bluuebunny/crossref_metadata_2025_split huggingface dataset:
Size-based ecological interactions drive food web responses to climate warming
Authors: Lindmark Max , Ohlberger Jan , Huss Magnus , Gårdmark Anna 
Published: September 2018

AbstractPredicting the impacts of climate change on animal populations and communities requires understanding of feedbacks between direct physiological responses and indirect effects via ecological interactions. Food-dependent body growth and within-species size variation have major effects on dynamics of populations and communities through feedbacks between individual performance and population size structure. Moreover, evidence suggests a link between temperature and population size structure, but we lack an understanding of how this is mediated by species interactions when life history processes are food-dependent. Here, we use a dynamic stage-structured biomass model with food-, size- and temperature-dependent life history processes to assess how temperature affects coexistence, stability and size structure in a tri-trophic food chain. We show that predator biomass densities decline with warming either gradually or in the form of collapses, depending on which consumer life stage they predominantly feed on. Collapses occur when warming destabilizes the community and induces alternative stable states via Allee effects, which emerge when predators promote their own food source through predation. By contrast, warming at low temperatures stabilizes the community as limit cycles turn to fixed point dynamics, unless predators feed only on juveniles. Elevated costs of being large in warmer environments accelerate the decline in predator persistence and mean body size of the community. These results suggest that predator persistence in warmer climates may be lower than previously acknowledged when accounting for size- and food-dependence of life history processes, and that interactions within and between species can mediate the effects of warming on food web stability.SignificanceClimate warming is altering the dynamics and structure of aquatic ecosystems worldwide. Predicting food web reorganization under rising temperatures requires an understanding of physiological responses and ecological interactions of organisms, both of which depend on body size. We show that size variation within species, food-dependent growth and ecological interactions critically affect how food chains respond to warming. Specifically, warming can stabilize or destabilize food chains and expose predators to increased risk of sudden collapses, resulting in alternative stable food web states. Increasing temperatures can cause abrupt reductions in mean community body size, primarily due to loss of top predators. The potential loss of biodiversity and shifts in ecosystem stability are among the major challenges caused by a warming climate.
Gsmodutils: A python based framework for test-driven genome scale metabolic model development
Authors: Gilbert James P , Pearcy Nicole , Norman Rupert , Millat Thomas , Winzer Klaus , King John , Hodgman Charlie , Minton Nigel , Twycross Jamie 
Published: September 2018

AbstractMotivationGenome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include thousands of reactions and metabolites, with many crucial pathways that only become activated in specific simulation settings. However, despite their widespread use, power and the availability of tools to aid with the construction and analysis of large scale models, little methodology is suggested for the continued management of curated large scale models. For example, when genome annotations are updated or new understanding regarding behaviour of is discovered, models often need to be altered to reflect this. This is quickly becoming an issue for industrial systems and synthetic biotechnology applications, which require good quality reusable models integral to the design, build and test cycle.ResultsAs part of an ongoing effort to improve genome scale metabolic analysis, we have developed a test-driven development methodology for the continuous integration of validation data from different sources. Contributing to the open source technology based around COBRApy, we have developed thegsmodutilsmodelling framework placing an emphasis on test-driven design of models through defined test cases. Crucially, different conditions are configurable allowing users to examine how different designs or curation impact a wide range of system behaviours, minimising error between model versions.AvailabilityThe software framework described within this paper is open source and freely available fromhttp://github.com/SBRCNottingham/gsmodutils
Changes in social groups across reintroductions and effects on post-release survival
Authors: Franks Victoria R. , Andrews Caitlin E. , Ewen John G. , McCready Mhairi , Parker Kevin A. , Thorogood Rose 
Published: September 2018

AbstractReintroductions are essential to many conservation programmes, and thus much research has focussed on understanding what determines the success of these translocation interventions. However, while reintroductions disrupt both the abiotic and social environments, there has been less focus on the consequences of social disruption. Therefore, here we investigate if moving familiar social groups may help animals (particularly naïve juveniles) adjust to their new environment and increase the chances of population establishment. We used social network analysis to study changes in group composition and individual sociality across a reintroduction of 40 juvenile hihi (Notiomystis cincta), a threatened New Zealand passerine. We collected observations of groups before a translocation to explore whether social behaviour before the reintroduction predicted associations after, and whether reintroduction influenced individual sociality (degree). We also assessed whether grouping familiar birds during temporary captivity in aviaries maintained group structure and individual sociality, compared to our normal translocation method (aviaries of random familiarity). Following release, we measured if survival depended on how individual sociality had changed. By comparing these analyses with birds that remained at the source site, we found that translocation lead to re-assortment of groups: non-translocated birds maintained their groups, but translocated juveniles formed groups with both familiar and unfamiliar birds. Aviary holding did not improve group cohesion; instead, juveniles were less likely to associate with aviary-mates. Finally, we found that translocated juveniles that lost the most associates experienced a small but significant tendency for higher mortality. This suggests sociality loss may have represented a disruption that affected their ability to adapt to a new site.
Is there a BMAA transfer in the pelagic and benthic food webs in the Baltic Sea?
Authors: Zguna Nadezda , Karlson Agnes , Ilag Leopold L. , Garbaras Andrius , Gorokhova Elena 
Published: September 2018

AbstractThe evidence regarding BMAA occurrence in the Baltic Sea is contradictory, with benthic sources appearing to be more important than pelagic ones. The latter is counterintuitive considering that pelagic primary producers, such as diatoms, dinoflagellates, and cyanobacteria, are the only plausible source of this compound in the food webs. To elucidate BMAA distribution in trophic pathways, we analyzed BMAA in the pelagic and benthic food webs sampled in summer 2010 in the Northern Baltic Proper. As potential BMAA sources, phytoplankton communities in early and late summer were used. As pelagic consumers, zooplankton, mysids and zooplanktivorous fish (herring) were used, whereas benthic invertebrates (amphipods, priapulids, polychaetes, and clams) and benthivorous fish (perch and flounder) represented the benthic food chain. To establish the trophic structure of the system, the stable isotope (δ13C and δ15N) composition of its components was determined. Contrary to the reported ubiquitous occurrence of BMAA in the Baltic food webs, only phytoplankton and lower consumers (zooplankton and mysids) of the pelagic food chain tested positive. Given that our analytical approaches were adequate, we conclude that no measurable levels of this compound occurred in the benthic invertebrates and any of the tested fish species in the study area. These findings indicate that widely assumed presence and transfer of BMAA to the top consumers in the food webs of the Baltic Sea and, possibly, other systems remain an open question. More controlled experiments and field observations are needed to understand the transfer and possible transformation of BMAA in the food web under various environmental settings.
Quantifying individual differences in brain morphometry underlying symptom severity in Autism Spectrum Disorders
Authors: Kiat Pua Emmanuel Peng , Ball Gareth , Adamson Chris , Bowden Stephen , Seal Marc L 
Published: September 2018

AbstractThe neurobiology of heterogeneous neurodevelopmental disorders such as autism spectrum disorders (ASD) are still unclear. Despite extensive efforts, most findings are difficult to reproduce due to high levels of individual variance in phenotypic expression. To quantify individual differences in brain morphometry in ASD, we implemented a novel subject-level, distance-based method on subject-specific attributes. In a large multi-cohort sample, each subject with ASD (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.58) was strictly matched to a control participant (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.70). Intrapair Euclidean distance of MRI brain morphometry and symptom severity measures were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and bootstrapped permutation testing. Subject-specific structural morphometry features significantly predicted individual variation in ASD symptom severity (19 cortical thickness features, p=0.01, n=5000 permutations; 10 surface area features, p=0.006, n=5000 permutations). Findings remained robust across subjects and were replicated in validation samples. Identified cortical regions implicate key hubs of the salience and default mode networks as neuroanatomical features of social impairment in ASD. Present results highlight the importance of subject-level markers in ASD, and offer an important step forward in understanding the neurobiology of heterogeneous disorders.
Cholinergic switch between two types of slow waves in cerebral cortex
Authors: Nghiem Trang-Anh E , Tort-Colet Núria , Górski Tomasz , Ferrari Ulisse , Moghimyfiroozabad Shayan , Goldman Jennifer S. , Teleńczuk Bartosz , Capone Cristiano , Bal Thierry , di Volo Matteo , Destexhe Alain 
Published: September 2018

AbstractSleep slow waves are known to participate in memory consolidation, yet slow waves occurring under anesthesia present no positive effects on memory. Here, we shed light onto this paradox, based on a combination of extracellular recordingsin vivo,in vitro, and computational models. We find two types of slow waves, based on analyzing the temporal patterns of successive slow-wave events. The first type is consistently observed in natural slow-wave sleep, while the second is shown to be ubiquitous under anesthesia. Network models of spiking neurons predict that the two slow wave types emerge due to a different gain on inhibitory vs excitatory cells and that different levels of spike-frequency adaptation in excitatory cells can account for dynamical distinctions between the two types. This prediction was testedin vitroby varying adaptation strength using an agonist of acetylcholine receptors, which demonstrated a neuromodulatory switch between the two types of slow waves. Finally, we show that the first type of slow-wave dynamics is more sensitive to external stimuli, which can explain how slow waves in sleep and anesthesia differentially affect memory consolidation, as well as provide a link between slow-wave dynamics and memory diseases.
Reduced frontal gamma power at 24 months is associated with better expressive language in toddlers at risk for autism
Authors: Wilkinson Carol L. , Levin April R. , Gabard-Durnam Laurel J. , Tager-Flusberg Helen , Nelson Charles A. 
Published: September 2018

ABSTRACTGamma oscillations have been associated with early language development in typically developing toddlers, and gamma band abnormalities have been observed in individuals with ASD, as well high-risk infant siblings (those having an older sibling with autism), as early as 6-months of age. The current study investigated differences in baseline frontal gamma power and its association with language development in toddlers at high versus low familial risk for autism. EEG recordings as well as cognitive and behavioral assessments were acquired at 24-months as part of prospective, longitudinal study of infant siblings of children with and without autism. Diagnosis of autism was determined at 24–36 months, and data was analyzed across three outcome groups - low risk without ASD (n=43), high-risk without ASD (n=42), and high-risk with ASD (n=16). High-risk toddlerswithoutASD had reduced baseline frontal gamma power (30–50Hz) compared to low-risk toddlers. Among high-risk toddlers increased frontal gamma was only marginally associated with ASD diagnosis (p=0.06), but significantly associated with reduced expressive language ability (p=0.007). No association between gamma power and language was present in the low-risk group. These findings suggest that differences in gamma oscillations in high-risk toddlers may represent compensatory mechanisms associated with improved developmental outcomes.
Switching toxic protein function in life cells
Authors: Faden Frederik , Mielke Stefan , Dissmeyer Nico 
Published: September 2018

SUMMARYToxic proteins are prime targets for molecular farming and efficient tools for targeted cell ablation in genetics, developmental biology, and biotechnology. Achieving conditional activity of cytotoxins and their maintenance in form of stably transformed transgenes is challenging. We demonstrate here a switchable version of the highly cytotoxic bacterial ribonuclease barnase by using efficient temperature-dependent control of protein accumulation in living multicellular organisms. By tuning the levels of the protein, we were able to control the fate of a plant organin vivo. The on-demand-formation of specialized epidermal cells (trichomes) through manipulating stabilization versus destabilization of barnase is a proof-of-concept for a robust and powerful tool for conditional switchable cell arrest. We present this tool both as a potential novel strategy for the manufacture and accumulation of cytotoxic proteins and toxic high-value products in plants or for conditional genetic cell ablation.
Dynamic interaction network inference from longitudinal microbiome data
Authors: Lugo-Martinez Jose , Ruiz-Perez Daniel , Narasimhan Giri , Bar-Joseph Ziv 
Published: September 2018

AbstractBackgroundSeveral studies have focused on the microbiota living in environmental niches including human body sites. In many of these studies researchers collect longitudinal data with the goal of understanding not just the composition of the microbiome but also the interactions between the different taxa. However, analysis of such data is challenging and very few methods have been developed to reconstruct dynamic models from time series microbiome data.ResultsHere we present a computational pipeline that enables the integration of data across individuals for the reconstruction of such models. Our pipeline starts by aligning the data collected for all individuals. The aligned profiles are then used to learn a dynamic Bayesian network which represents causal relationships between taxa and clinical variables. Testing our methods on three longitudinal microbiome data sets we show that our pipeline improve upon prior methods developed for this task. We also discuss the biological insights provided by the models which include several known and novel interactions.ConclusionsWe propose a computational pipeline for analyzing longitudinal microbiome data. Our results provide evidence that microbiome alignments coupled with dynamic Bayesian networks improve predictive performance over previous methods and enhance our ability to infer biological relationships within the microbiome and between taxa and clinical factors.
Transcriptional initiation and mechanically driven propagation of a tissue morphogenetic wave during axis elongation
Authors: Bailles Anais , Collinet Claudio , Philippe Jean-Marc , Lenne Pierre-François , Munro Edwin , Lecuit Thomas 
Published: September 2018

AbstractTissue morphogenesis emerges from coordinated cell shape changes driven by actomyosin contraction1, 2. Spatial patterns of gene expression regionalize and polarize cell behaviours, such as apical constriction in the ventral mesoderm and cell intercalation in the lateral ectoderm ofDrosophila3. Thus, tissue dynamics is largely governed genetically. Actomyosin contractile networks drive cell and tissue-level shape changes and can respond to mechanical stimuli4–9. However how genetic information and mechanical control drive tissue-level morphogenesis is not well understood.Here we report two phases and modalities of Rho1 and non-muscle MyosinII (MyoII) activation in theDrosophilaposterior endoderm. First, Rho1/MyoII are induced apically in a spatially restricted primordium region via localized transcription of the GPCR ligand Fog. Second, a tissue-scale travelling wave of Rho1/MyoII activation and cell invagination progresses anteriorly across the dorsal epithelium at a constant speed of 1 cell every 3 minutes. Remarkably, the MyoII wave does not require sustained gene transcription, and is also insensitive to perturbations in the level and pattern of Fog expression. Thus, whilefogtranscription initiates Rho1/MyoII activation in the primordium, Fog delivery does not govern wave dynamics. Instead, perturbing the mechanical environment of the endoderm impaired MyoII wave dynamics. MyoII inhibition blocked acute Rho1 activation and propagation, suggesting that MyoII contractility provides both local feedback amplification and spatial coupling necessary for wave progression. Finally, we identify a cycle of 3D cell deformations that link MyoII activation and invagination in one row of cells to vitelline membrane attachment, apical spreading, MyoII activation and invagination in the next row, to drive anterior progression of the invagination wave. Thus endoderm morphogenesis emerges from local transcriptional initiation and a mechanically driven travelling cycle of cell contraction and deformation.
A Genetically Engineered Primary Human Natural Killer Cell Platform for Cancer Immunotherapy
Authors: Pomeroy Emily J. , Hunzeker John T. , Kluesner Mitchell T. , Crosby Margaret R. , Lahr Walker S. , Bendzick Laura , Miller Jeffrey S. , Webber Beau R. , Geller Melissa A. , Walcheck Bruce , Felices Martin , Starr Timothy K. , Moriarity Branden S. 
Published: September 2018

AbstractTumors can evade natural killer (NK) cells by activating inhibitory pathways. We therefore have developed a highly efficient CRISPR/Cas9-based method for editing the genome of peripheral blood human NK cells (PB-NKs) to knock out ADAM17 and PD1 or knock-in genes using recombinant AAV6. Our method allows editing of PB-NKs at efficiencies reaching 90%, equivalent to methods reported for primary human T cells. Moreover, we demonstrate that ADAM17 and PD1 KO PB-NKs have significantly improved activity, cytokine production, and cancer cell cytotoxicity. Our platform represents a feasible method for generating engineered NK cells as a universal therapeutic for cancer immunotherapy.
A phylogenomic resolution of the sea urchin tree of life
Authors: Mongiardino Koch Nicolás , Coppard Simon E. , Lessios Harilaos A. , Briggs Derek E. G. , Mooi Rich , Rouse Greg W. 
Published: September 2018

AbstractBackgroundEchinoidea is a clade of marine animals including sea urchins, heart urchins, sand dollars and sea biscuits. Found in benthic habitats across all latitudes, echinoids are key components of marine communities such as coral reefs and kelp forests. A little over 1,000 species inhabit the oceans today, a diversity that traces its roots back at least to the Permian. Although much effort has been devoted to elucidating the echinoid tree of life using a variety of morphological data, molecular attempts have relied on only a handful of genes. Both of these approaches have had limited success at resolving the deepest nodes of the tree, and their disagreement over the positions of a number of clades remains unresolved.ResultsWe performed de novo sequencing and assembly of 17 transcriptomes to complement available genomic resources of sea urchins and produce the first phylogenomic analysis of the clade. Multiple methods of probabilistic inference recovered identical topologies, with virtually all nodes showing maximum support. In contrast, the coalescent-based method ASTRAL-II resolved one node differently, a result apparently driven by gene tree error induced by evolutionary rate heterogeneity. Regardless of the method employed, our phylogenetic structure deviates from the currently accepted classification of echinoids, with neither Acroechinoidea (all euechinoids except echinothurioids), nor Clypeasteroida (sand dollars and sea biscuits) being monophyletic as currently defined. We demonstrate the strength and distribution of phylogenetic signal throughout the genome for novel resolutions of these lineages and rule out systematic biases as possible explanations.ConclusionsOur investigation substantially augments the molecular resources available for sea urchins, providing the first transcriptomes for many of its main lineages. Using this expanded genomic dataset, we resolve the position of several clades in agreement with early molecular analyses but in disagreement with morphological data. Our efforts settle multiple phylogenetic uncertainties, including the position of the enigmatic deep-sea echinothurioids and the identity of the sister clade to sand dollars. We offer a detailed assessment of evolutionary scenarios that could reconcile our findings with morphological evidence, opening up new lines of research into the development and evolutionary history of this ancient clade.
Changes in epithelial proportions and transcriptional state underlie major premenopausal breast cancer risks
Authors: Murrow Lyndsay M. , Weber Robert J. , Caruso Joseph A. , McGinnis Christopher S. , Phong Kiet , Gascard Philippe , Borowsky Alexander D. , Desai Tejal A. , Thomson Matthew , Tlsty Thea , Gartner Zev J. 
Published: September 2018

AbstractThe human breast undergoes lifelong remodeling in response to estrogen and progesterone, but hormone exposure also increases breast cancer risk. Here, we use single-cell analysis to identify distinct mechanisms through which breast composition and cell state affect hormone signaling. We show that prior pregnancy reduces the transcriptional response of hormone-responsive (HR+) epithelial cells, whereas high body mass index (BMI) reduces overall HR+ cell proportions. These distinct changes both impact neighboring cells by effectively reducing the magnitude of paracrine signals originating from HR+ cells. Because pregnancy and high BMI are known to protect against hormone-dependent breast cancer in premenopausal women, our findings directly link breast cancer risk with person-to-person heterogeneity in hormone responsiveness. More broadly, our findings illustrate how cell proportions and cell state can collectively impact cell communities through the action of cell-to-cell signaling networks.