bluuebunny/crossref_metadata_2025_split huggingface dataset:
Different processes shape prokaryotic and picoeukaryotic assemblages in the sunlit ocean microbiome
Authors: Logares Ramiro , Deutschmann Ina M. , Giner Caterina. R. , Krabberød Anders K. , Schmidt Thomas S. B. , Rubinat-Ripoll Laura , Mestre Mireia , Salazar Guillem , Ruiz-González Clara , Sebastián Marta , de Vargas Colomban , Acinas Silvia G. , Duarte Carlos M. , Gasol Josep M. , Massana Ramon 
Published: July 2018

ABSTRACTThe smallest members of the sunlit-ocean microbiome (prokaryotes and picoeukaryotes) participate in a plethora of ecosystem functions with planetary-scale effects. Understanding the processes determining the spatial turnover of this assemblage can help us better comprehend the links between microbiome species composition and ecosystem function. Ecological theory predicts thatselection,dispersalanddriftare main drivers of species distributions, yet, the relative quantitative importance of these ecological processes in structuring the surface-ocean microbiome is barely known. Here we quantified the role of selection, dispersal and drift in structuring surface-ocean prokaryotic and picoeukaryotic assemblages by using community DNA-sequence data collected during the global Malaspina expedition. We found that dispersal limitation was the dominant process structuring picoeukaryotic communities, while a balanced combination of dispersal limitation, selection and drift shaped prokaryotic counterparts. Subsequently, we determined the agents exerting abiotic selection as well as the spatial patterns emerging from the action of different ecological processes. We found that selection exerted via temperature had a strong influence on the structure of prokaryotic communities, particularly on species co-occurrences, a pattern not observed among communities of picoeukaryotes. Other measured abiotic variables had limited selective effects on microbiome structure. Picoeukaryotes presented a higher differentiation between neighbouring communities and a higher distance-decay when compared to prokaryotes, agreeing with their higher dispersal limitation. Finally, drift seemed to have a limited role in structuring the sunlit-ocean microbiome. The different predominance of ecological processes acting on particular subsets of the ocean microbiome suggests uneven responses to environmental change.SIGNIFICANCE STATEMENTThe global ocean contains one of the largest microbiomes on Earth and changes on its structure can impact the functioning of the biosphere. Yet, we are far from understanding the mechanisms that structure the global ocean microbiome, that is, the relative importance of environmentalselection,dispersaland random events (drift). We evaluated the role of these processes at the global scale, based on data derived from a circumglobal expedition and found that these ecological processes act differently on prokaryotes and picoeukaryotes, two of the main components of the ocean microbiome. Our work represents a significant contribution to understand the assembly of marine microbial communities, providing also insights on the links between ecological mechanisms, microbiome structure and ecosystem function.
The impact of different sources of heterogeneity on loss of accuracy from genomic prediction models
Authors: Zhang Yuqing , Bernau Christoph , Parmigiani Giovanni , Waldron Levi 
Published: July 2018

SUMMARYCross-study validation (CSV) of prediction models is an alternative to traditional cross-validation (CV) in domains where multiple comparable datasets are available. Although many studies have noted potential sources of heterogeneity in genomic studies, to our knowledge none have system atically investigated their intertwined impacts on prediction accuracy across studies. We employ a hybrid parametric/non-parametric bootstrap method to realistically simulate publicly available compendia of microarray, RNA-seq, and whole metagenome shotgun (WMS) microbiome studies of health outcomes. Three types of heterogeneity between studies are manipulated and studied: imbalances in the prevalence of clinical and pathological covariates, 2) differences in gene covariance that could be caused by batch, platform, or tumor purity effects, and 3) differences in the “true” model that associates gene expression and clinical factors to outcome. We assess model accuracy while altering these factors. Lower accuracy is seen in CSV than in CV. Surprisingly, heterogeneity in known clinical covariates and differences in gene covariance structure have very limited contributions in the loss of accuracy when validating in new studies. However, forcing identical generative models greatly reduces the within/across study difference. These results, observed consistently for multiple disease outcomes and omics platforms, suggest that the most easily identifiable sources of study heterogeneity are not necessarily the primary ones that undermine the ability to accurately replicate the accuracy of omics prediction models in new studies. Unidentified heterogeneity, such as could arise from unmeasured confounding, may be more important.
Positive-feedback defines the timing and robustness of angiogenesis
Authors: Page Donna J. , Thuret Raphael , Venkatraman Lakshmi , Takahashi Tokiharu , Bentley Katie , Herbert Shane P. 
Published: July 2018

SUMMARYBlood vessel formation by angiogenesis is critical for tissue development, homeostasis and repair, and is frequently dysregulated in disease[1–3]. Angiogenesis is triggered by vascular endothelial growth factor receptor-2/3 (VEGFR) signalling, which induces motile endothelial cell (ECs) tip identity[4,5]. Tip cells lead new branching vessels, but also coordinate collective EC movement by repressing tip identity in adjacent ECs via Delta-Like 4 (DLL4)-Notch-mediated down-regulation of VEGFR activity[6–13]. Hence, angiogenesis is driven by lateral inhibition-mediated competition of ECs for migratory status. Recent work reveals that temporal modulation of this DLL4-Notch-mediated lateral inhibition circuit fundamentally shapes both normal and pathological angiogenesis[14–17]. However, the core regulatory network defining the timing and dynamics of EC decision-making is unclear. Here, by integrating computational modeling with in-vivo experimentation, we uncover a unique ultrasensitive switch that temporally defines EC lateral inhibition and ultimately determines the timing, magnitude and robustness of angiogenic responses. We reveal that positive-feedback to Vegfr via the atypical tetraspanin, tm4sf18, amplifies Vegfr activity and expedites EC decision-making in-vivo. Moreover, this Tm4sf18-mediated positive-feedback confers robustness to angiogenesis against changeable environmental conditions by invoking bistable-like behavior. Consequently, mutation of tm4sf18 in zebrafish delays motile EC selection, generates hypoplastic vessels, sensitizes ECs to fluctuations in pro-angiogenic signal and disrupts angiogenesis. We propose that positive-feedback transforms the normally protracted process of lateral inhibition into a quick, adaptive and robust decision-making mechanism, suggestive of a general framework for temporal modulation of cell fate specification in development and disease.
Deciphering gene regulation from gene expression dynamics using deep neural network
Authors: Shen Jingxiang , Petkova Mariela D. , Tu Yuhai , Liu Feng , Tang Chao 
Published: July 2018

AbstractComplex biological functions are carried out by the interaction of genes and proteins. Uncovering the gene regulation network behind a function is one of the central themes in biology. Typically, it involves extensive experiments of genetics, biochemistry and molecular biology. In this paper, we show that much of the inference task can be accomplished by a deep neural network (DNN), a form of machine learning or artificial intelligence. Specifically, the DNN learns from the dynamics of the gene expression. The learnt DNN behaves like an accurate simulator of the system, on which one can performin-silicoexperiments to reveal the underlying gene network. We demonstrate the method with two examples: biochemical adaptation and the gap-gene patterning in fruit fly embryogenesis. In the first example, the DNN can successfully find the two basic network motifs for adaptation – the negative feedback and the incoherent feed-forward. In the second and much more complex example, the DNN can accurately predict behaviors of essentially all the mutants. Furthermore, the regulation network it uncovers is strikingly similar to the one inferred from experiments. In doing so, we develop methods for deciphering the gene regulation network hidden in the DNN “black box”. Our interpretable DNN approach should have broad applications in genotype-phenotype mapping.SignificanceComplex biological functions are carried out by gene regulation networks. The mapping between gene network and function is a central theme in biology. The task usually involves extensive experiments with perturbations to the system (e.g. gene deletion). Here, we demonstrate that machine learning, or deep neural network (DNN), can help reveal the underlying gene regulation for a given function or phenotype with minimal perturbation data. Specifically, after training with wild-type gene expression dynamics data and a few mutant snapshots, the DNN learns to behave like an accurate simulator for the genetic system, which can be used to predict other mutants’ behaviors. Furthermore, our DNN approach is biochemically interpretable, which helps uncover possible gene regulatory mechanisms underlying the observed phenotypic behaviors.
Neural crest cells regulate optic cup morphogenesis by promoting extracellular matrix assembly
Authors: Bryan Chase D. , Pfeiffer Rebecca L. , Jones Bryan W. , Kwan Kristen M. 
Published: July 2018

AbstractThe interactions between an organ and its surrounding environment are critical in regulating its development. In vertebrates, neural crest and mesodermal mesenchymal cells have been observed close to the eye during development, and mutations affecting this periocular mesenchyme can cause defects in early eye development, yet the underlying mechanism has been unknown. Here, using timelapse microscopy and four-dimensional cell tracking in zebrafish, we establish that genetic loss of neural crest impairs cell movements within the optic vesicle. At the ultrastructural level, neural crest cells are required for basement membrane formation specifically around the retinal pigment epithelium. Neural crest cells express the extracellular matrix crosslinking protein nidogen and, strikingly, ectopically expressing nidogen in the absence of neural crest partially restores optic cup morphogenesis. These results demonstrate that the neural crest is required for local establishment of ocular extracellular matrix superstructure, which in turn drives optic cup morphogenesis.
EIPR1 controls dense-core vesicle cargo retention and EARP complex localization in insulin-secreting cells
Authors: Topalidou Irini , Cattin-Ortolá Jérôme , Hummer Blake , Asensio Cedric S. , Ailion Michael 
Published: July 2018

AbstractDense-core vesicles (DCVs) are secretory vesicles found in neurons and endocrine cells. DCVs package and release cargos including neuropeptides, biogenic amines, and peptide hormones. We recently identified the endosome-associated recycling protein (EARP) complex and the EARP-interacting protein EIPR-1 as proteins important for controlling levels of DCV cargos inC. elegansneurons. Here we determine the role of mammalian EIPR1 in insulinoma cells. We find that inEipr1KO cells, there is reduced insulin secretion, and mature DCV cargos such as insulin and carboxypeptidase E (CPE) accumulate near the trans-Golgi network and are not retained in mature DCVs in the cell periphery. In addition, we find that EIPR1 is required for the stability of the EARP complex subunits and for the localization of EARP and its association with membranes, but EIPR1 does not affect localization or function of the related Golgi-associated retrograde protein (GARP) complex. EARP is localized to two distinct compartments related to its function: an endosomal compartment and a DCV biogenesis-related compartment. We propose that EIPR1 functions with EARP to control both endocytic recycling and DCV maturation.
iOmicsPASS: a novel method for integration of multi-omics data over biological networks and discovery of predictive subnetworks
Authors: Koh Hiromi W.L. , Fermin Damian , Choi Kwok Pui , Ewing Rob , Choi Hyungwon 
Published: July 2018

AbstractWe developed iOmicsPASS, an intuitive method for network-based multi-omics data integration and detection of biological subnetworks for phenotype prediction. The method converts abundance measurements into co-expression scores of biological networks and uses a powerful phenotype prediction method adapted for network-wise analysis. Simulation studies show that the proposed data integration approach considerably improves the quality of predictions. We illustrate iOmicsPASS through the integration of quantitative multi-omics data using transcription factor regulatory network and protein-protein interaction network for cancer subtype prediction. Our analysis of breast cancer data identifies network signatures surrounding established markers of molecular subtypes. The analysis of colorectal cancer data highlights a protein interactome surrounding key proto-oncogenes as predictive features of subtypes, rendering them more biologically interpretable than the approaches integrating data without a priori relational information. However, the results indicate that current molecular subtyping is overly dependent on transcriptomic data and crude integrative analysis fails to account for molecular heterogeneity in other -omics data. The analysis also suggest that tumor subtypes are not mutually exclusive and future subtyping should therefore consider multiplicity in assignments.Availability: https://github.com/cssblab/iOmicsPASS
Continuous single cell transcriptome dynamics reveal a default vascular smooth muscle fate of FLK1 mesoderm
Authors: Zhao Haiyong , Choi Kyunghee 
Published: July 2018

AbstractBlood and endothelial cells arise from hemangiogenic progenitors that are specified from FLK1-expressing mesoderm by the transcription factor ETV2. FLK1 mesoderm also contributes to other tissues, including vascular smooth muscle (VSM) and cardiomyocytes. However, the developmental process of FLK1 mesoderm generation and its allocation to various cell fates remain obscure. Recent single cell RNA-sequencing (scRNA-seq) studies of early stages of embryos, or in vitro differentiated human embryonic stem (ES) cells have provided unprecedented information on the spatiotemporal resolution of cells in embryogenesis. These snapshots nonetheless offer insufficient information on dynamic developmental processes due to inadvertently missing intermediate states and unavoidable batch effects. Here we performed scRNA-seq of in vitro differentiated ES cells as well as extraembryonic yolk sac cells, which contain the very first arising hemangiogenic and VSM lineages, to capture the continuous developmental process leading to hemangiogenesis. We found that hemangiogenic progenitors from ES cells develop through intermediate gastrulation stages, which were gradually specified by ‘relay’-like highly overlapping transcription factor modules. Unexpectedly, VSM and hemangiogenic lineages share the closest transcriptional program. Moreover, transcriptional program of theFlk1mesoderm was maintained in the VSM lineage, suggesting the VSM lineage may be the default pathway of FLK1 mesoderm. We also identified cell adhesion signals possibly contributing to ETV2-mediated activation of the hemangiogenic program. This continuous transcriptome map will facilitate both basic and applied studies of mesoderm and its derivatives.
Expression of the Phosphatase Ppef2 Controls Survival and Function of CD8+Dendritic Cells
Authors: Zwick Markus , Ulas Thomas , Cho Yi-Li , Ried Christine , Grosse Leonie , Simon Charlotte , Bernhard Caroline , Busch Dirk H. , Schultze Joachim L. , Buchholz Veit R. , Stutte Susanne , Brocker Thomas 
Published: July 2018

AbstractApoptotic cell death of Dendritic cells (DCs) is critical for immune homeostasis. Although intrinsic mechanisms controlling DC death have not been fully characterized up to now, experimentally enforced inhibition of DC-death causes various autoimmune diseases in model systems. We have generated mice deficient forProtein Phosphatase with EF-Hands 2(Ppef2), which is selectively expressed in CD8+DCs, but not in other related DC subtypes such as tissue CD103+DCs. Ppef2 is down-regulated rapidly upon maturation of DCs by toll-like receptor stimuli, but not upon triggering of CD40. Ppef2-deficient CD8+DCs accumulate the pro-apoptoticBcl-2-like protein 11(Bim) and show increased apoptosis and reduced competitve repopulation capacities. Furthermore, Ppef2−/−CD8+DCs have strongly diminished antigen presentation capacitiesin vivo, as CD8+T cells primed by Ppef2−/−CD8+DCs undergo reduced expansion. In conclusion, our data suggests that Ppef2 is crucial to support survival of immature CD8+DCs, while Ppef2 down-regulation during DC-maturation limits T cell responses.
Different subtypes of EGFR exon19 mutation can affect prognosis of patients with non-small cell lung adenocarcinoma
Authors: Tian Yingying , Zhao Jiuzhou , Ren Pengfei , Wang Bo , Zhao Chengzhi , Shi Chao , Wei Bing , Ma Jie , Guo Yongjun 
Published: July 2018

AbstractAimsIn this study, we determined whether different subtypes of epidermal growth factor receptor (EGFR) exon19 mutation are associated with the therapeutic effect of EGFR-tyrosine kinase inhibitors (TKIs) on advanced non-small cell lung adenocarcinoma.MethodsA total of 122 patients with stage III or IV non-small cell lung adenocarcinoma were retrospectively reviewed. Clinical characteristics of these patients, including progression-free survival (PFS) outcome for EGFR-TKI treatment, were analyzed.ResultsAccording to the mutation pattern, we classified the in-frame deletions detected on EGFR Exon19 into three different types: codon deletion (CD), with a deletion of one or more original codons; codon substitution and skipping (CSS), with a deletion of one or two nucleotides but the residues could be translated into a new amino acid without changing following amino acid sequence; CD or CSS plus single nucleotide variant (SNV) (CD/CSS+SNV), exclude CD or CSS, there’s another SNV nearby the deletion region. The clinical characteristics of three groups were analyzed and as a result, no significant difference was found. By comparing the average number of missing bases and amino acids of the three mutation subtypes, it could be discovered that the number of missing bases and amino acids of the three mutation subtypes is diverse, and group CSS> group CD> group CD/CSS+SNV. Finally, survival analysis was performed between three groups of patients. The median PFS of group CD, group CSS and group CD/CSS+SNV was 11 months, 9 months and 14 months respectively. There was a distinct difference in the PFS between group CSS and group CD/CSS+SNV (P=0.035<0.05), and the PFS of group CD/CSS+SNV was longer.ConclusionsDifferent mutation subtypes of EGFR exon19 can predict the therapeutic effect of EGFR-TKIs on advanced non-small cell lung adenocarcinoma.
MagicplexTM Sepsis real-time test for the rapid diagnosis of bloodstream infections in adults
Authors: Zboromyrska Yuliya , Cillóniz Catia , Cobos-Trigueros Nazaret , Almela Manel , Carlos Hurtado Juan , Vergara Andrea , Mata Caterina , Soriano Alex , Mensa Josep , Marco Francesc , Vila Jordi 
Published: July 2018

ABSTRACTSepsis is a serious health condition worldwide, affecting more than 30 million people globally each year. In 2017, the World Health Organization (WHO) adopted a resolution on sepsis: “improving the prevention, diagnosis and clinical management of sepsis”, with the aim of improving early diagnosis, management and prevention to save lives. Blood culture (BC) is generally used to diagnose sepsis because of the low quantity of microbes occurring in the blood during such infections. However, approximately 50% of bloodstream infections (BSI) give negative BC, this figure being higher for sepsis, which delays the start of appropriate antimicrobial therapy. This prospective study evaluated a multiplex real-time polymerase chain reaction, the MagicplexTM Sepsis test (MP), for the detection of pathogens from whole blood, comparing it to routine BC. We analysed 809 blood samples from 636 adult patients, with 132/809 (16.3%) of the samples positive for one or more relevant microorganism according to BC and/or MP. The sensitivity and specificity of MP were 29% and 95%, respectively, while the level of agreement between BC and MP was 87%. The rate of contaminated samples was higher for BC (10%) than MP (4.8%) (P < 0.001). Patients with only MP-positive samples were more likely to be on antimicrobial treatment (47%) than those with only BC-positive samples (18%) (P = 0.002). In summary, the MP test reduces the time taken to identify the microbial pathogen, improving the diagnosis of BSI in patients on antibiotic treatment.
Incomplete information about the partner affects the development of collaborative strategies in joint action
Authors: Chackochan Vinil T. , Sanguineti Vittorio 
Published: July 2018

AbstractPhysical interaction with a partner plays an essential role in our life experience and is the basis of many daily activities. When two physically coupled humans have different and partly conflicting goals, they face the challenge of negotiating some type of collaboration. This requires that both subjects understand their opponent’s state and current actions. But, how would the collaboration be affected if information about their opponent were unreliable or incomplete? Here we show that incomplete information about the partner affects not only the speed at which a collaborative strategy is achieved (less information, slower learning), but also the modality of the collaboration. In particular, incomplete or unreliable information leads to an interaction strategy characterized by alternating leader-follower roles. In contrast, more reliable information leads to a more synchronous behavior, in which no specific roles can be identified. Simulations based on a combination of game theory and Bayesian estimation suggested that synchronous behaviors denote optimal interaction (Nash equilibrium). Roles emerge as sub-optimal forms of interaction, which minimize the need to know about the partner. These findings suggest that physical interaction strategies are shaped by the trade-off of between the task requirements and the uncertainty of the information available about the opponent.Author summaryMany activities in daily life involve physical interaction with a partner or opponent. In many situations they have conflicting goals. Therefore, they need to negotiate some form of collaboration. Although very common, these situations have rarely been studied empirically. In this study, we specifically address what is a ‘optimal’ collaboration and how it can be achieved. We also address how developing a collaboration is affected by uncertainty about the partner. Through a combination of empirical studies and computer simulations based on game theory, we show that subject pairs (dyads) are capable of developing stable collaborations, but the learned collaboration strategy depends on the reliability of the information about the partner. High-information dyads converge to the optimal strategies in game-theoretic sense. Low-information dyads converge to strategies that minimize the need to know about the partner. These findings are consistent with a game theoretic learning model which relies on estimates of partner actions, but not partner goals. This similarity sheds some light on the minimal computational machinery which is necessary to an intelligent agent in order to develop stable physical collaborations.