bluuebunny/crossref_metadata_2025_split huggingface dataset:
Embryonic circular RNAs at tandem duplicated genes in zebrafish present new paradigm in gene expression
Authors: Chong-Morrison Vanessa , Sauka-Spengler Tatjana 
Published: November 2017

AbstractCircular RNAs are a puzzling class of RNAs with covalently closed loop structure, lacking 5’ and 3’ ends. Present in all cells, no unifying theme has emerged regarding their function. Here, we use transcriptional data obtained by biotagging in zebrafish to uncover a high-resolution cohort of embryonic circRNAs expressed in nuclear and polysomal subcellular compartments in three developmental cell types. The ample presence of embryonic circRNAs on polysomes contradicts previous reports suggesting predominant nuclear localisation. We uncover a novel class of circRNAs, significantly enriched at tandem duplicated genes. Using newly-developed NGS-based approach, we simultaneously resolve the full sequence of putative "tandem-circRNAs" and their underlying mRNAs. These form by long-range cis-splicing events often between distant tandem duplicated genes, resulting in chimaeric mRNA transcripts and circRNAs containing their supernumerary excised exons, integrated from multiple tandem loci. Taken together, our results suggest that circularisation events rather than circRNAs themselves are functionally important.
Evaluation of nutrient stoichiometric relationships amongst ecosystem compartments of a subtropical treatment wetland. Do we have “Redfield Wetlands”?
Authors: Julian Paul , Gerber Stefan , Bhomia Rupesh K , King Jill , Osborne Todd Z. , Wright Alan L. , Powers Matthew , Dombrowski Jacob 
Published: November 2017

AbstractBackgroundEvaluation of carbon (C), nitrogen (N) and phosphorus (P) ratios in aquatic and terrestrial ecosystems can advance our understanding of biological processes, nutrient cycling and the fate of organic matter (OM) in these ecosystems. Eutrophication of aquatic ecosystems can change the accumulation and decomposition of OM which can alter biogeochemical cycling and alter the base of the aquatic food web. This study investigated nutrient stoichiometry within and among wetland ecosystem compartments (i.e. water column, flocculent, soil and above ground vegetation biomass) of two sub-tropical treatment wetlands with distinct vegetation communities. Two flow-ways (FWs) within the network of Everglades Stormwater Treatment Areas in south Florida (USA) were selected for this study. We evaluated nutrient stoichiometry of these to understand biogeochemical cycling and controls of nutrient removal in a treatment wetland within an ecological stoichiometry context.ResultsThis study demonstrates that C, N, and P stoichiometry can be highly variable among ecosystem compartments and between FWs. Power law slopes of C, N and P within surface water floc, soil and vegetation were significantly different between and along FWs.ConclusionsAssessment of wetland nutrient stoichiometry between and within ecosystem compartments suggests unconstrained stoichiometry related to P that conforms with the notion of P limitation in the ecosystem. Differences in N:P ratios between floc and soil suggest different pathways of organic nutrient accumulation and retention between FWs. Surface nutrient stoichiometry was highly variable and decoupled (or closed to decoupled, by our criteria), in particular with respect to P. We hypothesize that decoupling may be the imprint of variability in inflow nutrient stoichiometry. However, despite active biogeochemical cycles that could act to restore nutrient stoichiometry along the FW, there was little evidence that such balancing occurred, as the degree of stochiometric decoupling in the water column did change with distance downstream. This information is only the beginning of a larger journey to understand stoichiometric processes within wetland ecosystems and how it related to ecosystem function.
Salt-bridge Dynamics in Intrinsically Disordered Proteins: A trade-off between electrostatic interactions and structural flexibility
Authors: Basu Sankar , Biswas Parbati 
Published: November 2017

AbstractIntrinsically Disordered Proteins (IDPs) are enriched in charged and polar residues; and, therefore, electrostatic interactions play a predominant role in their dynamics. In order to remain multi-functional and exhibit their characteristic binding promiscuity, they need to retain considerable dynamic flexibility. At the same time, they also need to accommodate a large number of oppositely charged residues, which eventually lead to the formation of salt-bridges, imparting local rigidity. The formation of salt-bridges therefore oppose the desired dynamic flexibility. Hence, there appears to be a meticulous trade-off between the two mechanisms which the current study attempts to unravel. With this objective, we identify and analyze salt-bridges, both as isolated as well as composite ionic bond motifs, in the molecular dynamic trajectories of a set of appropriately chosen IDPs. Time evolved structural properties of these salt-bridges like persistence, associated secondary structural ′order-disorder′ transitions, correlated atomic movements, contribution in the overall electrostatic balance of the proteins have been studied in necessary detail. The results suggest that the key to maintain such a trade-off over time is the continuous formation and dissolution of salt-bridges with a wide range of persistence. Also, the continuous dynamic interchange of charged-atom-pairs (coming from a variety of oppositely charged side-chains) in the transient ionic bonds supports a model of dynamic flexibility concomitant with the well characterized stochastic conformational switching in these proteins. The results and conclusions should facilitate the future design of salt-bridges as a mean to further explore the disordered-globular interface in proteins.
Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures
Authors: Palva J. Matias , Wang Sheng H. , Palva Satu , Zhigalov Alexander , Monto Simo , Brookes Matthew J. , Schoffelen Jan-Mathijs , Jerbi Karim 
Published: November 2017

AbstractWhen combined with source modeling, magneto‐ (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase‐ and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or “ghost” interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.Highlights✓Reliable estimation of neuronal coupling with MEG and EEG is challenged by signal mixing✓A number of coupling techniques attempt to overcome this limitation by excluding zero-lag interactions✓Contrary to what is commonly admitted, our simulations illustrate that such interaction metrics will still yield false positives✓Spurious, or “ghost”, interactions are generally detected between sources in the vicinity of true phase-lagged interacting sources✓Signal mixing also severely affects the mutual separability of phase and amplitude correlations
Dissecting single–cell molecular spatiotemporal mobility and clustering at Focal Adhesions in polarised cells by fluorescence fluctuation spectroscopy methods
Authors: Garcia Esther , Bernardino de la Serna Jorge 
Published: November 2017

AbstractQuantitative fluorescence fluctuation spectroscopy from optical microscopy datasets is a very powerful tool to resolve multiple spatiotemporal cellular and subcellular processes at the molecular level. In particular, raster image correlation spectroscopy (RICS) and number and brightness analyses (N&B) yield molecular mobility and clustering dynamic information extracted from real-time cellular processes. This quantitative information can be inferred in a highly flexibly and detailed manner, i.e. 1) at the localisation level: from full-frame datasets and multiple regions of interest within; and 2) at the temporal level: not only from full-frame and multiple regions, but also intermediate temporal events. Here we build on previous research in deciphering the molecular dynamics of paxillin, a main component of focal adhesions. Cells use focal adhesions to attach to the extracellular matrix and interact with their local environment. Through focal adhesions and other adhesion structures, cells sense their local environment and respond accordingly; due to this continuous communication, these structures can be highly dynamic depending on the extracellular characteristics. By using a previously well-characterised model like paxillin, we examine powerful sensitivity characteristics and some limitations of RICS and N&B analyses. We show that cells upon contact to different surfaces show differential self-assembly dynamics in terms of molecular diffusion and oligomerisation. In addition, single-cell studies show that these dynamics change gradually following an antero-posterior gradient.
Noise-driven cell differentiation and the emergence of spatiotemporal patterns
Authors: Safdari Hadiseh , Kalirad Ata , Picioreanu Cristian , Tusserkani Rouzbeh , Goliaei Bahram , Sadeghi Mehdi 
Published: November 2017

AbstractOne of the major transitions in evolution is the step from unicellularity into the brave new world of multicellularity. To understand this feat, one has to fathom two main characteristics of multicellular organisms: differentiation and self-organization. Any explanation concerning this major transition should involve mechanisms that can simultaneously explain the marvellous intricacies manifest in the aforementioned characteristics, and an account of the evolution of such traits. Here we propose a noise-driven differentiation (NDD) model. The reliance on noise, in place of a more mechanistic approach, makes the NDD model a more suitable approach to explain differentiation and self-organization. Furthermore, our model sheds some light on the possible evolutionary origins of these biological innovations. To test the NDD model, we utilize a model of cell aggregation. The behavior of this model of cell aggregation is in concert with the NDD model.
Organization of Neural Population Code in Mouse Visual System
Authors: Esfahany Kathleen , Siergiej Isabel , Zhao Yuan , Park Il Memming 
Published: November 2017

AbstractThe mammalian visual system consists of several anatomically distinct areas, layers, and cell types. To understand the role of these subpopulations in visual information processing, we analyzed neural signals recorded from excitatory neurons from various anatomical and functional structures. For each of 186 mice, one of six genetically tagged cell-types and one of six visual areas were targeted while the mouse was passively viewing various visual stimuli. We trained linear classifiers to decode one of six visual stimulus categories with distinct spatiotemporal structures from the population neural activity. We found that neurons in both the primary visual cortex and secondary visual areas show varying degrees of stimulus-specific decodability, and neurons in superficial layers tend to be more informative about the stimulus categories. Additional decoding analyses of directional motion were consistent with these findings. We observed synergy in the population code of direction in several visual areas suggesting area-specific organization of information representation across neurons. These differences in decoding capacities shed light on the specialized organization of neural information processing across anatomically distinct subpopulations, and further establish the mouse as a model for understanding visual perception.
A FRET based biosensor for measuring Gα13 activation in single cells
Authors: Mastop Marieke , Reinhard Nathalie R. , Zuconelli Cristiane R. , Terwey Fenna , Gadella Theodorus W. J. , van Unen Jakobus , Adjobo-Hermans Merel J. W. , Goedhart Joachim 
Published: November 2017

AbstractFörster Resonance Energy Transfer (FRET) provides a way to directly observe the activation of heterotrimeric G-proteins by G-protein coupled receptors (GPCRs). To this end, FRET based biosensors are made, employing heterotrimeric G-protein subunits tagged with fluorescent proteins. These FRET based biosensors complement existing, indirect, ways to observe GPCR activation. Here we report on the insertion of mTurquoise2 at several sites in the human Gα13 subunit. Three variants were found to be functional based on i) plasma membrane localization and ii) ability to recruit p115-RhoGEF upon activation of the LPA2 receptor. The tagged Gα13 subunits were used as FRET donor and combined with cp173Venus fused to the Gγ2 subunit as the acceptor. We constructed Gα13 biosensors by generating a single plasmid that produces Gα13-mTurquoise2, Gβ1 and cp173Venus-Gγ2. The Gα13 activation biosensors showed a rapid and robust response when used in primary human endothelial cells that were treated with thrombin, triggering endogenous protease activated receptors (PARs). This response was efficiently inhibited by the RGS domain of p115-RhoGEF and from the biosensor data we inferred that this is due to GAP activity. Finally, we demonstrated that the Gα13 sensor could be used to dissect heterotrimeric G-protein coupling efficiency in single living cells. We conclude that the Gα13 biosensor is a valuable tool for live-cell measurements that probe Gα13 activation.
TGF-β1 enhances mouse mast cell release of IL-6 and IL-13
Authors: Lyons David O. , Plewes Michele R. , Pullen Nicholas A. 
Published: November 2017

AbstractFor immune cells, TGF-β1 can enhance or repress effector functions. Here, we characterize the effects of TGF-β1 on IgE-mediated activation of primary murine mast cells derived from hematopoietic stem cells (BMMC). We also investigated potential interaction between TGF-β1 and stem-cell factor (SCF). Resting IL-6 production was increased with TGF-β1 but significance was lost following BMMC activation via IgE receptor (FcεRI) crosslinking. SCF also enhanced resting levels of IL-6, but there was no difference from control once FcεRI was engaged. SCF had no effect on IL-13 production; however, TGF-β1 treatment enhanced release of IL-13 upon FcεRI activation. Lastly, percent colocalization of SCF receptor (CD117) and FcεRI were unaffected by TGF-β1 treatment. These data reveal a novel positive effect of soluble TGF-β1 on mast cell activation.
The fractured landscape of RNA-seq alignment: The default in our STARs
Authors: Ballouz Sara , Dobin Alexander , Gingeras Thomas , Gillis Jesse 
Published: November 2017

ABSTRACTMany tools are available for RNA-seq alignment and expression quantification, with comparative value being hard to establish. Benchmarking assessments often highlight methods’ good performance, but are focused on either model data or fail to explain variation in performance. This leaves us to ask, what is the most meaningful way to assess different alignment choices? And importantly, where is there room for progress? In this work, we explore the answers to these two questions by performing an exhaustive assessment of the STAR aligner. We assess STAR’s performance across a range of alignment parameters using common metrics, and then on biologically focused tasks. We find technical metrics such as fraction mapping or expression profile correlation to be uninformative, capturing properties unlikely to have any role in biological discovery. Surprisingly, we find that changes in alignment parameters within a wide range have little impact on both technical and biological performance. Yet, when performance finally does break, it happens in difficult regions, such as X-Y paralogs and MHC genes. We believe improved reporting by developers will help establish where results are likely to be robust or fragile, providing a better baseline to establish where methodological progress can still occur.
Sensory attenuation is related to dopamine dose in Parkinson’s disease
Authors: Wolpe Noham , Zhang Jiaxiang , Nombela Cristina , Ingram James N , Wolpert Daniel M ,   Cam-CAN, Rowe James B. 
Published: November 2017

ABSTRACTAbnormal initiation and control of voluntary movements are among the principal manifestations of Parkinson’s disease (PD). However, the processes underlying these abnormalities and their potential remediation by dopamine treatment remain poorly understood. Normally, movements depend on the integration of sensory information with the predicted consequences of action. This integration leads to a suppression in the intensity of predicted sensations, and increases the relative salience of unexpected stimuli to facilitate the control of movements. We examined this integration process and its relation to dopamine in PD, by measuring sensorimotor attenuation – the reduction in the perceived intensity of predicted sensations from self-generated versus external actions. Patients with idiopathic PD (n=18) and population-derived controls (n=175) matched a set of target forces applied to their left index finger by a torque motor. To match the force, participants either pressed with their right index finger (‘Direct’ condition) or used a linear potentiometer that controlled a motor (‘Slider’ condition). We found that despite changes in sensitivity to different forces, overall sensory attenuation did not differ between medicated PD patients and controls. Importantly, the degree of attenuation was negatively related to PD motor severity but positively related to individual patient dopamine dose, as measured by levodopa dose equivalency. The results suggest that dopamine could regulate the integration of sensorimotor prediction with sensory information to facilitate the control of voluntary movements.
Performance-optimized hierarchical models only partially predict neural responses during perceptual decision making
Authors: Gwilliams Laura , King Jean-Rémi 
Published: November 2017

AbstractModels of perceptual decision making have historically been designed to maximally explain behaviour and brain activity independently of their ability to actually perform tasks. More recently, performance-optimized models have been shown to correlate with brain responses to images and thus present a complementary approach to understand perceptual processes. In the present study, we compare how these approaches comparatively account for the spatio-temporal organization of neural responses elicited by ambiguous visual stimuli. Forty-six healthy human subjects performed perceptual decisions on briefly flashed stimuli constructed from ambiguous characters. The stimuli were designed to have 7 orthogonal properties, ranging from low-sensory levels (e.g. spatial location of the stimulus) to conceptual (whether stimulus is a letter or a digit) and task levels (i.e. required hand movement). Magneto-encephalography source and decoding analyses revealed that these 7 levels of representations are sequentially encoded by the cortical hierarchy, and actively maintained until the subject responds. This hierarchy appeared poorly correlated to normative, drift-diffusion, and 5-layer convolutional neural networks (CNN) optimized to accurately categorize alpha-numeric characters, but partially matched the sequence of activations of 3/6 state-of-the-art CNNs trained for natural image labeling (VGG-16, VGG-19, MobileNet). Additionally, we identify several systematic discrepancies between these CNNs and brain activity, revealing the importance of single-trial learning and recurrent processing. Overall, our results strengthen the notion that performance-optimized algorithms can converge towards the computational solution implemented by the human visual system, and open possible avenues to improve artificial perceptual decision making.
Hard Limits and Performance Tradeoffs in a Class of Sequestration Feedback Systems
Authors: Olsman Noah , Baetica Ania-Ariadna , Xiao Fangzhou , Leong Yoke Peng , Murray Richard M. , Doyle John C. 
Published: November 2017

SummaryFeedback regulation is pervasive in biology at both the organismal and cellular level. In this article, we explore the properties of a particular biomolecular feedback mechanism implemented using the sequestration binding of two molecules. Our work develops an analytic framework for understanding the hard limits, performance tradeoffs, and architectural properties of this simple model of biological feedback control. Using tools from control theory, we show that there are simple parametric relationships that determine both the stability and the performance of these systems in terms of speed, robustness, steady-state error, and leakiness. These findings yield a holistic understanding of the behavior of sequestration feedback and contribute to a more general theory of biological control systems.
Molecular basis of hemoglobin adaptation in the high-flying bar-headed goose
Authors: Natarajan Chandrasekhar , Jendroszek Agnieszka , Kumar Amit , Weber Roy E. , Tame Jeremy R. H. , Fago Angela , Storz Jay F. 
Published: November 2017

AbstractDuring adaptive phenotypic evolution, some selectively fixed mutations may be directly causative and others may be purely compensatory. The relative contribution of these two classes of mutation depends on the form and prevalence of mutational pleiotropy. To investigate the nature of adaptive substitutions and their pleiotropic effects, we used a protein engineering approach to characterize the molecular basis of hemoglobin (Hb) adaptation in the bar-headed goose (Anser indicus), a hypoxia-tolerant species renowned for its trans-Himalayan migratory flights. We synthesized and tested all possible mutational intermediates in the line of descent connecting the wildtype bar-headed goose genotype with the most recent common ancestor of bar-headed goose and its lowland relatives. Site-directed mutagenesis experiments revealed effect-size distributions of causative mutations and biophysical mechanisms underlying changes in function. Trade-offs between alternative functional properties revealed the importance of compensating deleterious pleiotropic effects in the adaptive evolution of protein function.
A method to keep the excitation light sheet in focus in selective plane illumination microscopy
Authors: Gao Liang 
Published: November 2017

AbstractKeeping the excitation light sheet in focus is critical in selective plane illumination microscopy (SPIM) to ensure its 3D imaging ability. Unfortunately, an effective method that can be used in SPIM on general biological specimens to find the axial position of the excitation light sheet and keep it in focus is barely available. Here, we present a method to solve the problem. We investigate its mechanism and demonstrate its performance on a lattice light sheet microscope.