bluuebunny/crossref_metadata_2025_split huggingface dataset:
From morphogenesis to pathogenesis: A cellulose loosening protein is one of the most widely distributed tools in nature
Authors: Chase William R. , Zhaxybayeva Olga , Rocha Jorge , Cosgrove Daniel J. , Shapiro Lori R. 
Published: May 2019

AbstractPlants must rearrange the network of complex carbohydrates in their cell walls during normal growth and development. To accomplish this, all plants depend on proteins called expansins that non-enzymatically loosen hydrogen bonds between cellulose microfibrils. Because of their key role in cell wall extension during growth, expansin genes are ubiquitous, diverse, and abundant throughout all land plants. Surprisingly, expansin genes have more recently been found in some bacteria and microbial eukaryotes, where their biological functions are largely unknown. Here, we reconstruct the phylogeny of microbial expansin genes. We find these genes in all eukaryotic microorganisms that have structural cellulose in their cell walls, suggesting expansins evolved in ancient marine microorganisms long before the evolution of land plants. We also find expansins in an unexpectedly high phylogenetic diversity of bacteria and fungi that do not have cellulosic cell walls. These bacteria and fungi with expansin genes inhabit varied ecological contexts mirroring the diversity of terrestrial and aquatic niches where plant and/or algal cellulosic cell walls are present. The microbial expansin phylogeny shows evidence of multiple horizontal gene transfer events within and between bacterial and eukaryotic microbial lineages, which may in part underlie their unusually broad phylogenetic distribution. Taken together, we find expansins to be unexpectedly widespread in both bacterial and eukaryotic genetic backgrounds, and that the contribution of these genes to bacterial and fungal ecological interactions with plants and algae has likely been underappreciated.ImportanceCellulose is the most abundant biopolymer on earth. In plant cell walls, where most global cellulose biomass is found, cellulose microfibrils occur intertwined with hemicelluloses and pectins. The rigidity of this polysaccharide matrix provides plant cell walls with structural support, but this rigidity also restricts cellular growth and development. Irreversible, non-enzymatic loosening of structural carbohydrates by expansin proteins is key to successful cell wall growth in plants and green algae. Here, we find that expansin genes are distributed far more broadly throughout diverse bacterial and fungal lineages lacking cellulosic cell walls than previously known. Multiple horizontal gene transfer events are in part responsible for their unusually wide phylogenetic distribution. Together, these results suggest that in addition to being the key evolutionary innovation by which eukaryotes remodel structural cellulose in their cell walls, expansins likely have remarkably broad and under-recognized utility for microbial species that interact with plant and algal structural cellulose in diverse ecological contexts.
Practical considerations for improved reliability and precision during compound specific analysis of δ15N in amino acids using a single combined oxidation-reduction reactor
Authors: Riekenberg Philip M. , van der Meer Marcel , Schouten Stefan 
Published: May 2019

AbstractRATIONALEThere has been increased interest in the analysis for δ15N in amino acids to gain simultaneous insight into both trophic relationships and source producers within ecosystems. New developments in gas chromatography combustion isotope ratio mass spectrometry equipment has led to variable outcomes in performance due to limited information about best practices for new systems.METHODSPrecision for δ15N in amino acids using the single combined oxidation-reduction reactor is improved across a sequence of analyses if the reactor is oxidized for a substantial period (2 h), immediately followed with a conditioning run of alkanes prior to analysis for N, and the liquid N2 CO2 trap is left immersed throughout. A five point calibration curve using amino acids with a range of δ15N values from −2.4‰ to +61.5‰ was used in combination with a 13 amino acid mixture to correct for offsets during derivatization.RESULTSCombining the improved setup with normalization techniques using both internal and external standards allows for a reliable throughput of ~25 samples per week. It allowed for a reproducible level of error of <±0.5‰ within standards repeated 10 times across each sequence and a sample error of (±0.18‰), which is lower than analytical error typically associated with δ15N-amino acid analysis (±1‰).CONCLUSIONSA few practical considerations regarding oxidation and conditioning of the combustion reactor allow for increased sequence capacity with the single combined oxidation-reduction reactor. These considerations combined with normalization techniques result in a higher throughput and reduced analytical error during analysis of δ15N in amino acids.
A dynamical systems framework to uncover the drivers of large-scale cortical activity
Authors: Ashourvan Arian , Pequito Sérgio , Bertolero Maxwell , Kim Jason Z. , Bassett Danielle S. , Litt Brian 
Published: May 2019

ABSTRACTA fundamental challenge in neuroscience is to uncover the principles governing complex interactions between the brain and its external environment. Over the past few decades, the development of functional neuroimaging techniques and tools from graph theory, network science, and computational neuroscience have markedly expanded opportunities to study the intrinsic organization of brain activity. However, many current computational models are fundamentally limited by little to no explicit assessment of the brain’s interactions with external stimuli. To address this limitation, we propose a simple scheme that jointly estimates the intrinsic organization of brain activity and extrinsic stimuli. Specifically, we adopt a linear dynamical model (intrinsic activity) under unknown exogenous inputs (e.g., sensory stimuli), and jointly estimate the model parameters and exogenous inputs. First, we demonstrate the utility of this scheme by accurately estimating unknown external stimuli in a synthetic example. Next, we examine brain activity at rest and task for 99 subjects from the Human Connectome Project, and find significant task-related changes in the identified system, and task-related increases in the estimated external inputs showing high similarity to known task regressors. Finally, through detailed examination of fluctuations in the spatial distribution of the oscillatory modes of the estimated system during the resting state, we find an apparent non-stationarity in the profile of modes that span several brain regions including the visual and the dorsal attention systems. The results suggest that these brain structures display a time-varying relationship, or alternatively, receive non-stationary exogenous inputs that can lead to apparent system non-stationarities. Together, our embodied model of brain activity provides an avenue to gain deeper insight into the relationship between cortical functional dynamics and their drivers.
Task-Based Functional Connectomes Predict Cognitive Phenotypes Across Psychiatric Disease
Authors: Barron Daniel S. , Gao Siyuan , Dadashkarimi Javid , Greene Abigail S. , Spann Marisa N. , Noble Stephanie , Lake Evelyn , Krystal John , Constable R. Todd , Scheinost Dustin 
Published: May 2019

AbstractImportanceWe show that three common approaches to clinical deficits (cognitive phenotype, disease group, disease severity) each offer useful and perhaps complimentary explanations for the brain’s underlying functional architecture as affected by psychiatric disease.ObjectiveTo understand how different clinical frameworks are represented in the brain’s functional connectome.DesignWe use an openly available dataset to create predictive models based on multiple connectomes built from task-based functional MRI data. We use these models to predict individual traits corresponding to multiple cognitive constructs across disease category. We also show that these same connectomes statistically differ depending on disease category and symptom burden.SettingThis was a population-based study with data collected in UCLA.ParticipantsHealthy adults were recruited by community advertisements from the Los Angeles area. Participants with adult ADHD, bipolar disorder, and schizophrenia were recruited using a patient-oriented strategy involving outreach to local clinics and online portals (separate from the methods used to recruit healthy volunteers)
OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine
Authors: López-Cortés Andrés , Paz-y-Miño César , Guerrero Santiago , Cabrera-Andrade Alejandro , Barigye Stephen J. , Munteanu Cristian R. , González-Díaz Humberto , Pazos Alejandro , Pérez-Castillo Yunierkis , Tejera Eduardo 
Published: May 2019

SUMMARYBreast cancer (BC) is a heterogeneous disease where each OncoOmics approach needs to be fully understood as a part of a complex network. Therefore, the main objective of this study was to analyze genetic alterations, signaling pathways, protein-protein interaction networks, protein expression, dependency maps and enrichment maps in 230 previously prioritized genes by the Consensus Strategy, the Pan-Cancer Atlas, the Pharmacogenomics Knowledgebase and the Cancer Genome Interpreter, in order to reveal essential genes to accelerate the development of precision medicine in BC. The OncoOmics essential genes were rationally filtered to 144, 48 (33%) of which were hallmarks of cancer and 20 (14%) were significant in at least three OncoOmics approaches: RAC1, AKT1 CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, PLCG1, GRB2, MED1, TOP2A, GATA3, BCL2, CTNNB1, EGFR and CDK2. According to the Open Targets Platform, there are 111 drugs that are currently being analyzed in 3151 clinical trials in 39 genes. Lastly, there are more than 800 clinical annotations associated with 94 genes in BC pharmacogenomics.
Bayesian multivariate reanalysis of large genetic studies identifies many new associations
Authors: Turchin Michael C. , Stephens Matthew 
Published: May 2019

AbstractGenome-wide association studies (GWAS) have now been conducted for hundreds of phenotypes of relevance to human health. Many such GWAS involve multiple closely-related phenotypes collected on the same samples. However, the vast majority of these GWAS have been analyzed using simple univariate analyses, which consider one phenotype at a time. This is de-spite the fact that, at least in simulation experiments, multivariate analyses have been shown to be more powerful at detecting associations. Here, we conduct multivariate association analyses on 13 different publicly-available GWAS datasets that involve multiple closely-related phenotypes. These data include large studies of anthropometric traits (GIANT), plasma lipid traits (GlobalLipids), and red blood cell traits (HaemgenRBC). Our analyses identify many new associations (433 in total across the 13 studies), many of which replicate when follow-up samples are available. Overall, our results demonstrate that multivariate analyses can help make more effective use of data from both existing and future GWAS.1Author SummaryGenome-wide association studies (GWAS) have become a common and powerful tool for identifying significant correlations between markers of genetic variation and physical traits of interest. Often these studies are conducted by comparing genetic variation against single traits one at a time (‘univariate’); however, it has previously been shown that it is possible to increase your power to detect significant associations by comparing genetic variation against multiple traits simultaneously (‘multivariate’). Despite this apparent increase in power though, researchers still rarely conduct multivariate GWAS, even when studies have multiple traits readily available. Here, we reanalyze 13 previously published GWAS using a multivariate method and find >400 additional associations. Our method makes use of univariate GWAS summary statistics and is available as a software package, thus making it accessible to other researchers interested in conducting the same analyses. We also show, using studies that have multiple releases, that our new associations have high rates of replication. Overall, we argue multivariate approaches in GWAS should no longer be overlooked and how, often, there is low-hanging fruit in the form of new associations by running these methods on data already collected.
Century long fertilization reduces stochasticity controlling grassland microbial community succession
Authors: Liang Yuting , Ning Daliang , Lu Zhenmei , Zhang Na , Hale Lauren , Wu Liyou , Clark Ian M. , McGrath Steve P. , Storkey Jonathan , Hirsch Penny R. , Sun Bo , Zhou Jizhong 
Published: May 2019

AbstractDetermining the drivers underlying ecological succession is a fundamental goal of ecological research and essential for predicting ecosystem functioning in response to human-induced environmental changes. Although various studies have examined the impacts of nitrogen (N) addition on plant and microbial community diversity, structure and activities, it remains unknown how long-term anthropogenic fertilization affects the ecological succession of microbial functional guilds and its underlying community assembly mechanisms. Here, using archived soils, we examined more than a century’s succession in soil microbial functional communities (from 1870 to 2008) from the Park Grass Experiment at Rothamsted Experimental Station, the longest running ecological experiment in the world. Long-term fertilization was found to significantly alter soil functional community structure and led to increasingly convergent succession of soil microbial communities. Meta-analysis indicated that microbial temporal turnover (w) was highly time scale-dependent, and the w value threshold was estimated as 0.0025 with a threshold time point of approximately 160 years. In addition, the importance of stochastic assembly varied greatly in regulating the succession of different microbial guilds. Fertilization had large to medium effects on reducing ecological stochasticity for microbial guilds involved in carbon (C) fixation and degradation, N fixation and mineralization, and denitrification. This century long-term study elucidated the differing influences of assembly mechanisms on soil microbial functional communities involved in C and N cycling, which could not be derived from taxonomic or phylogenetic approaches.
Efficient horizontal transmission without viral super-spreaders may cause the high prevalence of STLV-1 infection in Japanese macaques
Authors: Murata Megumi , Yasunaga Jun-ichirou , Washizaki Ayaka , Seki Yohei , Tan Wei Keat , Mizukami Takuo , Matsuoka Masao , Akari Hirofumi 
Published: May 2019

AbstractsSimian T-cell leukemia virus type-1 (STLV-1) is disseminated among various non-human primate species and is closely related to human T-cell leukemia virus type-1 (HTLV-1), the causative agent of adult T-cell leukemia and HTLV-1-associated myelopathy/tropical spastic paraparesis. Notably, the prevalence of STLV-1 infection in Japanese macaques (JMs) is estimated to be much greater than that in other non-human primates; however, the mechanism and mode of STLV-1 transmission remain unknown. We hypothesized that a substantial proportion of infected macaques may play a critical role as viral super-spreaders for efficient inter-individual transmission leading to the high prevalence of infection. To address this, we examined a cohort of 280 JMs reared in a free-range facility for levels of anti-STLV-1 antibody titers (ABTs) and STLV-1 proviral loads (PVLs). We found that the prevalence of STLV-1 in the cohort reached up to 65% (180/280), however, the ABTs and PVLs were normally distributed with mean values of 4076 and 0.62%, respectively, which were comparable to those of HTLV-1-infected humans. Contrary to our expectations, we did not observe the macaques with abnormally high PVLs and poor ABTs, and therefore, the possibility of viral super-spreaders was unlikely. Results from further analyses regarding age-dependent changes in STLV-1 prevalence and a longitudinal follow-up of STLV-1 seroconversion strongly suggest that frequent horizontal transmission is a major route of STLV-1 infection, probably due to the unique social ecology of JMs associated with environmental adaptation.ImportanceWe investigated the cause of the high prevalence of STLV-1 infection in the studied JMs cohort. Contrary to our expectations, the potential viral super-spreaders as shown by abnormally high PVLs and poor ABTs were not observed among the JMs. Rather, the ABTs and PVLs among the infected JMs were comparable to those of HTLV-1-infected humans although the prevalence of HTLV-1 in humans is much less than the macaques. Further analyses demonstrate that the prevalence drastically increased over one year of age and most of these animals over 6 years of age were infected with STLV-1, and that in the longitudinal follow-up study frequent seroconversion occurred in not only infants but also in juvenile and adult seronegative monkeys (around 20% per year). This is the first report showing that frequent horizontal transmission without viral super-spreaders may cause high prevalence of STLV-1 infection in JMs.
Carbon starvation induces the expression of PprB-regulated genes inPesudomonas aeruginosa
Authors: Wang Congcong , Chen Wenhui , Xia Aiguo , Zhang Rongrong , Huang Yajia , Yang Shuai , Ni Lei , Jin Fan 
Published: May 2019

ABSTRACTPseudomonas aeruginosacan cause severe infections in humans. This bacteria often adopt a biofilm lifestyle that is hard to treat. In several previous studies, the PprA-PprB two-component system (TCS), which controls the expression of type IVb pili, BapA adhesin, and CupE fimbriae, was shown to be involved in biofilm formation. However, signals or environmental conditions that can trigger the PprA-PprB TCS are still unknown, and the molecular mechanisms of PprB-mediated biofilm formation are poorly characterized. Here we report that carbon starvation stress (CCS) can induce the expression ofpprBand genes in the PprB regulon. The stress response sigma factor RpoS, rather than the two-component sensor PprA, was determined to mediate the induction ofpprBtranscription. We also observed a strong negative regulation of PprB to the transcription of itself. Further experiments showed that PprB overexpression greatly enhanced cell-cell adhesion (CCA) and cell-surface adhesion (CSA) inP. aeruginosa. Specially, under the background of PprB overexpression, both of the BapA adhesin and CupE fimbriae displayed positive effect on CCA and CSA, while the type IVb pili showed an unexpected negative effect on CCA and no effect on CSA. In addition, expression of the PprB regulon genes displayed significant increases in 3-day colony biofilms, indicating a possible carbon limitation state in these biofilms. The CSS-RpoS-PprB-Bap/Flp/CupE/Tad pathway identified in this study provides a new perspective on the process of biofilm formation under carbon-limited environments.IMPORTANCETypically, determining the external signals that can trigger a regulatory system is crucial to understand the regulatory logic and inward function of that system. The PprA-PprB two-component system was reported to be involved in biofilm formation inPseudomonas aeruginosa, but the signals that can trigger this system are unknown. In this study, we found that carbon starvation stress (CSS) can induce the transcription ofpprBand genes in PprB regulon, through an RpoS dependent pathway. Increase of PprB expression leads to enhanced cell-cell and cell-surface adhesions inP. aeruginosa,both of which are dependent mainly on the Bap adhesin secretion system and partially on the CupE fimbriae. Our findings suggest that PprB reinforces the structure of biofilms under carbon-limited conditions, and the Bap secretion system and CupE fimbriae are two potential targets for biofilm treatment.
The Polycomb group protein Ring1 regulates dorsoventral patterning of the mouse telencephalon
Authors: Eto Hikaru , Kishi Yusuke , Koseki Haruhiko , Gotoh Yukiko 
Published: May 2019

SummaryPatterning of the dorsal-ventral (D-V) axis of the mammalian telencephalon is fundamental to the formation of distinct functional regions including the neocortex and ganglionic eminences. Morphogenetic signaling by bone morphogenetic protein (BMP), Wnt, Sonic hedgehog (Shh), and fibroblast growth factor (FGF) pathways determines regional identity along this axis. It has remained unclear, however, how region-specific expression patterns of these morphogens along the D-V axis are established, especially at the level of epigenetic (chromatin) regulation. Here we show that epigenetic regulation by Ring1, an essential Polycomb group (PcG) protein, plays a key role in formation of ventral identity in the mouse telencephalon. Deletion of theRing1bor bothRing1aandRing1bgenes in neuroepithelial cells of the mouse embryo attenuated expression of the gene for Shh, a key morphogen for induction of ventral identity, and induced misexpression of dorsal marker genes including those for BMP and Wnt ligands in the ventral telencephalon. PcG protein–mediated trimethylation of histone H3 on lysine-27 (H3K27me3) was also apparent at BMP and Wnt ligand genes in wild-type embryos. Importantly, forced activation of Wnt or BMP signaling repressed the expression ofShhin organotypic and dissociated cultures of the early-stage telencephalon. Our results thus indicate that epigenetic regulation by PcG proteins—and, in particular, that by Ring1— confers a permissive state for the induction ofShhexpression through suppression of BMP and Wnt signaling pathways, which in turn allows the development of ventral identity in the telencephalon.