bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatially Resolved Estimation of Metabolic Oxygen Consumption From Optical Measurements in Cortex
Authors: Sætra Marte J. , Solbrå Andreas V. , Devor Anna , Dale Anders M. , Einevoll Gaute T. 
Published: November 2019

AbstractThe cerebral metabolic rate of oxygen (CMRO2) is an important indicator of brain function and pathology. Knowledge about its magnitude is also required for proper interpretation of the blood oxygenation level dependent (BOLD) signal measured with functional MRI (fMRI). The ability to measure CMRO2 with high spatial and temporal accuracy is thus highly desired. Traditionally the estimation of CMRO2 has been pursued with somewhat indirect approaches combining several different types of measurements with mathematical modeling of the underlying physiological processes. Given the numerous assumptions involved, questions have thus been raised about the accuracy of the resulting CMRO2 estimates. The recent ability to measure the level of oxygen (pO2) in cortex with high spatial resolution in in vivo conditions has provided a more direct way for estimating CMRO2. CMRO2 and pO2 are related via the Poisson partial differential equation. Assuming a constant CMRO2 and cylindrical symmetry around the blood vessel providing the oxygen, the so-called Krogh-Erlang formula relating the spatial pO2 profile to a constant CMRO2 value can be derived. This Krogh-Erlang formula has previously been used to estimate the average CMRO2 close to cortical blood vessels based on pO2 measurements in rats.Here we introduce a new method, the Laplace method, to provide spatial maps of CMRO2 based on the same measured pO2 profiles. The method has two key steps: First the measured pO2 profiles are spatially smoothed to reduce effects of spatial noise in the measurements. Next, the Laplace operator (a double spatial derivative) in two spatial dimensions is applied on the smoothed pO2 profiles to obtain spatially resolved CMRO2 estimates. The smoothing introduces a bias, and a balance must be found where the effects of the noise are sufficiently reduced without introducing too much bias. In this model-based study we explore this balance in situations where the ground truth, that is, spatial profile of CMRO2 is preset and thus known, and the corresponding pO2 profiles are found by solving the Poisson equation, either numerically or by taking advantage of the Krogh-Erlang formula. MATLAB code for using the Laplace method is provided.
Data architecture for a large-scale neuroscience collaboration
Authors:   The International Brain Laboratory, Bonacchi Niccolò , Chapuis Gaelle , Churchland Anne , Harris Kenneth D. , Hunter Max , Rossant Cyrille , Sasaki Maho , Shen Shan , Steinmetz Nicholas A. , Walker Edgar Y. , Winter Olivier , Wells Miles 
Published: November 2019

AbstractEffective data management is a major challenge for neuroscience labs, and even greater for collaborative projects. In the International Brain laboratory (IBL), ten experimental labs spanning 7 geographically distributed sites measure neural activity across the brains of mice making perceptual decisions. Here, we report a novel, modular architecture that allows users to contribute, access, and analyze data across this collaboration. Users contribute data using a web-based electronic lab notebook (Alyx), which automatically registers recorded data files and uploads them to a central server. Users access data with a lightweight interface, the Open Neurophysiology Environment (ONE), which searches data from all labs and loads it into MATLAB or Python. To analyze data, we have developed pipelines based on DataJoint, which automatically populate a website displaying a graphical summary of results to date. This architecture provides a new framework to contribute, access and analyze data, surmounting many challenges currently faced by neuroscientists.
Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis
Authors: Yang Jing , McGovern Amanda , Martin Paul , Duffus Kate , Ge Xiangyu , Zarrineh Peyman , Morris Andrew P , Adamson Antony , Fraser Peter , Rattray Magnus , Eyre Stephen 
Published: November 2019

AbstractGenome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T-cells over 24 hours, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T-cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.
A mathematical dissection of the adaptation of cell populations to fluctuating oxygen levels
Authors: Ardaševa Aleksandra , Gatenby Robert A , Anderson Alexander R A , Byrne Helen M , Maini Philip K , Lorenzi Tommaso 
Published: November 2019

AbstractThe disordered network of blood vessels that arises from tumour angiogenesis results in variations in the delivery of oxygen into the tumour tissue. This brings about regions of chronic hypoxia (i.e. sustained low oxygen levels) and regions with alternating phases of low and relatively higher oxygen levels within vascularised tumours, and makes it necessary for cancer cells to adapt to fluctuating environmental conditions. We use a phenotype-structured model to dissect the evolutionary dynamics of cell populations exposed to fluctuating oxygen levels. In this model, the phenotypic state of every cell is described by a continuous variable that provides a simple representation of its metabolic phenotype, ranging from fully oxidative to fully glycolytic, and cells are grouped into two competing populations that undergo heritable, spontaneous phenotypic variations at different rates. Model simulations indicate that, depending on the rate at which oxygen is consumed by the cells, nonlinear dynamic interactions between cells and oxygen can stimulate chronic hypoxia and cycling hypoxia. Moreover, the model supports the idea that under chronic-hypoxic conditions lower rates of phenotypic variation lead to a competitive advantage, whereas higher rates of phenotypic variation can confer a competitive advantage under cycling-hypoxic conditions. In the latter case, the numerical results obtained show that bet-hedging evolutionary strategies, whereby cells switch between oxidative and glycolytic phenotypes, can spontaneously emerge. We explain how these results can shed light on the evolutionary process that may underpin the emergence of phenotypic heterogeneity in vascularised tumours.
Mitochondria tether to Focal Adhesions during cell migration and regulate their size
Authors: Daniel Redaet , Mengeta Abebech , Bilodeau Patricia , Lee Jonathan M 
Published: November 2019

AbstractMitochondria are the key generators of ATP in a cell. Visually, they are highly dynamic organelles that undergo cellular fission and fusion events in response to changing cellular energy requirements. Mitochondria are now emerging as regulators of mammalian cell motility. Here we show that mitochondria infiltrate the leading edge of NIH3T3 fibroblasts during migration. At the leading edge, we find that mitochondria move to and tether to Focal Adhesions (FA). FA regulate cell migration by coupling the cytoskeleton to the Extracellular Matrix through integrin receptors. Importantly, we find that inhibition of mitochondrial ATP generation concomitantly inhibits FA size. This suggests that mitochondrial energy production regulates migration through FA control.
Biological sex and age shape melanoma tumour evolution
Authors: Lotz Martin , Furney Simon J. , Virós Amaya 
Published: November 2019

AbstractMany cancer types display sex and age disparity in incidence and outcome. Here, we establish a mathematical approach using cancer mutational data to analyze how sex and age shape the tumour genome. We model how age-related (clock-like) somatic mutations that arise during cell division, and extrinsic (environmental) mutations accumulate in cancer genomes. As a proof-of-concept, we apply our approach to melanoma, a cancer driven by cell-intrinsic age-related mutations and extrinsic ultraviolet light-induced mutations, and show these mutation types differ in magnitude, chronology and by sex in the distinct molecular melanoma subtypes.Our model confirms age and sex are determinants of cellular mutation rate, shaping the final mutation composition. We show mathematically for the first time how, similar to non-cancer tissues, melanoma genomes reflect a decline in cell division during ageing. We find clock-like mutations strongly correlate with the acquisition of ultraviolet light-induced mutations, but critically, males present a higher number and rate of cell division-linked mutations. These data indicate the contribution of environmental damage to melanoma likely extends beyond genetic damage to affect cell division.
MIRAGE: a Bayesian rare variant association analysis method incorporating functional information of variants
Authors: Han Shengtong , Sun Xiaotong , Sloofman Laura , Satterstrom F. Kyle , Wang Gao , Liang Lifan , Knoblauch Nicholas , Zhao Siming , Liu Yuwen , Sheng Wenhui , Nguyen Hoang T. , He Xin 
Published: November 2019

AbstractMany biobanks and consortiums have generated large whole-exome and whole-genome sequencing datasets, making it possible to perform rare variant association studies. Compared to common variants, rare variants tend to have larger effect sizes and generally have much lower linkage disequilibrium (LD), making it easier to identify causal variants. These potential benefits make association analysis with rare variants a priority for human genetics researchers. Because of the low frequencies of these variants, however, the power of single-variant association is often low. To improve the power, numerous methods have been developed to aggregate information of all variants of a gene to better identify risk genes. These gene-based methods, however, often make unrealistic assumptions, e.g. all rare variants in a risk gene have the same effects. In practice, current gene-based analysis methods often fail to show any advantage over simple single-variant analysis. In this work, we develop a Bayesian method: MIxture model based Rare variant Analysis on GEnes (MIRAGE). MIRAGE captures the heterogeneity of variant effects by treating all variants of a gene as a mixture of risk and non-risk variants, and models the prior probabilities of being risk variants as function of external information of variants, such as allele frequencies and predicted deleterious effects. MIRAGE uses an empirical Bayes approach, combining information across genes to estimate these prior probabilities. We demonstrate in both simulations and analysis of an exome-sequencing dataset of Autism, that MIRAGE significantly outperforms current methods for rare variant analysis. The top genes identified by MIRAGE are highly enriched with known or plausible Autism risk genes. Our results highlight several novel Autism genes. MIRAGE is available athttps://xinhe-lab.github.io/mirage.
Bioengineering a novel 3D in-vitro model to recreate physiological oxygen levels and tumor-immune interactions
Authors: Bhattacharya Somshuvra , Calar Kristin , Evans Claire , Petrasko Mark , de la Puente Pilar 
Published: November 2019

ABSTRACTOxygen deprivation within tumors is one of the most prevalent causes of resilient cancer cell survival and increased immune evasion in breast cancer (BCa). Current in vitro models do not adequately mimic physiological oxygen levels relevant to breast tissue and its tumor-immune interactions. Here, we propose an approach to engineer a three-dimensional (3D) model (named 3D engineered oxygen, 3D-O) that supports growth of BCa cells and generates physio- and pathophysiological oxygen levels. Low oxygen-induced changes within the 3D-O model supported known tumor hypoxia characteristics such as reduced BCa cell proliferation, increased extracellular matrix protein expression, increased extracellular vesicle secretion and enhanced immune surface marker expression on BCa cells. We further demonstrated that low oxygen-induced changes mimicked tumor-immune interactions leading to immune evasion mechanisms. CD8+ T cell infiltration was significantly impaired under pathophysiological oxygen levels and we were able to establish that hypoxia inhibition re-sensitize BCa cells to cytotoxic CD8+ T cells. Therefore, our novel 3D-O model could serve as a promising platform for the evaluation of immunological events and as a drug-screening platform tool to overcome hypoxia-driven immune evasion.
Gradual replacement of wild bees by honeybees in flowers of the Mediterranean Basin over the last 50 years
Authors: Herrera Carlos M. 
Published: November 2019

AbstractEvidence for pollinator declines largely originates from mid-latitude regions in North America and Europe. Geographical heterogeneity in pollinator trends combined with geographical biases in pollinator studies, can produce distorted extrapolations and limit understanding of pollinator responses to environmental changes. In contrast to the declines experienced in some well-investigated European and North American regions, honeybees seem to have increased recently in some areas of the Mediterranean Basin. Since honeybees can impact negatively on wild bees, it was hypothesized that a biome-wide alteration in bee pollinator assemblages may be underway in the Mediterranean Basin involving a reduction in the importance of wild bees as pollinators. This hypothesis was tested using published quantitative data on bee pollinators of wild and cultivated plants from studies conducted between 1963-2017 in 13 circum-Mediterranean countries. Honeybee colonies increased exponentially and wild bees were gradually replaced by honeybees in flowers of wild and cultivated plants. Proportion of wild bees at flowers quadruplicated that of honeybees at the beginning of the period, the proportions of both groups becoming roughly similar fifty years later. The Mediterranean Basin is a world biodiversity hotspot for wild bees and wild bee-pollinated plants, and the ubiquitous rise of honeybees to dominance as pollinators could in the long run undermine the diversity of plants and wild bees in the region.
Differential modes of orphan subunit recognition for the WRB/CAML complex
Authors: Inglis Alison J. , Page Katharine R. , Guna Alina , Voorhees Rebecca M. 
Published: November 2019

AbstractA large proportion of membrane proteins must be assembled into oligomeric complexes for function. How this process occurs is poorly understood, but it is clear that complex assembly must be tightly regulated to avoid accumulation of orphan subunits with potential cytotoxic effects. We interrogated assembly in mammalian cells using a model system of the WRB/CAML complex: an essential insertase for tail-anchored proteins in the endoplasmic reticulum (ER). Our data suggests that the stability of each subunit is differentially regulated. In WRB’s absence, CAML folds incorrectly, causing aberrant exposure of a hydrophobic transmembrane domain to the cytosol. When present, WRB can post-translationally correct the topology of CAML both in vitro and in cells. In contrast, WRB can independently fold correctly, but is still degraded in the absence of CAML. We therefore propose at least two distinct regulatory pathways for the surveillance of orphan subunits during complex assembly in the mammalian ER.
FtsK in motion reveals its mechanism for double-stranded DNA translocation
Authors: Jean Nicolas L. , Rutherford Trevor J. , Löwe Jan 
Published: November 2019

AbstractFtsK protein contains a fast DNA motor involved in bacterial chromosome dimer resolution. To understand how FtsK moves DNA, we solved the 3.6 Å resolution cryo-EM structure of the motor domain of FtsK while translocating double-stranded DNA. Each subunit of the hexameric ring adopts a unique conformation and one of three nucleotide states. Two DNA-binding loops within four subunits form a pair of spiral staircases within the ring, interacting with the two DNA strands. This suggests that simultaneous conformational changes in all ATPase domains at each catalytic step generate movement through a mechanism related to filament treadmilling. While the ring is only rotating around the DNA slowly, it is instead the conformational states that rotate around the ring as the DNA substrate is pushed through.
Genomic characterization and curation of UCEs improves species tree reconstruction
Authors: Van Dam Matthew H. , Henderson James B. , Esposito Lauren , Trautwein Michelle 
Published: November 2019

ABSTRACTUltraconserved genomic elements (UCEs), are generally treated as independent loci in phylogenetic analyses. The identification pipeline for UCE probes is agnostic to genetic identity, only selecting loci that are highly conserved, single copy, without repeats, and of a particular length. Here we characterized UCEs from 12 phylogenomic studies across the animal tree of life, from birds to marine invertebrates. We found that within vertebrate lineages, UCEs are mostly intronic and intergenic, while in invertebrates, the majority are in exons. We then curated 4 different sets of UCE markers by genomic category from 5 different studies including; birds, mammals, fish, Hymenoptera (ants, wasps and bees) and Coleoptera (beetles). Of genes captured by UCEs, we find that many are represented by 2 or more UCEs, corresponding to non-overlapping segments of a single gene. We considered these UCEs to be non-independent, merged all UCEs that belonged to a particular gene, constructed gene and species trees, and then evaluated the subsequent effect of merging co-genic UCEs on gene and species tree reconstruction. Average bootstrap support for merged UCE gene trees were significantly improved across all datasets. Increased loci length appears to drive this increase in bootstrap support. Additionally, we found that gene trees generated from merged UCEs were more accurate than those generated by unmerged and randomly merged UCEs, based on our simulation study. This modest degree of UCE characterization and curation impacts downstream analyses and demonstrates the advantages of incorporating basic genomic characterizations into phylogenomic analyses.
A Plausible Accelerating Function of Intermediate States in Cancer Metastasis
Authors: Goetz Hanah , Melendez-Alvarez Juan R. , Chen Luonan , Tian Xiao-Jun 
Published: November 2019

AbstractEpithelial-to-mesenchymal transition (EMT) is a fundamental cellular process and plays an essential role in development, tissue regeneration, and cancer metastasis. Interestingly, EMT is not a binary process but instead proceeds with multiple partial intermediate states. However, the functions of these intermediate states are not fully understood. Here, we focus on a general question about how the number of partial EMT states affects cell transformation. First, by fitting a hidden Markov model of EMT with experimental data, we propose a statistical mechanism for EMT in which many unobservable microstates may exist within one of the observable macrostates. Furthermore, we find that increasing the number of intermediate states can accelerate the EMT process and that adding parallel paths or transition layers accelerates the process even further. Last, a stabilized intermediate state traps cells in one partial EMT state. This work advances our understanding of the dynamics and functions of EMT plasticity during cancer metastasis.
Evaluation of haplotype callers for next-generation sequencing of viruses
Authors: Eliseev Anton , Gibson Keylie M. , Avdeyev Pavel , Novik Dmitry , Bendall Matthew L. , Pérez-Losada Marcos , Alexeev Nikita , Crandall Keith A. 
Published: November 2019

AbstractCurrently, the standard practice for assembling next-generation sequencing (NGS) reads of viral genomes is to summarize thousands of individual short reads into a single consensus sequence, thus confounding useful intra-host diversity information for molecular phylodynamic inference. It is hypothesized that a few viral strains may dominate the intra-host genetic diversity with a variety of lower frequency strains comprising the rest of the population. Several software tools currently exist to convert NGS sequence variants into haplotypes. However, previous studies suggest that current approaches of haplotype reconstruction greatly underestimate intra-host diversity. Here, we tested twelve NGS haplotype reconstruction methods using viral populations simulated under realistic evolutionary dynamics. Parameters for the simulated data spanned known fast evolving viruses (e.g., HIV-1) diversity estimates to test the limits of the haplotype reconstruction methods and ensured coverage of predicted intra-host viral diversity levels. Using those parameters, we simulated HIV-1 viral populations of 216-1,185 haplotypes per host at a frequency <7%. All twelve investigated haplotype callers showed variable performance and produced drastically different results that were mainly driven by differences in mutation rate and, to a lesser extent, in effective population size. Most methods were able to accurately reconstruct haplotypes when genetic diversity was low. However, under higher levels of diversity (e.g., those seen intra-host HIV-1 infections), haplotype reconstruction accuracy was highly variable and, on average, poor. High diversity levels led to severe underestimation of, with a few tools greatly overestimating, the true number of haplotypes. PredictHaplo and PEHaplo produced estimates close to the true number of haplotypes, although their haplotype reconstruction accuracy was worse than that of the other ten tools. We conclude that haplotype reconstruction from NGS short reads is unreliable due to high genetic diversity of fast-evolving viruses. Local haplotype reconstruction of longer reads to phase variants may provide a more reliable estimation of viral variants within a population.HighlightsHaplotype callers for NGS data vary greatly in their performance.Haplotype callers performance is mainly determined by mutation rate.Haplotype callers performance is less sensitive to effective population size.Most haplotype callers perform well with low diversity and poorly with high diversity.PredictHaplo performs best if genetic diversity is in the range of HIV diversity.
Fbxo45 binds SPRY motifs in the extracellular domain of N-cadherin and regulates neuron migration during brain development
Authors: Na Youn , Calvo-Jiménez Elisa , Kon Elif , Cao Hong , Jossin Yves , Cooper Jonathan A. 
Published: November 2019

ABSTRACTSeveral events during normal development of the mammalian neocortex depend on N-cadherin, including the radial migration of immature projection neurons into the cortical plate. Remarkably, radial migration requires the N-cadherin extracellular domain but not N-cadherin-dependent homophilic cell-cell adhesion, suggesting that other N-cadherin-binding proteins may be involved. We used proximity ligation and affinity purification proteomics to identify N-cadherin-binding proteins. Both screens detected MycBP2 and SPRY-domain protein Fbxo45, two components of an intracellular E3 ubiquitin ligase. Fbxo45 appears to be secreted by a non-classical mechanism, not involving a signal peptide and not requiring endoplasmic reticulum to Golgi transport. Fbxo45 binding requires N-cadherin SPRY motifs that are not involved in cell-cell adhesion. SPRY-mutant N-cadherin does not support radial migration in vivo. Radial migration was similarly inhibited when Fbxo45 expression was suppressed. The results suggest that projection neuron migration requires both Fbxo45 and binding of Fbxo45 or another protein to SPRY motifs in the extracellular domain of N-cadherin.