Algorithms for mapping of mRNA targets for microRNA

MicroRNAs (miRNAs) are involved in human health and disease as endogenous suppressors of the translation of coding genes. At this early point of time in miRNA biology, it is important to identify specific cognate mRNA targets for miRNA. Investigation of the significance of miRNAs in disease processes relies on algorithms that hypothetically link specific miRNAs to their putative target genes. The development of such algorithms represents a hot area of research in biomedical informatics. Lack of biological data linking specific miRNAs to their respective mRNA targets represents the most serious limitation at this time. This article presents a concise review addressing the most popular concepts underlying state-of-the-art algorithms and principles aimed at target mapping for specific miRNAs. Strategies for improvement of the current bioinformatics tools and effective approaches for biological validation are discussed.     

A simple shape characteristic of protein-protein recognition

MOTIVATION: Observation of co-crystallized protein-protein complexes and low-resolution protein-protein docking studies suggest the existence of a binding-related anisotropic shape characteristic of protein-protein complexes. RESULTS: Our study systematically assessed the global shape of proteins in a non-redundant database of co-crystallized protein-protein complexes by measuring the distance of the surface residues to the protein's center of mass. The results show that on average the binding site residues are closer to the center of mass than the non-binding surface residues. Thus, the study directly detects an important and simple binding-related characteristic of protein shapes. The results provide an insight into one of the fundamental properties of protein structure and association.     

<Emphasis Type="Italic">Helicobacter pylori</Emphasis> genome variability in a framework of familial transmission

Background  

Helicobacter pylori infection is exceptionally prevalent and is considered to be acquired primarily early in life through person-to-person transmission within the family. H. pylori is a genetically diverse bacterial species, which may facilitate adaptation to new hosts and persistence for decades. The present study aimed to explore the genetic diversity of clonal isolates from a mother and her three children in order to shed light on H. pylori transmission and host adaptation.     

CPEB Regulation of TAK1 Synthesis Mediates Cytokine Production and the Inflammatory Immune Response

The cytoplasmic-element-binding (CPEB) protein is a sequence-specific RNA-binding protein that regulates cytoplasmic polyadenylation-induced translation. In mouse embryo fibroblasts (MEFs) lacking CPEB, many mRNAs encoding proteins involved in inflammation are misregulated. Correlated with this aberrant translation in MEFs, a macrophage cell line depleted of CPEB and treated with lipopolysaccharide (LPS) to stimulate the inflammatory immune response expresses high levels of interleukin-6 (IL-6), which is due to prolonged nuclear retention of NF-κB. Two proteins involved in NF-κB nuclear localization and IL-6 expression, IκBα and transforming growth factor beta-activated kinase 1 (TAK1), are present at excessively low and high steady-state levels, respectively, in LPS-treated CPEB-depleted macrophages. However, only TAK1 has an altered synthesis rate that is CPEB dependent and CPEB/TAK1 double depletion alleviates high IL-6 production. Peritoneal macrophages isolated from CPEB knockout (KO) mice treated with LPS in vitro also have prolonged NF-κB nuclear retention and produce high IL-6 levels. LPS-injected CPEB KO mice secrete prodigious amounts of IL-6 and other proinflammatory cytokines and exhibit hypersensitivity to endotoxic shock; these effects are mitigated when the animals are also injected with (5Z)-7-oxozeaenol, a potent and specific inhibitor of TAK1. These data show that CPEB control of TAK1 mRNA translation mediates the inflammatory immune response.     

The Geoglobus acetivorans Genome: Fe(III) Reduction,Acetate Utilization,Autotrophic Growth,and Degradation of Aromatic Compounds in a Hyperthermophilic Archaeon

Geoglobus acetivorans is a hyperthermophilic anaerobic euryarchaeon of the order Archaeoglobales isolated from deep-sea hydrothermal vents. A unique physiological feature of the members of the genus Geoglobus is their obligate dependence on Fe(III) reduction, which plays an important role in the geochemistry of hydrothermal systems. The features of this organism and its complete 1,860,815-bp genome sequence are described in this report. Genome analysis revealed pathways enabling oxidation of molecular hydrogen, proteinaceous substrates, fatty acids, aromatic compounds, n-alkanes, and organic acids, including acetate, through anaerobic respiration linked to Fe(III) reduction. Consistent with the inability of G. acetivorans to grow on carbohydrates, the modified Embden-Meyerhof pathway encoded by the genome is incomplete. Autotrophic CO₂ fixation is enabled by the Wood-Ljungdahl pathway. Reduction of insoluble poorly crystalline Fe(III) oxide depends on the transfer of electrons from the quinone pool to multiheme c-type cytochromes exposed on the cell surface. Direct contact of the cells and Fe(III) oxide particles could be facilitated by pilus-like appendages. Genome analysis indicated the presence of metabolic pathways for anaerobic degradation of aromatic compounds and n-alkanes, although an ability of G. acetivorans to grow on these substrates was not observed in laboratory experiments. Overall, our results suggest that Geoglobus species could play an important role in microbial communities of deep-sea hydrothermal vents as lithoautotrophic producers. An additional role as decomposers would close the biogeochemical cycle of carbon through complete mineralization of various organic compounds via Fe(III) respiration.     

Forest transitions in Eastern Europe and their effects on carbon budgets

Forests often rebound from deforestation following industrialization and urbanization, but for many regions our understanding of where and when forest transitions happened, and how they affected carbon budgets remains poor. One such region is Eastern Europe, where political and socio‐economic conditions changed drastically over the last three centuries, but forest trends have not yet been analyzed in detail. We present a new assessment of historical forest change in the European part of the former Soviet Union and the legacies of these changes on contemporary carbon stocks. To reconstruct forest area, we homogenized statistics at the provincial level for ad 1700–2010 to identify forest transition years and forest trends. We contrast our reconstruction with the KK11 and HYDE 3.1 land change scenarios, and use all three datasets to drive the LPJ dynamic global vegetation model to calculate carbon stock dynamics. Our results revealed that forest transitions in Eastern Europe occurred predominantly in the early 20th century, substantially later than in Western Europe. We also found marked geographic variation in forest transitions, with some areas characterized by relatively stable or continuously declining forest area. Our data suggest extensive deforestation in European Russia already prior to ad 1700, and even greater deforestation in the 18th and 19th centuries than in the KK11 and HYDE scenarios. Based on our reconstruction, cumulative carbon emissions from deforestation were greater before 1700 (60 Pg C) than thereafter (29 Pg C). Summed over our entire study area, forest transitions led to a modest uptake in carbon over recent decades, with our dataset showing the smallest effect (<5.5 Pg C) and a more heterogeneous pattern of source and sink regions. This suggests substantial sequestration potential in regrowing forests of the region, a trend that may be amplified through ongoing land abandonment, climate change, and CO₂ fertilization.     

An extract of Artemisia dracunculus L. enhances insulin receptor signaling and modulates gene expression in skeletal muscle in KK-A mice

An ethanolic extract of Artemisia dracunculus L. (PMI 5011) has been observed to decrease glucose and insulin levels in animal models, but the cellular mechanisms by which insulin action is enhanced in vivo are not precisely known. In this study, we evaluated the effects of PMI 5011 to modulate gene expression and cellular signaling through the insulin receptor in skeletal muscle of KK-A^y mice. Eighteen male KK-A^y mice were randomized to a diet (w/w) mixed with PMI 5011 (1%) or diet alone for 8 weeks. Food intake, adiposity, glucose and insulin were assessed over the study, and at study completion, vastus lateralis muscle was obtained to assess insulin signaling parameters and gene expression. Animals randomized to PMI 5011 were shown to have enhanced insulin sensitivity and increased insulin receptor signaling, i.e., IRS-associated PI-3 kinase activity, Akt-1 activity and Akt phosphorylation, in skeletal muscle when compared to control animals (P<.01, P<.01 and P<.001, respectively). Gene expression for insulin signaling proteins, i.e., IRS-1, PI-3 kinase and Glut-4, was not increased, although a relative increase in protein abundance was noted with PMI 5011 treatment. Gene expression for specific ubiquitin proteins and specific 20S proteasome activity, in addition to skeletal muscle phosphatase activity, i.e., PTP1B activity, was significantly decreased in mice randomized to PMI 5011 relative to control. Thus, the data demonstrate that PMI 5011 increases insulin sensitivity and enhances insulin receptor signaling in an animal model of insulin resistance. PMI 5011 may modulate skeletal muscle protein degradation and phosphatase activity as a possible mode of action.     

Mathematical treatment of adiabatic fast passage pulses for the computation of nuclear spin relaxation rates in proteins with conformational exchange

Although originally designed for broadband inversion and decoupling in NMR spectroscopy, recent methodological developments have introduced adiabatic fast passage (AFP) pulses into the field of protein dynamics. AFP pulses employ a frequency sweep, and have not only superior inversion properties with respect to offset effects, but they are also easily implemented into a pulse sequence. As magnetization is dragged from the +z to the -z direction, Larmor precession is impeded since magnetization becomes spin-locked, which is a potentially useful feature for the investigation of microsecond to millisecond dynamics. A major drawback of these pulses as theoretical prediction is concerned, however, results from their time-dependent offset: simulations of spin density matrices under the influence of a time-dependent Hamiltonian with non-commuting elements are costly in terms of computational time, rendering data analysis impracticable. In this paper we suggest several ways to reduce the computational time without compromising accuracy with respect to effects such as cross-correlated relaxation and modulation of the chemical shift.