Comparative Genomics of Marine Bacteria from a Historically Defined Plastic Biodegradation Consortium with the Capacity to Biodegrade Polyhydroxyalkanoates

Biodegradable and compostable plastics are getting more attention as the environmental impacts of fossil-fuel-based plastics are revealed. Microbes can consume these plastics and biodegrade them within weeks to months under the proper conditions. The biobased polyhydroxyalkanoate (PHA) polymer family is an attractive alternative due to its physicochemical properties and biodegradability in soil, aquatic, and composting environments. Standard test methods are available for biodegradation that employ either natural inocula or defined communities, the latter being preferred for standardization and comparability. The original marine biodegradation standard test method ASTM D6691 employed such a defined consortium for testing PHA biodegradation. However, the taxonomic composition and metabolic potential of this consortium have never been confirmed using DNA sequencing technologies. To this end, we revived available members of this consortium and determined their phylogenetic placement, genomic sequence content, and metabolic potential. The revived members belonged to the Bacillaceae, Rhodobacteraceae, and Vibrionaceae families. Using a comparative genomics approach, we found all the necessary enzymes for both PHA production and utilization in most of the members. In a clearing-zone assay, three isolates also showed extracellular depolymerase activity. However, we did not find classical PHA depolymerases, but identified two potentially new extracellular depolymerases that resemble triacylglycerol lipases

The Angiotensin-melatonin axis

Accumulating evidence indicates that various biological and neuroendocrine circadian rhythms may be disrupted in cardiovascular and metabolic disorders. These circadian alterations may contribute to the progression of disease. Our studies direct to an important role of angiotensin II and melatonin in the modulation of circadian rhythms. The brain renin-angiotensin system (RAS) may modulate melatonin synthesis, a hormone with well-established roles in regulating circadian rhythms. Angiotensin production in the central nervous system may not only influence hypertension but also appears to affect the circadian rhythm of blood pressure. Drugs acting on RAS have been proven effective in the treatment of cardiovascular and metabolic disorders including hypertension and diabetes mellitus (DM). On the other hand, since melatonin is capable of ameliorating metabolic abnormalities in DM and insulin resistance, the beneficial effects of RAS blockade could be improved through combined RAS blocker and melatonin therapy. Contemporary research is evidencing the existence of specific clock genes forming central and peripheral clocks governing circadian rhythms. Further research on the interaction between these two neurohormones and the clock genes governing circadian clocks may progress our understanding on the pathophysiology of disease with possible impact on chronotherapeutic strategies

Prolactin-signal transduction in neonatal rat pancreatic islets and interaction with the insulin-signaling pathway

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCNPQ – CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICODuring pregnancy, pancreatic islets undergo structural and functional changes in response to an increased demand for insulin. Different hormones, especially placental lactogens, mediate these adaptive changes. Prolactin (PRL) mainly exerts its biological effects by activation of the JAK2/STAT5 pathway. PRL also stimulates some biological effects via activation of IRS-1, IRS-2, PI 3-kinase, and MAPK in different cell lines. Since IRS-2 is important for the maintenance of pancreatic islet cell mass, we investigated whether PRL affects insulin-signaling pathways in neonatal rat islets. PRL significantly potentiated glucose-induced insulin secretion in islets cultured for 7 days. This effect was blocked by the specific PI 3-kinase inhibitor wortmannin. To determine possible effects of PRL on insulin-signaling pathways, fresh islets were incubated with or without the hormone for 5 or 15 min. Immunoprecipitation and immunoblotting with specific antibodies showed that PRL induced a dose-dependent IRS-1 and IRS-2 phosphorylation compared to control islets. PRL-induced increase in IRS-1/-2 phosphorylation was accompanied by an increase in the association with and activation of PI 3-kinase. PRL-induced IRS-2 phosphorylation and its association with PI 3-kinase did not add to the effect of insulin. PRL also induced JAK2, SHC, ERK1 and ERK2 phosphorylation in neonatal islets, demonstrating that PRL can activate MAPK. These data indicate that PRL can stimulate the IRSs/PI 3-kinase and SHC/ERK pathways in islets from neonatal rats355282289FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCNPQ – CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCNPQ – CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOsem informaçãosem informaçãosem informaçã

Facet Formation in the Negative Quenched Kardar-Parisi-Zhang Equation

The quenched Kardar-Parisi-Zhang (QKPZ) equation with negative non-linear term shows a first order pinning-depinning (PD) transition as the driving force $F$ is varied. We study the substrate-tilt dependence of the dynamic transition properties in 1+1 dimensions. At the PD transition, the pinned surfaces form a facet with a characteristic slope $s_c$ as long as the substrate-tilt $m$ is less than $s_c$. When $m<s_c$, the transition is discontinuous and the critical value of the driving force $F_c(m)$ is independent of $m$, while the transition is continuous and $F_c(m)$ increases with $m$ when $m>s_c$. We explain these features from a pinning mechanism involving a localized pinning center and the self-organized facet formation.Comment: 4 pages, source TeX file and 7 PS figures are tarred and compressed via uufile

Highly clustered scale-free networks

We propose a model for growing networks based on a finite memory of the nodes. The model shows stylized features of real-world networks: power law distribution of degree, linear preferential attachment of new links and a negative correlation between the age of a node and its link attachment rate. Notably, the degree distribution is conserved even though only the most recently grown part of the network is considered. This feature is relevant because real-world networks truncated in the same way exhibit a power-law distribution in the degree. As the network grows, the clustering reaches an asymptotic value larger than for regular lattices of the same average connectivity. These high-clustering scale-free networks indicate that memory effects could be crucial for a correct description of the dynamics of growing networks.Comment: 6 pages, 4 figure

Large-scale structural organization of social networks

The characterization of large-scale structural organization of social networks is an important interdisciplinary problem. We show, by using scaling analysis and numerical computation, that the following factors are relevant for models of social networks: the correlation between friendship ties among people and the position of their social groups, as well as the correlation between the positions of different social groups to which a person belongs.Comment: 5 pages, 3 figures, Revte

A Geometric Fractal Growth Model for Scale Free Networks

We introduce a deterministic model for scale-free networks, whose degree distribution follows a power-law with the exponent $\gamma$. At each time step, each vertex generates its offsprings, whose number is proportional to the degree of that vertex with proportionality constant m-1 (m>1). We consider the two cases: first, each offspring is connected to its parent vertex only, forming a tree structure, and secondly, it is connected to both its parent and grandparent vertices, forming a loop structure. We find that both models exhibit power-law behaviors in their degree distributions with the exponent $\gamma=1+\ln (2m-1)/\ln m$. Thus, by tuning m, the degree exponent can be adjusted in the range, $2 <\gamma < 3$. We also solve analytically a mean shortest-path distance d between two vertices for the tree structure, showing the small-world behavior, that is, $d\sim \ln N/\ln {\bar k}$, where N is system size, and $\bar k$ is the mean degree. Finally, we consider the case that the number of offsprings is the same for all vertices, and find that the degree distribution exhibits an exponential-decay behavior

Generic scale of the "scale-free" growing networks

We show that the connectivity distributions $P(k,t)$ of scale-free growing networks ($t$ is the network size) have the generic scale -- the cut-off at $k_{cut} \sim t^\beta$. The scaling exponent $\beta$ is related to the exponent $\gamma$ of the connectivity distribution, $\beta=1/(\gamma-1)$. We propose the simplest model of scale-free growing networks and obtain the exact form of its connectivity distribution for any size of the network. We demonstrate that the trace of the initial conditions -- a hump at $k_h \sim k_{cut} \sim t^\beta$ -- may be found for any network size. We also show that there exists a natural boundary for the observation of the scale-free networks and explain why so few scale-free networks are observed in Nature.Comment: 4 pages revtex, 3 figure