bluuebunny/crossref_metadata_2025_split huggingface dataset:
Light affects behavioral despair involving the clock genePeriod 1
Authors: Olejniczak Iwona , Ripperger Jürgen A. , Sandrelli Federica , Schnell Anna , Mansencal-Strittmatter Laureen , Hui Ka Yi , Brenna Andrea , Fredj Naila Ben , Albrecht Urs 
Published: May 2020

AbstractLight at night has strong effects on physiology and behavior of mammals. It affects mood in humans, which is exploited as light therapy, and has been shown to reset the circadian clock in the suprachiasmatic nuclei (SCN). This resetting is paramount to align physiological and biochemical timing to the environmental light-dark cycle. Here we provide evidence that light affects mood-related behaviors also in mice by activating the clock genePeriod1 (Per1)in the lateral habenula (LHb), a brain region known to modulate mood-related behaviors. A light pulse given at ZT22 to wild type mice caused profound changes of gene expression in the mesolimbic dopaminergic system including the nucleus accumbens (NAc). Sensory perception of smell and G-protein coupled receptor signaling was affected the most in this brain region. Interestingly, most of these genes were not affected inPer1knock-out animals, indicating that induction ofPer1by light serves as a filter for light-mediated gene induction in the brain. Taken together we show that light affects mood-related behavior in mice at least in part via induction ofPer1in the LHb with consequences on signaling mechanisms in the mesolimbic dopaminergic system.
Using optimal control to understand complex metabolic pathways
Authors: Tsiantis Nikolaos , Banga Julio R. 
Published: May 2020

AbstractBackgroundWe revisit the idea of explaining and predicting dynamics in biochemical pathways from first-principles. A promising approach is to exploit optimality principles that can be justified from an evolutionary perspective. In the context of the cell, several previous studies have explained the dynamics of simple metabolic pathways exploiting optimality principles in combination with dynamic models, i.e. using an optimal control framework. For example, dynamics of gene expression in small metabolic models can be explained assuming that cells have developed optimal adaptation strategies. Most of these works have considered rather simplified representations, such as small linear pathways, or reduced networks with a single branching point.ResultsHere we consider the extension of this approach to more realistic scenarios, i.e. biochemical pathways of arbitrary size and structure. We first show that exploiting optimality principles for these networks poses great challenges due to the complexity of the associated optimal control problems. Second, in order to surmount such challenges, we present a computational framework based on multicriteria optimal control which has been designed with scalability and efficiency in mind, extending several recent methods. This framework includes mechanisms to avoid common pitfalls, such as local optima, unstable solutions or excessive computation time. We illustrate its performance with several case studies considering the central carbon metabolism ofS. cerevisiaeandB. subtilis. In particular, we consider metabolic dynamics during nutrient shift experiments.ConclusionsWe show how multi-objective optimal control can be used to predict temporal profiles of enzyme activation and metabolite concentrations in complex metabolic pathways. Further, we show how the multicriteria approach allows us to consider general cost/benefit trade-offs that have been likely favored by evolution. In this study we have considered metabolic pathways, but this computational framework can also be applied to analyze the dynamics of other complex pathways, such as signal transduction networks.
The use of two-sample methods for Mendelian randomization analyses on single large datasets
Authors: Minelli Cosetta , Fabiola Del Greco M. , van der Plaat Diana A. , Bowden Jack , Sheehan Nuala A. , Thompson John 
Published: May 2020

AbstractBackgroundWith genome-wide association data for many exposures and outcomes now available from large biobanks, one-sample Mendelian randomization (MR) is increasingly used to investigate causal relationships. Many robust MR methods are available to address pleiotropy, but these assume independence between the gene-exposure and gene-outcome association estimates. Unlike in two-sample MR, in one-sample MR the two estimates are obtained from the same individuals, and the assumption of independence does not hold in the presence of confounding.MethodsWith simulations mimicking a typical study in UK Biobank we assessed the performance, in terms of bias and precision of the MR estimate, of the fixed-effect and (multiplicative) random-effects meta-analysis method, weighted median estimator, weighted mode estimator and MR-Egger regression, used in both one-sample and two-sample data. We considered scenarios differing for: presence/absence of a true causal effect; amount of confounding; presence and type of pleiotropy (none, balanced or directional).ResultsEven in the presence of substantial correlation due to confounding, all methods performed well when used in one-sample MR except for MR-Egger, which resulted in bias reflecting direction and magnitude of the confounding. Such bias was much reduced in the presence of very high variability in instrumental strength across variants (I2GXof 97%).ConclusionsTwo-sample MR methods can be safely used for one-sample MR performed within large biobanks, expect for MR-Egger. MR-Egger is not recommended for one-sample MR unless the correlation between the gene-exposure and gene-outcome estimates due to confounding can be kept low, or the variability in instrumental strength is very high.Key MessagesCurrent availability of phenotypic and genetic data from large biobanks, such as UK Biobank, has led to increasing use of one-sample Mendelian randomization (MR) to investigate causal relationships in epidemiological researchRobust MR methods have been developed to address pleiotropy, but they assume independence between the gene-exposure and gene-outcome association estimates; this holds in two-sample MR but not in one-sample MRWe illustrate the practical implications, in terms of bias and precision of the MR causal effect estimate, of using robust two-sample methods in one-sample MR studies performed within large biobanksTwo-sample MR methods can be safely used for one-sample MR performed within large biobanks, expect for MR-Egger regressionMR-Egger is not recommended for one-sample MR unless the correlation between the gene-exposure and gene-outcome estimates due to confounding can be kept low, or the variability in instrumental strength is very high
VolcaNoseR – a web app for creating, exploring, labeling and sharing volcano plots
Authors: Goedhart Joachim , Luijsterburg Martijn S. 
Published: May 2020

AbstractComparative genome- and proteome-wide screens yield large amounts of data. To efficiently present such datasets and to simplify the identification of hits, the results are often presented in a type of scatterplot known as a volcano plot, which shows a measure of effect size versus a measure of significance. The data points with the largest effect size and a statistical significance beyond a user-defined threshold are considered as hits. Such hits are usually annotated in the plot by a label with their name. Volcano plots can represent ten thousands of data points, of which typically only a handful is annotated. The information of data that is not annotated is hardly or not accessible. To simplify access to the data and enable its re-use, we have developed an open source and online web tool with R/shiny. The web app is named VolcaNoseR and it can be used to create, explore, label and share volcano plots (https://huygens.science.uva.nl/VolcaNoseR). When the data is stored in an online data repository, the web app can retrieve that data together with user-defined settings to generate a customized, interactive volcano plot. Users can interact with the data, adjust the plot and share their modified plot together with the underlying data. Therefore, VolcaNoseR increases the transparency and re-use of large comparative genome- and proteome-wide datasets.
Mutational processes impact the evolution of anti-EGFR antibody resistance in colorectal cancer
Authors: Woolston Andrew , Barber Louise J , Griffiths Beatrice , Matthews Nik , Rao Sheela , Watkins David , Chau Ian , Starling Naureen , Cunningham David , Gerlinger Marco 
Published: May 2020

SUMMARYAnti-EGFR antibodies such as cetuximab are active againstKRAS/NRASwild-type colorectal cancers (CRC) but acquired resistance invariably evolves. Which mutational mechanisms enable resistance evolution and whether adaptive mutagenesis, a transient cetuximab-induced increase in mutagenesis, contributes in patients is unknown. We investigated this in exome sequencing data of 42 baseline and progression biopsies from cetuximab treated CRCs. Mutation loads did not increase from baseline to progression. Evidence for a contribution of cetuximab-induced mutagenesis was limited. However, the mutational Signature 17 was a key contributer of specificKRAS/NRASandEGFRdriver mutations that are common at acquired resistance. Signature 17 activity before treatment predicted shorter progression free survival. This demonstrates the utility of mutational signatures to predict cancer drug resistance evolution.SIGNIFICANCEDrug resistance evolution occurs ubiquitously in solid tumours during treatment with targeted drugs. Biomarkers that can be assessed prior to treatment to predict the time to resistance evolution and the genetic resistance mechanisms that will evolve have not been described. We identified the mutational Signature 17 as the first candidate biomarker that predicts shorter time to progression and several specificKRAS/NRASandEGFRmutations that will likely evolve in CRCs during cetuximab treatment. Understanding the mutational mechanism underlying Signature 17 may open opportunities to delay resistance acquisition. The potential of mutational signatures to predict resistance to a broader range of drugs in other tumor types should be assessed.
Eyes are essential for magnetoreception in a mammal
Authors: Caspar Kai R. , Moldenhauer Katrin , Moritz Regina E. , Malkemper E. Pascal , Begall Sabine 
Published: May 2020

AbstractSeveral groups of mammals use the Earth’s magnetic field for orientation, but their magnetosensory organ remains unknown. The Ansell’s mole-rat (Fukomys anselli) is a subterranean rodent with innate magnetic orientation behavior. Previous studies proposed that its magnetoreceptors are located in the eye. To test this hypothesis, we assessed magnetic orientation in enucleated mole-rats.Initially, we demonstrate that enucleation of mole-rats does not lead to changes in routine behaviors. We then studied magnetic compass orientation by employing a well-established nest building assay. To ensure that directional responses were based on magnetic parameters, we tested animals under four magnetic field alignments. In line with previous studies, control animals exhibited a significant preference to build nests in magnetic south-east. In contrast, enucleated mole-rats built nests in random magnetic orientations, suggesting an impairment of their magnetic sense. The results provide robust support for the hypothesis that mole-rats perceive magnetic fields with their minute eyes.
Unlocking the Reversal Potential of Solid Supported Membrane Electrophysiology to Determine Transport Stoichiometry
Authors: Thomas Nathan E. , Henzler-Wildman Katherine A. 
Published: May 2020

AbstractTransport stoichiometry provides insight into the mechanism and function of ion-coupled transporters, but measuring transport stoichiometry is time-consuming and technically difficult. With the increasing evidence that many ion-coupled transporters employ multiple transport stoichiometries under different conditions, improved methods to determine transport stoichiometry are required to accurately characterize transporter activity. Reversal potential was previously shown to be a reliable, general method for determining the transport stoichiometry of ion-coupled transporters (Fitzgerald & Mindell, 2017). Here, we develop a new technique for measuring transport stoichiometry with greatly improved throughput using solid supported membrane electrophysiology (SSME). Using this technique, we are able to verify the recent report of a fixed 2:1 stoichiometry for the proton:guanidinium antiporter Gdx. Our SSME method requires only small amounts of transporter and provides a fast, easy, general method for measuring transport stoichiometry, which will facilitate future mechanistic and functional studies of ion-coupled transporters.
PyHIST: A Histological Image Segmentation Tool
Authors: Muñoz-Aguirre Manuel , Ntasis Vasilis F. , Guigó Roderic 
Published: May 2020

AbstractThe development of increasingly sophisticated methods to acquire high resolution images has led to the generation of large collections of biomedical imaging data, including images of tissues and organs. Many of the current machine learning methods that aim to extract biological knowledge from histopathological images require several data preprocessing stages, creating an overhead before the proper analysis. Here we present PyHIST (https://github.com/manuel-munoz-aguirre/PyHIST), an easy-to-use, open source whole slide histological image tissue segmentation and preprocessing tool aimed at data preparation for machine learning applications.
From sea surface to seafloor: a benthic allochthonous eDNA survey for the abyssal ocean
Authors: Laroche Olivier , Kersten Oliver , Smith Craig R. , Goetze Erica 
Published: May 2020

AbstractDiverse and remote deep-sea communities are critically under-sampled and increasingly threatened by anthropogenic impacts. Environmental DNA (eDNA) metabarcoding could facilitate rapid and comprehensive biotic surveys in the deep ocean, yet many aspects of the sources and distribution of eDNA in the deep sea are still poorly understood. In order to examine the influence of the water column on benthic eDNA surveys in regions targeted for deep-sea polymetallic nodule mining, we investigated the occurrence of pelagic eDNA across: (1) two different deep-sea habitat types, abyssal plains and seamounts, (2) benthic sample types, including nodules, sediment, and seawater within the benthic boundary layer (BBL), and (3) sediment depth horizons (0-2 cm, 3-5 cm). Little difference was observed between seamounts and the adjacent abyssal plains in the proportion of legacy pelagic eDNA sampled in the benthos, despite an > 1000 m depth difference for these habitats. In terms of both reads and amplicon sequence variants (ASVs), pelagic eDNA was minimal within sediment and nodule samples (< 2%), and is unlikely to affect benthic surveys that monitor resident organisms at the deep seafloor. However, pelagic eDNA was substantial within the BBL (up to 13 % ASVs, 86% reads), deriving both from the high biomass upper ocean as well as deep pelagic residents. While most pelagic eDNA found in sediments and on nodules could be sourced from the epipelagic for metazoans, protist legacy eDNA sampled on these substrates appeared to originate across a range of depths in the water column. Some evidence of eDNA degradation across a vertical sediment profile was observed for protists, with higher diversity in the 0-2 cm layer and a significantly lower proportion of legacy pelagic eDNA in deeper sediments (3-5 cm). Study-wide, our estimated metazoan sampling coverage ranged from 40% to 74%, despite relatively large sample size. Future deep-sea eDNA surveys should examine oceanographic influences on eDNA transport and residence times, consider habitat heterogeneity at a range of spatial scales in the abyss, and aim to process large amounts of material per sample (with replication) in order to increase the sampling coverage in these diverse deep ocean communities.
Recurrent evolution of vertebrate transcription factors by transposase capture
Authors: Cosby Rachel L. , Judd Julius , Zhang Ruiling , Zhong Alan , Garry Nathaniel , Pritham Ellen J. , Feschotte Cedric 
Published: May 2020

AbstractHow genes with novel cellular functions evolve is a central biological question. Exon shuffling is one mechanism to assemble new protein architectures. Here we show that DNA transposons, which are mobile and pervasive in genomes, have provided a recurrent supply of exons and splice sites to assemble protein-coding genes in vertebrates via exon-shuffling. We find that transposase domains have been captured, primarily via alternative splicing, to form new fusion proteins at least 94 times independently over ∼350 million years of tetrapod evolution. Evolution favors fusion of transposase DNA-binding domains to host regulatory domains, especially the Krüppel-associated Box (KRAB), suggesting transposase capture frequently yields new transcriptional repressors. We show that four independently evolved KRAB-transposase fusion proteins repress gene expression in a sequence-specific fashion. Genetic knockout and rescue of the bat-specificKRABINERfusion gene in cells demonstrates that it binds its cognate transposons genome-wide and controls a vast network of genes andcis-regulatory elements. These results illustrate a powerful mechanism by which a transcription factor and its dispersed binding sites emerge at once from a transposon family.One Sentence SummaryHost-transposase fusion generates novel cellular genes, including deeply conserved and lineage specific transcription factors.
A gas-and-brake mechanism of bHLH proteins modulates shade avoidance inArabidopsis thaliana
Authors: Buti Sara , Pantazopoulou Chrysoula K. , Hoogers Valérie , van Gelderen Kasper , Reinen Emilie , Pierik Ronald 
Published: May 2020

ABSTRACTPlants detect proximity of competitors through reduction in the ratio between red and far red light triggering the shade avoidance syndrome, which includes accelerated shoot elongation and early flowering. Shade avoidance is regulated through PHYTOCHROME INTERACTING FACTORs (PIFs), a group of bHLH transcription factors. Another (b)HLH protein, KIDARI (KDR), which is non-DNA-binding, was identified in de-etiolation studies and proposed to interact with LONG HYPOCOTYL IN FAR-RED 1 (HFR1), a (b)HLH protein that inhibits shade avoidance. Here we establish novel roles of KDR in regulating shade avoidance and investigate how KDR regulates the shade avoidance network. We show that KDR is a positive regulator of shade avoidance and interacts with several negative growth regulators. We identify novel interactors using a combination of yeast two-hybrid screening and dedicated confirmations with bimolecular fluorescence complementation. We demonstrate that KDR is translocated primarily to the nucleus when coexpressed with these newly discovered interactors. A genetic approach confirmed that several of these novel interactions are indeed functional to shade avoidance inArabidopsis thaliana, whereas we propose that KDR does not interact with HFR1 to regulate shade avoidance. Based on this, we propose that shade avoidance is regulated by a three-layered gas-and-brake mechanism of bHLH protein interactions, adding an additional layer of complexity to what was previously known.One-sentence summaryKIDARI is a positive regulator of shade avoidance and part of a three-layer network of bHLH transcription factor interactions.
Host and environmental determinants of microbial community structure in the marine phyllosphere
Authors: Vogel Margaret A. , Mason Olivia U. , Miller Thomas E. 
Published: May 2020

AbstractAlthough seagrasses are economically and ecologically critical species, little is known about their blade surface microbial communities and how these communities relate to the plant host. To determine microbial community composition and diversity on seagrass blade surfaces and in the surrounding seawater,16S rRNA gene sequencing (iTag) was used for samples collected at five sites along a gradient of freshwater input in the northern Gulf of Mexico on three separate sampling dates. Additionally, seagrass surveys were performed and environmental parameters were measured to characterize host characteristics and the abiotic conditions at each site. Results showed thatThalassia testudinum(turtle grass) blades hosted unique microbial communities that were distinct in composition and diversity from the water column. Additionally, results suggested that environmental conditions, including water depth, salinity, and temperature, were the major driver of community structure as blade surface microbial communities varied among sites and over sampling dates. Host condition may be a secondary driver of community structure as compositional changes were also correlated with host characteristics, including leaf growth rates and blade nutrient composition, Additionally, 21 microorganisms from five phyla (Cyanobacteria, Proteobacteria, Planctomycetes, Chloroflexi, and Bacteroidetes) were present in all blade surface samples and may represent a core community forT. testudinum. Members of this core community may have ecological importance for determining community structure or in performing key community functions. This study provides new insights and understanding of the processes that influence the structure of marine phyllosphere communities, how these microbial communities relate to their host, and their role as a part of the seagrass holobiont, which is an important contribution given the current decline of seagrass coverage worldwide.
Validation of a PNA clamping method for reducing host DNA amplification and increasing eukaryotic diversity in rhizosphere microbiome studies
Authors: Taerum Stephen J. , Steven Blaire , Gage Daniel J. , Triplett Lindsay R. 
Published: May 2020

AbstractProtists and microscopic animals are important but poorly understood determinants of plant health. Plant-associated eukaryotes could be surveyed by high-throughput sequencing of 18S ribosomal RNA (rRNA) genes, but the abundance of plant DNA in rhizosphere samples makes 18S rRNA gene amplification with universal primers unfeasible. Here we applied a pipeline to generate peptide nucleic acid (PNA) clamps to suppress the amplification of plant host DNA during 18S rRNA gene library preparation. We designed a PNA clamp, PoacV9_01, specific to the V9 region of the 18S rRNA gene for plants in the family Poaceae. PoacV9_01 suppressed the amplification of five species of grain crops in quantitative PCR reactions. In an 18S rRNA gene sequencing survey of the rhizosphere of maize, PoacV9_01 reduced the relative abundance of plant reads from 65% to 0.6%, while drastically increasing the number and diversity of animal, fungal, and protist reads detected. Thus, PoacV9_01 can be used to facilitate the study of eukaryotes present in grass phytobiomes. In addition, the pipeline developed here can be used to develop PNA clamps that target other plant species.