bluuebunny/crossref_metadata_2025_split huggingface dataset:
BMPR2 inhibits activin- and BMP-signaling via wild type ALK2
Authors: Olsen Oddrun Elise , Sankar Meenu , Elsaadi Samah , Hella Hanne , Buene Glenn , Darvekar Sagar Ramesh , Misund Kristine , Katagiri Takenobu , Holien Toril 
Published: November 2017

AbstractActivin A is a member of the TGF-β superfamily and activates the transcription factors SMAD2/3 through the ALK4 type 1 receptor. Activin A has also been shown to activate SMAD1/5/8 through mutated variants of the type 1 receptor ALK2. Interestingly, we here show that both activin A and activin B could activate SMAD1/5/8 through endogenous wild type ALK2 in multiple myeloma cells. Knockdown of the type 2 receptor BMPR2 strongly potentiated activin A- and activin B-induced SMAD1/5/8 activation and subsequent cell death. Furthermore, activity of BMP6, BMP7 or BMP9, which also signal via ALK2, was potentiated by BMPR2 knockdown. Similar results were seen in HepG2 liver carcinoma cells. We propose that BMPR2 inhibited ALK2-mediated signaling by preventing ALK2 from oligomerizing with the type 2 receptors ACVR2A and ACVR2B, necessary for ALK2 activation by activins and several BMPs in these cells. In conclusion, BMPR2 could be explored as a possible target for therapy in patients with multiple myeloma.Summary StatementThe activation of SMAD1/5/8 via endogenous wild type ALK2 by activin A, activin B, and certain BMPs was enhanced when BMPR2 levels were knocked down.
Bidirectional Cycling Dynamics of Living Neuronal Networksin Vitro
Authors: Gladkov Arseniy , Grinchuk Oleg , Yana Pigareva , Mukhina Irina , Kazantsev Victor , Pimashkin Alexey 
Published: November 2017

AbstractPhenomena of synchronization, rhythmogenesis and coherence found in brain networks are believed to be a dynamical substrate for cognitive functions such as learning and memory. However, it is still debated whether the rhythmic activity emerges from network morphology developed in neurogenesis or as a result of neuronal dynamics realized under certain conditions. In this research we found, that in neural networks formed in mature hippocampal cultures with high cellular density the spiking activity self-organized and converged to long, complex and rhythmically repeated superbursts. The superburst lasted tens of seconds and consisted of hundreds of short (50-100 ms) small bursts with a high spiking rate of 139.0 ± 78.6 Hz that can be associated with high-frequency oscillations in the hippocampus. In turn, the interval between peak burst activities in the range of 100-150 ms can be treated as a theta rhythm (11.2 ± 1.5 Hz). Distribution of spikes within the bursts was non-random, representing a set of well-defined space-time base patterns or motifs. We found that the long superburst can be classified into two types. Each type was associated with a unique direction of spike propagation and, hence, can be encoded by a binary sequence with random switching between the two “functional” states. Such precisely structured bidirectional rhythmic activity developed in self-organizing cultured networks were quite similar to what observed in thein vivoexperiments.
Blind prediction of noncanonical RNA structure at atomic accuracy
Authors: Watkins Andrew , Geniesse Caleb , Kladwang Wipapat , Zakrevsky Paul , Jaeger Luc , Das Rhiju 
Published: November 2017

AbstractPrediction of RNA structure from nucleotide sequence remains an unsolved grand challenge of biochemistry and requires distinct concepts from protein structure prediction. Despite extensive algorithmic development in recent years, modeling of noncanonical base pairs of new RNA structural motifs has not been achieved in blind challenges. We report herein a stepwise Monte Carlo (SWM) method with a unique add-and-delete move set that enables predictions of noncanonical base pairs of complex RNA structures. A benchmark of 82 diverse motifs establishes the method’s general ability to recover noncanonical pairs ab initio, including multistrand motifs that have been refractory to prior approaches. In a blind challenge, SWM models predicted nucleotide-resolution chemical mapping and compensatory mutagenesis experiments for three in vitro selected tetraloop/receptors with previously unsolved structures (C7.2, C7.10, and R1). As a final test, SWM blindly and correctly predicted all noncanonical pairs of a Zika virus double pseudoknot during a recent community-wide RNA-puzzle. Stepwise structure formation, as encoded in the SWM method, enables modeling of noncanonical RNA structure in a variety of previously intractable problems.
Efficient Flexible Backbone Protein-Protein Docking for Challenging Targets
Authors: Marze Nicholas A. , Roy Burman Shourya S. , Sheffler William , Gray Jeffrey J. 
Published: November 2017

AbstractComputational prediction of protein-protein complex structures facilitates a fundamental understanding of biological mechanisms and enables therapeutics design. Binding-induced conformational changes challenge all current computational docking algorithms by exponentially increasing the conformational space to be explored. To restrict this search to relevant space, some computational docking algorithms exploit the inherent flexibility of the protein monomers to simulate conformational selection from pre-generated ensembles. As the ensemble size expands with increased protein flexibility, these methods struggle with efficiency and high false positive rates. Here, we develop and benchmark a method that efficiently samples large conformational ensembles of flexible proteins and docks them using a novel, six-dimensional, coarse-grained score function. A strong discriminative ability allows an eight-fold higher enrichment of nearnative candidate structures in the coarse-grained phase compared to a previous method. Further, the method adapts to the diversity of backbone conformations in the ensemble by modulating sampling rates. It samples 100 conformations each of the ligand and the receptor backbone while increasing computational time by only 20–80%. In a benchmark set of 88 proteins of varying degrees of flexibility, the expected success rate for blind predictions after resampling is 77% for rigid complexes, 49% for moderately flexible complexes, and 31% for highly flexible complexes. These success rates on flexible complexes are a substantial step forward from all existing methods. Additionally, for highly flexible proteins, we demonstrate that when a suitable conformer generation method exists, RosettaDock 4.0 can dock the complex successfully.SignificancePredicting binding-induced conformational plasticity in protein backbones remains a principal challenge in computational protein–protein docking. To date, there are no methods that can reliably dock proteins that undergo more than 1 Å root-mean-squared-deviation of the backbones of the interface residues upon binding. Here, we present a method that samples backbone motions and scores conformations rapidly, obtaining–for the first time–successful docking of nearly 50% of flexible target complexes with backbone conformational change up to 2.2 Å RMSD. This method will be applicable to a broader range of protein docking problems, which in turn will help us understand biomolecular assembly and protein function.
Variance reduction for antithetic integral control of stochastic reaction networks
Authors: Briat Corentin , Gupta Ankit , Khammash Mustafa 
Published: November 2017

AbstractThe antithetic integral feedback motif recently introduced in [6] is known to ensure robust perfect adaptation for the mean dynamics of a given molecular species involved in a complex stochastic biomolecular reaction network. However, it was observed that it also leads to a higher variance in the controlled network than that obtained when using a constitutive (i.e. open-loop) control strategy. This was interpreted as the cost of the adaptation property and may be viewed as a performance deterioration for the overall controlled network. To decrease this variance and improve the performance, we propose to combine the antithetic integral feedback motif with a negative feedback strategy. Both theoretical and numerical results are obtained. The theoretical ones are based on a tailored moment closure method allowing one to obtain approximate expressions for the stationary variance for the controlled network and predict that the variance can indeed be decreased by increasing the strength of the negative feedback. Numerical results verify the accuracy of this approximation and show that the controlled species variance can indeed be decreased, sometimes below its constitutive level. Three molecular networks are considered in order to verify the wide applicability of two types of negative feedback strategies. The main conclusion is that there is a trade-off between the speed of the settling-time of the mean trajectories and the stationary variance of the controlled species; i.e. smaller variance is associated with larger settling-time.Author summaryHomeostasis, the ability of living organisms to regulate their internal state, is of fundamental importance for their adaptation to environmental changes and their survival. This is the reason why complex regulatory genetic networks evolved and allowed for the emergence of more and more complex organisms. Recently, the theoretical study of those regulatory networks using ideas and concepts from control theory and the design of novel ones have gained a lot of attention. Synthetic regulatory circuits are seen as elementary building blocks for the design of complex networks that need to incorporate some regulating elements to be fully functional. This is for instance the case in metabolic engineering where the production of biomolecules, such as drugs or biofuels, need to be optimized and tightly regulated. A particular circuit, the so-called antithetic integral controller, is now known to ensure homeostasis even when regulatory circuits are subject to randomness. However, it is also known that this circuit increases variability in the network. The effects of a correcting negative feedback loop on the variance are discussed here and it is shown that variability can be reduced this way. Notably, we show that there is a tradeoff between speed of the network and variability.
Aiptasia as a model to study metabolic diversity and specificity in cnidarian-dinoflagellate symbioses
Authors: Rädecker Nils , Raina Jean-Baptiste , Pernice Mathieu , Perna Gabriela , Guagliardo Paul , Kilburn Matt R , Aranda Manuel , Voolstra Christian R 
Published: November 2017

AbstractThe symbiosis between cnidarian hosts and microalgae of the genusSymbiodiniumprovides the foundation of coral reefs in oligotrophic waters. Understanding the nutrient-exchange between these partners is key to identifying the fundamental mechanisms behind this symbiosis. However, deciphering the individual role of host and algal partners in the uptake and cycling of nutrients has proven difficult, given the endosymbiotic nature of this relationship. In this study, we highlight the advantages of the emerging model system Aiptasia to investigate the metabolic diversity and specificity of cnidarian – dinoflagellate symbiosis. For this, we combined traditional measurements with nano-scale secondary ion mass spectrometry (NanoSIMS) and stable isotope labeling to investigate carbon and nitrogen cycling both at the organismal scale and the cellular scale. Our results suggest that the individual nutrient assimilation by hosts and symbionts depends on the identity of their respective symbiotic partner. Further,δ13C enrichment patterns revealed that alterations in carbon fixation rates only affected carbon assimilation in the cnidarian host but not the algal symbiont, suggesting a ‘selfish’ character of this symbiotic association. Based on our findings, we identify new venues for future research regarding the role and regulation of nutrient exchange in the cnidarian - dinoflagellate symbiosis. In this context, the model system approach outlined in this study constitutes a powerful tool set to address these questions.
Mechanochemical Coupling and Bi-Phasic Force-Velocity Dependence in the Ultra-Fast Ring ATPase SpoIIIE
Authors: Liu Ninning , Chistol Gheorghe , Cui Yuanbo , Bustamante Carlos 
Published: November 2017

AbstractMulti-subunit ring-shaped ATPases are molecular motors that harness chemical free energy to perform vital mechanical tasks such as polypeptide translocation, DNA unwinding, and chromosome segregation. Previously we reported the intersubunit coordination and stepping behavior of the hexameric ring-shaped ATPase SpoIIIE (Liu et al., 2015). Here we use optical tweezers to characterize the motor’s mechanochemistry. Analysis of the motor response to external force at various nucleotide concentrations identifies phosphate release as the likely force-generating step. Analysis of SpoIIIE pausing indicates that pauses are off-pathway events. Characterization of SpoIIIE slipping behavior reveals that individual motor subunits engage DNA upon ATP binding. Furthermore, we find that SpolIIE’s velocity exhibits an intriguing bi-phasic dependence on force. We hypothesize that this behavior is an adaptation of ultra-fast motors tasked with translocating DNA from which they must also remove DNA-bound protein roadblocks. Based on these results, we formulate a comprehensive mechanochemical model for SpoIIIE.
Impacts of predators, habitat, recruitment, and disease on soft-shell clamsMya arenariaand stout razor clamsTagelus plebeiusin Chesapeake Bay
Authors: Glaspie Cassandra N. , Seitz Rochelle D. , Ogburn Matthew B. , Dungan Christopher F. , Hines Anson H. 
Published: November 2017

ABSTRACTSoft-shell clams,Mya arenaria, and razor clams,Tagelus plebeius, in Chesapeake Bay have declined since the 1970s, with severe declines since the 1990s. These declines are likely caused by multiple factors including warming, predation, habitat loss, recruitment limitation, disease, and harvesting. A bivalve survey in Chesapeake Bay examined influential factors on bivalve populations, focusing on predation (crabs, fish, and cownose rays), habitat (mud, sand, gravel, shell, or seagrass), environment (temperature, salinity, and dissolved oxygen), recruitment, and disease.M. arenariaandT. plebeiuswere found more often in habitats with complex physical structures (seagrass, shell) than any other habitat. Pulses in bivalve density associated with recruitment were attenuated through the summer and fall when predators are most active, indicating that predators likely influence temporal dynamics in these species. Presence ofMya arenaria,which is near the southern extent of its range in Chesapeake Bay, was negatively correlated with water temperature. Recruitment ofM. arenariain Rhode River, MD, declined between 1980 and 2016. Infection by the parasitic protistPerkinsussp. was associated with stressful environmental conditions, bivalve size, and environmental preferences ofPerkinsussp, but was not associated with bivalve densities. It is likely that habitat loss, low recruitment, and predators are major factors keepingT. plebeiusandM. arenariaat low densities in Chesapeake Bay. Persistence at low densities may be facilitated by habitat complexity (presence of physical structures), whereas further reductions in habitats such as seagrass and shell hash could result in local extinction of these important bivalve species.
Placenta DNA Methylation Adaptation to Maternal Glucose Tolerance in Pregnancy
Authors: Cardenas Andres , Gagné-Ouellet Valerie , Allard Catherine , Brisson Diane , Perron Patrice , Bouchard Luigi , Hivert Marie-France 
Published: November 2017

ABSTRACTMaternal hyperglycemia during pregnancy is associated with fetal growth and adverse perinatal and developmental outcomes. Placental epigenetic maladaptation may underlie these associations. We performed an epigenome-wide association study of term placentas and prenatal maternal glucose response 2-hour post oral glucose challenge at 24-30 weeks of gestation among 448 mother-infant pairs. Maternal glucose levels post-load were strongly associated with lower DNA methylation of 4 CpGs (FDR q<0.05) within the Phosphodiesterase 4B gene (PDE4B). Additionally, three other CpGs were differentially methylated relative to maternal glucose response within the TNFRSF1B; LDLR; and BLM genes (FDR q<0.05). Methylation levels correlated with expression in placental tissue for all 4 CpG sites in PDE4B (rs: 0.26–0.35, P<0.01), LDLR (rs: 0.22, P=0.03) and at TNFRSF1B (rs: -0.25, P=0.01). Our study provides evidence that maternal glucose response during pregnancy is associated with DNA methylation of genes within the placenta that are partially under epigenetic control.
EB1 binding provides a diffusion trap mechanism regulating STIM1 localization and Ca2+ signaling
Authors: Chang Chi-Lun , Chen Yu-Ju , Liou Jen 
Published: November 2017

AbstractThe endoplasmic reticulum (ER) Ca2+ sensor STIM1 forms oligomers and translocates to ER-plasma membrane (PM) junctions to activate store-operated Ca2+ entry (SOCE) following ER Ca2+ depletion. STIM1 also directly interacts with end binding protein 1 (EB1) at microtubule (MT) plus-ends and resembles comet-like structures during time-lapse imaging. Nevertheless, the role of STIM1-EB1 interaction in regulating SOCE remains unresolved. Using live-cell imaging combined with pharmacological perturbation and a reconstitution approach, we revealed that EB1 binding constitutes a diffusion trap mechanism restricting STIM1 targeting to ER-PM junctions. We further showed that STIM1 oligomers retain EB1 binding ability in ER Ca2+-depleted cells. EB1 binding delayed the translocation of STIM1 oligomers to ER-PM junctions and recaptured STIM1 to prevent excess SOCE and ER Ca2+ overload. Thus, the counterbalance of EB1 binding and PM targeting of STIM1 shapes the kinetics and amplitude of local SOCE in regions with growing MTs, and contributes to precise spatiotemporal regulation of Ca2+ signaling crucial for cellular functions and homeostasis.SummarySTIM1 activates store-operated Ca2+ entry (SOCE) by translocating to endoplasmic reticulum-plasma membrane junctions. Chang et al. revealed that STIM1 localization and SOCE are regulated by a diffusion trap mechanism mediated by STIM1 binding to EB1 at growing microtubule ends.
Spliceosome profiling visualizes the operations of a dynamic RNPin vivoat nucleotide resolution
Authors: Burke Jordan E. , Longhurst Adam D. , Merkurjev Daria , Sales-Lee Jade , Rao Beiduo , Moresco James , Yates John , Li Jingyi Jessica , Madhani Hiten D. 
Published: November 2017

SummaryTools to understand how the spliceosome functionsin vivohave lagged behind advances in its structural biology. We describe methods to globally profile spliceosome-bound precursor, intermediates and products at nucleotide resolution. We apply these tools to three divergent yeast species that span 600 million years of evolution. The sensitivity of the approach enables detection of novel cases of non-canonical catalysis including interrupted, recursive and nested splicing. Employing statistical modeling to understand the quantitative relationships between RNA features and the data, we uncover independent roles for intron size, position and number in substrate progression through the two catalytic stages. These include species-specific inputs suggestive of spliceosome-transcriptome coevolution. Further investigations reveal ATP-dependent discard of numerous endogenous substrates at both the precursor and lariat-intermediate stages and connect discard to intron retention, a form of splicing regulation. Spliceosome profiling is a quantitative, generalizable global technology to investigate an RNP central to eukaryotic gene expression.HighlightsMeasurement of spliceosome-bound precursor and intermediate in three speciesNon-canonical splicing events revealedStatistical modeling uncovers substrate features that predict catalytic efficiencyDiscard of suboptimal substrates occursin vivoand predicts intron-retained mRNAs
On-orbit frequency identification of spacecraft based on attitude maneuver data
Authors: Xie Yong , Liu Pan , Cai Guoping 
Published: November 2017

Purpose
The purpose of this paper is to present an on-orbit frequency identification method for spacecraft directly using attitude maneuver data. Natural frequency of flexible solar arrays plays an important role in attitude control design of spacecraft with solar arrays, and its precision will directly affect the accuracy of attitude maneuver. However, when the flexibility of the solar arrays is large, because of air damping, gravity effect etc., the frequency obtained by ground test shows great error compared with the on-orbit real value. One solution to this problem is to conduct on-orbit identification during which proper identification methods are used to obtain the parameters of interest based on the real on-orbit data of spacecraft.

Design/methodology/approach
The observer/Kalman filter identification and eigensystem realization algorithm are used as identification methods, and the attitude maneuver controller is designed using the rigid-body dynamics method.

Findings
Two conclusions are drawn in this paper according to results of numerical simulations. The first one is that the attitude controller based on the rigid-body dynamics method is effective in attitude maneuver of the spacecraft. The second one is that the on-orbit parameter identification can be directly achieved by using attitude maneuver data of spacecraft without adding additional missions.

Practical implications
Based on the methods proposed in this paper, it is convenient to obtain the natural frequencies of the spacecraft using the data of the attitude maneuver, which may greatly reduce the cost of on-orbit identification test.

Originality/value
The way of obtaining natural frequencies based on attitude maneuver data of spacecraft provides high originality and value for practical application.
A simplified model for predicting the propeller-wing interaction
Authors: Huang Xianghua , Zhao Xiaochun , Huang Jiaqin 
Published: November 2017

Purpose
The traditional numerical methods to predict the interaction between the wing and propeller are too complex and time-consuming for computation to a certain extent. Therefore, they are not applicable for a real-time integrated turboprop aircraft model. This paper aims to present a simplified model capable of high-precision and real-time computing.

Design/methodology/approach
A wing model based on the lifting line theory coupled with a propeller model based on the strip theory is used to predict the propeller-wing interaction. To meet the requirement of real-time computing, a novel decoupling parameter is presented to replace lifting line model (LLM) applied for wings with a simplified fitting model (FM).

Findings
The comparison between the LLM and the simplified FM demonstrates that the results of the FM have a good agreement with the results of the LLM, which means that the simplified FM has the advantages of both high-accuracy and real-time computation.

Practical implications
After simplification, the propeller-wing interaction model is suitable for a real-time integrated turboprop aircraft model.

Originality/value
A novel decoupling parameter is presented to replace LLM applied for wings with a simplified FM, which has the advantages of both high-accuracy and real-time computation.