Endothelial cells from lungs of 1-week-old Mmp14-/- mice show reduced migration and formation of three-dimensional structures on Matrigel. Since pulmonary septal development requires capillary growth, the underlying mechanism of pulmonary hypoplasia in Mmp14-/- mice may be defective angiogenesis, supporting a model in which angiogenesis is a critical rate-limiting step for acquisition of pulmonary parenchymal mass.     

Identification of Multiple Phosphorylation Sites on Maize Endosperm Starch Branching Enzyme IIb,a Key Enzyme in Amylopectin Biosynthesis

Starch branching enzyme IIb (SBEIIb) plays a crucial role in amylopectin biosynthesis in maize endosperm by defining the structural and functional properties of storage starch and is regulated by protein phosphorylation. Native and recombinant maize SBEIIb were used as substrates for amyloplast protein kinases to identify phosphorylation sites on the protein. A multidisciplinary approach involving bioinformatics, site-directed mutagenesis, and mass spectrometry identified three phosphorylation sites at Ser residues: Ser⁶⁴⁹, Ser²⁸⁶, and Ser²⁹⁷. Two Ca²⁺-dependent protein kinase activities were partially purified from amyloplasts, termed K1, responsible for Ser⁶⁴⁹ and Ser²⁸⁶ phosphorylation, and K2, responsible for Ser⁶⁴⁹ and Ser²⁹⁷ phosphorylation. The Ser²⁸⁶ and Ser²⁹⁷ phosphorylation sites are conserved in all plant branching enzymes and are located at opposite openings of the 8-stranded parallel β-barrel of the active site, which is involved with substrate binding and catalysis. Molecular dynamics simulation analysis indicates that phospho-Ser²⁹⁷ forms a stable salt bridge with Arg⁶⁶⁵, part of a conserved Cys-containing domain in plant branching enzymes. Ser⁶⁴⁹ conservation appears confined to the enzyme in cereals and is not universal, and is presumably associated with functions specific to seed storage. The implications of SBEIIb phosphorylation are considered in terms of the role of the enzyme and the importance of starch biosynthesis for yield and biotechnological application.     

非均匀人群SIR模型的稳态分布

文章利用测度论的方法研究非均匀人群中疾病传播的SIR模型,建立了动态模型中感染人群的演化方程,在此基础上我们得到了非均匀SIR模型的稳态分布.     

Thermus thermophilus glycoside hydrolase family 57 branching enzyme: crystal structure, mechanism of action, and products formed

Branching enzyme (EC 2.4.1.18; glycogen branching enzyme; GBE) catalyzes the formation of α1,6-branching points in glycogen. Until recently it was believed that all GBEs belong to glycoside hydrolase family 13 (GH13). Here we describe the cloning and expression of the Thermus thermophilus family GH57-type GBE and report its biochemical properties and crystal structure at 1.35-Å resolution. The enzyme has a central (β/α)₇-fold catalytic domain A with an inserted domain B between β2 and α5 and an α-helix-rich C-terminal domain, which is shown to be essential for substrate binding and catalysis. A maltotriose was modeled in the active site of the enzyme which suggests that there is insufficient space for simultaneously binding of donor and acceptor substrates, and that the donor substrate must be cleaved before acceptor substrate can bind. The biochemical assessment showed that the GH57 GBE possesses about 4% hydrolytic activity with amylose and in vitro forms a glucan product with a novel fine structure, demonstrating that the GH57 GBE is clearly different from the GH13 GBEs characterized to date.     

Stochastic continuous time neurite branching models with tree and segment dependent rates

In this paper we introduce a continuous time stochastic neurite branching model closely related to the discrete time stochastic BES-model. The discrete time BES-model is underlying current attempts to simulate cortical development, but is difficult to analyze. The new continuous time formulation facilitates analytical treatment thus allowing us to examine the structure of the model more closely. We derive explicit expressions for the time dependent probabilities p(γ,t) for finding a tree γ at time t, valid for arbitrary continuous time branching models with tree and segment dependent branching rates. We show, for the specific case of the continuous time BES-model, that as expected from our model formulation, the sums needed to evaluate expectation values of functions of the terminal segment number μ(f(n),t) do not depend on the distribution of the total branching probability over the terminal segments. In addition, we derive a system of differential equations for the probabilities p(n,t) of finding n terminal segments at time t. For the continuous BES-model, this system of differential equations gives direct numerical access to functions only depending on the number of terminal segments, and we use this to evaluate the development of the mean and standard deviation of the number of terminal segments at a time t. For comparison we discuss two cases where mean and variance of the number of terminal segments are exactly solvable. Then we discuss the numerical evaluation of the S-dependence of the solutions for the continuous time BES-model. The numerical results show clearly that higher S values, i.e. values such that more proximal terminal segments have higher branching rates than more distal terminal segments, lead to more symmetrical trees as measured by three tree symmetry indicators.     

Stochastic models for virus and immune system dynamics

New stochastic models are developed for the dynamics of a viral infection and an immune response during the early stages of infection. The stochastic models are derived based on the dynamics of deterministic models. The simplest deterministic model is a well-known system of ordinary differential equations which consists of three populations: uninfected cells, actively infected cells, and virus particles. This basic model is extended to include some factors of the immune response related to Human Immunodeficiency Virus-1 (HIV-1) infection. For the deterministic models, the basic reproduction number, R₀, is calculated and it is shown that if R₀<1, the disease-free equilibrium is locally asymptotically stable and is globally asymptotically stable in some special cases. The new stochastic models are systems of stochastic differential equations (SDEs) and continuous-time Markov chain (CTMC) models that account for the variability in cellular reproduction and death, the infection process, the immune system activation, and viral reproduction. Two viral release strategies are considered: budding and bursting. The CTMC model is used to estimate the probability of virus extinction during the early stages of infection. Numerical simulations are carried out using parameter values applicable to HIV-1 dynamics. The stochastic models provide new insights, distinct from the basic deterministic models. For the case R₀>1, the deterministic models predict the viral infection persists in the host. But for the stochastic models, there is a positive probability of viral extinction. It is shown that the probability of a successful invasion depends on the initial viral dose, whether the immune system is activated, and whether the release strategy is bursting or budding.     

Application of the Character Compatibility Approach to Generalized Molecular Sequence Data: Branching Order of the Proteobacterial Subdivisions

The character compatibility approach, which removes all homoplasic characters and involves finding the largest clique of compatible characters in a dataset, in principle, provides a powerful means for obtaining correct topology in difficult to resolve cases. However, the usefulness of this approach to generalized molecular sequence data for phylogeny determination has not been studied in the past. We have used this approach to determine the topology of 23 proteobacterial species (6 each of α-, β- and γ-, 3 δ-, and 2 ε-proteobacteria) using sequence data for 10 conserved proteins (Hsp60, Hsp70, EF-Tu, EF-G, alanyl-tRNA synthetase, RecA, GyrA, GyrB, RpoB and RpoC). All sites in the sequence alignments of these proteins where only two amino acids were found, with each amino acid present in at least two species, were selected. Mutual compatibility determination on these binary state sites was carried out by two means. In one case, all of these sites were combined into a large dataset (Set A; 957 characters) prior to compatibility analysis. In the second case, compatibility analysis was carried out on characters from individual proteins and all compatible sites were combined into a large dataset (Set B; 398 characters) for further studies. Upon compatibility analyses, the largest cliques that were obtained from Sets A and B consisted of 337 and 323 compatible characters, respectively. In these cliques, all proteobacterial subgroups were clearly distinguished and branching orders of most of the species were also resolved. The ε-proteobacteria exhibited the earliest branching, whereas the β- and γ-subgroups were found to have emerged last. The relative placement of the α- and δ-subgroups, however, was not resolved. The topology of these species was also determined based on 16S rRNA sequences and a concatenated dataset of sequences for all 10 proteins by means of neighbor-joining, maximum likelihood, and maximum parsimony methods. In the protein trees, all proteobacterial groups were reliably resolved and they branched in the following order: (ε(δ(α(β,γ)))). However, in the rRNA trees, the γ- and β-subgroups exhibited polyphyletic branching and many internal nodes were not resolved. These results indicate that the character compatibility analysis using generalized molecular sequence data provides a powerful means for evolutionary studies. Based on molecular sequences, it should be possible to obtain very large datasets of compatible characters that should prove very helpful in clarifying difficult to resolve phylogenetic relationships. [Reviewing Editor: Dr. Yves Van de Peer]     

On a periodic-like behavior of a delayed density-dependent branching process

Most of natural populations seem to be regulated in their sizes in complex ways. Particularly, the sizes of some populations change in time or generation roughly periodically. There are many theoretical studies on such population dynamics. This paper develops stochastic population models for a periodic-like population dynamics. To see the nature of such mechanism, we consider simple models of a delayed density-dependent branching process, and present by numerical simulations how such a branching process shows periodic population changes. The effects of randomly changing stationary environments on the population dynamics are also considered.     

Reservoir interactions and disease emergence

Animal populations act as reservoirs for emerging diseases. In order for transmission to be self-sustaining, a pathogen must have a basic reproduction number R0>1. Following a founding transmission event from an animal reservoir to humans, a pathogen has not yet adapted to its new environment and is likely to have an R0<1. However, subsequent evolution may rescue the pathogen from extinction in its new host. Recent applications of branching process theory investigate how the emergence of a novel pathogen is influenced by the number and rates of intermediate evolutionary steps. In addition, repeated contacts between human and reservoir populations may promote pathogen emergence. This article extends a stepping-stone model of pathogen evolution to include reservoir interactions. We demonstrate that the probability of a founding event culminating in an emerged pathogen can be significantly influenced by ongoing reservoir interactions. While infrequent reservoir interactions do not change the probability of disease emergence, moderately frequent interactions can promote emergence by facilitating adaptation to humans. Frequent reservoir interactions promote emergence even with minimal adaptation to humans. Thus, these results warn against perpetuated interaction between humans and animal reservoirs, as occurs when there are ecological or environmental changes that bring humans into more frequent contact with animal reservoirs.