Solution structure of the core SMN-Gemin2 complex

In humans, assembly of spliceosomal snRNPs (small nuclear ribonucleoproteins) begins in the cytoplasm where the multi-protein SMN (survival of motor neuron) complex mediates the formation of a seven-membered ring of Sm proteins on to a conserved site of the snRNA (small nuclear RNA). The SMN complex contains the SMN protein Gemin2 and several additional Gemins that participate in snRNP biosynthesis. SMN was first identified as the product of a gene found to be deleted or mutated in patients with the neurodegenerative disease SMA (spinal muscular atrophy), the leading genetic cause of infant mortality. In the present study, we report the solution structure of Gemin2 bound to the Gemin2-binding domain of SMN determined by NMR spectroscopy. This complex reveals the structure of Gemin2, how Gemin2 binds to SMN and the roles of conserved SMN residues near the binding interface. Surprisingly, several conserved SMN residues, including the sites of two SMA patient mutations, are not required for binding to Gemin2. Instead, they form a conserved SMN/Gemin2 surface that may be functionally important for snRNP assembly. The SMN-Gemin2 structure explains how Gemin2 is stabilized by SMN and establishes a framework for structure-function studies to investigate snRNP biogenesis as well as biological processes involving Gemin2 that do not involve snRNP assembly.     

Substrate Locking Promotes Dimer-Dimer Docking of an Enzyme Antibiotic Target

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Soil organic carbon fractions in the Great Plains of the United States: an application of mid-infrared spectroscopy

Biogeochemistry - Spectroscopy is a powerful means of increasing the availability of soil data necessary for understanding carbon cycling in a changing world. Here, we develop a calibration...     

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration (R_eco), net ecosystem CO₂ exchange (NEE; R_eco − GPP), and terrestrial methane (CH₄) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km² flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO₂-C year⁻¹. Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH₄ emissions from tundra and boreal wetlands (not accounting for aquatic CH₄) were estimated at 35 Tg CH₄-C year⁻¹. Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.     

Biofeedback treatments of generalized anxiety disorder: Preliminary results

Forty-five individuals with generalized anxiety (38 with GAD as defined by DSM-III) were randomized to 4 treatment conditions or a waiting list control. Patients received 8 sessions of either frontal EMG biofeedback, biofeedback to increase EEG alpha, biofeedback to decrease EEG alpha, or a pseudomeditation control condition. All treated subjects showed significant reductions in STAI-Trait Anxiety and psychophysiologic symptoms on the Psychosomatic Symptom Checklist. Only alpha-increase biofeedback subjects showed significant reductions in heart rate reactivity to stressors at a separate psychophysiological testing session. Decreased self-report of anxiety was maintained at 6 weeks posttreatment.     

Bmpr1a signaling plays critical roles in palatal shelf growth and palatal bone formation

Cleft palate, including submucous cleft palate, is among the most common birth defects in humans. While overt cleft palate results from defects in growth or fusion of the developing palatal shelves, submucous cleft palate is characterized by defects in palatal bones. In this report, we show that the Bmpr1a gene, encoding a type I receptor for bone morphogenetic proteins (Bmp), is preferentially expressed in the primary palate and anterior secondary palate during palatal outgrowth. Following palatal fusion, Bmpr1a mRNA expression was upregulated in the condensed mesenchyme progenitors of palatal bone. Tissue-specific inactivation of Bmpr1a in the developing palatal mesenchyme in mice caused reduced cell proliferation in the primary and anterior secondary palate, resulting in partial cleft of the anterior palate at birth. Expression of Msx1 and Fgf10 was downregulated in the anterior palate mesenchyme and expression of Shh was downregulated in the anterior palatal epithelium in the Bmpr1a conditional mutant embryos, indicating that Bmp signaling regulates mesenchymal-epithelial interactions during palatal outgrowth. In addition, formation of the palatal processes of the maxilla was blocked while formation of the palatal processes of the palatine was significantly delayed, resulting in submucous cleft of the hard palate in the mutant mice. Our data indicate that Bmp signaling plays critical roles in the regulation of palatal mesenchyme condensation and osteoblast differentiation during palatal bone formation.     

Structural and functional effects of tryptophans inserted into the membrane-binding and substrate-binding sites of human group IIA phospholipase A2

Phospholipase A(2) (PLA(2)) enzymes become activated by binding to biological membranes and hydrolyze phospholipids to free fatty acids and lyso-phospholipids, the precursors of inflammatory mediators. To understand the functional significance of amino acid residues at key positions, we have studied the effects of the substitution of Val(3) (membrane binding surface) and Phe(5) (substrate binding pocket) of human group IIA PLA(2) by tryptophan on the structure and function of the enzyme. Despite the close proximity of the sites of mutations, the V3W mutation results in substantial enhancement of the enzyme activity, whereas the F5W mutant demonstrates significantly suppressed activity. A structural analysis of all three proteins free in buffer and bound to membranes indicates that large differences in activities result from distinct conformational changes in PLA(2)s upon membrane binding. Although PLA(2) and the V3W mutant demonstrate a decrease in helical content and an increase in helix flexibility, the F5W mutant experiences partial distortion of the alpha-helical structure presumably resulting from the tendency of Trp(5) to insert into the membrane. Furthermore, whereas the PLA(2) and the V3W mutant bind to the membrane at similar and apparently productive-mode orientation, the F5W mutant binds to membranes with a distinctly different orientation. It is suggested that both the stimulatory effect of the V3W mutation and the inhibitory effect of the F5W mutation result from the high affinity of Trp for the membrane-water interface. Although Trp(3) at the membrane binding face of PLA(2) facilitates the proper membrane binding of the enzyme, Trp(5) in the internal substrate binding site causes partial unwinding of the N-terminal helix in order to interact with the membrane.     

SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms

Background  

The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validation of these algorithms requires benchmark data sets for which the underlying network is known. Since experimental data sets of the appropriate size and design are usually not available, there is a clear need to generate well-characterized synthetic data sets that allow thorough testing of learning algorithms in a fast and reproducible manner.     

Islet hypertrophy following pancreatic disruption of Smad4 signaling

To investigate the role of transforming growth factor (TGF)-beta family signaling in the adult pancreas, a transgenic mouse (E-dnSmad4) was created that expresses a dominant-negative Smad4 protein driven by a fragment of the elastase promoter. Although E-dnSmad4 mice have normal growth, pancreas weight, and pancreatic exocrine and ductal histology, beginning at 4-6 wk of age, E-dnSmad4 mice show an age-dependent increase in the size of islets. In parallel, an expanded population of replicating cells expressing the E-dnSmad4 transgene is found in the stroma between the enlarged islets and pancreatic ducts. Despite the marked enlargement, E-dnSmad4 islets contain normal ratios and spatial organization of endocrine cell subtypes and have normal glucose homeostasis. Replication of cells derived from primary duct cultures of wild-type mice, but not E-dnSmad4 mice, was inhibited by the addition of TGF-beta family proteins, demonstrating a cell-autonomous effect of the transgene. These data show that, in the adult pancreas, TGF-beta family signaling plays a role in islet size by regulating the growth of a pluripotent progenitor cell residing in the periductal stroma of the pancreas.