bluuebunny/crossref_metadata_2025_split huggingface dataset:
Growth-driven displacement of protein aggregates along the cell length ensures partitioning to both daughter cells inCaulobacter crescentus
Authors: Schramm Frederic D. , Schroeder Kristen , Alvelid Jonatan , Testa Ilaria , Jonas Kristina 
Published: October 2018

AbstractAll living cells must deal with protein aggregation, which can occur as a result of experiencing stress. In the bacteriaEscherichia coliandMycobacterium smegmatis, aggregates collect at the cell poles and are retained over consecutive cell divisions only in the daughter cell that inherits the old pole, resulting in aggregation-free progeny within a few generations. Here we have studied thein vivokinetics of aggregate formation and clearance following heat and antibiotic stress inCaulobacter crescentus, which divides by a pre-programmed asymmetric cell cycle. Unexpectedly, we find that aggregates do not preferentially collect at the cell poles, but form as multiple distributed foci throughout the cell volume. Time-lapse microscopy revealed that under moderate stress, the majority of protein aggregates are short-lived and rapidly dissolved by the major chaperone DnaK and the disaggregase ClpB. Severe stress or genetic perturbation of the protein quality machinery results in long-lived protein aggregates, which individual cells can only clear by passing on to their progeny. Importantly, these persistent aggregates are neither collected at the old pole over multiple generations nor inherited exclusively by the old pole-inheriting stalked cell, but instead are partitioned between both daughter cells during successive division events in the same ratio. Our data indicate that this symmetric mode of aggregate inheritance is driven by the elongation and division of the growing mother cell. In conclusion, our study revealed a new pattern of aggregate inheritance in bacteria.
FoxM1 drives proximal tubule proliferation during repair from acute kidney injury
Authors: Chang-Panesso Monica , Kadyrov Farid F. , Lalli Matthew , Wu Haojia , Ikeda Shiyo , Kobayashi Akio , Humphreys Benjamin D. 
Published: October 2018

AbstractThe proximal tubule has a remarkable capacity for repair after acute injury but the cellular lineage and molecular mechanisms underlying this repair response have been poorly characterized. Here, we developed a Kim-1-GFPCreERt2knockin mouse line (Kim-1-GCE), performed genetic lineage analysis after injury and measured the cellular transcriptome of proximal tubule during repair. Acutely injured genetically labeled clones co-expressed Kim-1, Vimentin, Sox9 and Ki67, indicating a dedifferentiated and proliferative state. Clonal analysis revealed clonal expansion of Kim-1+ cells, indicating that acutely injured, dedifferentiated proximal tubule cells account for repair rather than a fixed tubular progenitor. Translational profiling during injury and repair revealed signatures of both successful and unsuccessful maladaptive repair. The transcription factor FoxM1 was induced early in injury, was required for epithelial proliferation, and was dependent on epidermal growth factor receptor (EGFR) stimulation. In conclusion, dedifferentiated proximal tubule cells effect proximal tubule repair and we reveal a novel EGFR-FoxM1-dependent signaling pathway that drives proliferative repair after injury.
SNAPS: A toolkit for studying cell surface shedding of diverse transmembrane receptors
Authors: Hayward Amanda N. , Aird Eric J. , Gordon Wendy R. 
Published: October 2018

SummaryProteolysis of transmembrane receptors is a critical cellular communication mechanism dysregulated in many diseases, yet decoding proteolytic regulation mechanisms of the estimated 400 receptors shed from the cell surface has been hindered by difficulties in controlling stimuli and unknown fates of cleavage products. Notch proteolytic regulation is a notable exception, where decades of study have revealed that intercellular forces drive exposure of a cryptic protease site within a juxtamembrane “proteolytic switch” domain to activate transcriptional programs inside the cell. Thus, we created a Synthetic Notch Assay for Proteolytic Switches (SNAPS) that exploits the modularity and unequivocal input/response of Notch proteolysis to screen surface receptors for other putative proteolytic switches. Here, we identify several new proteolytic switches among receptors with structural homology to Notch. We demonstrate that SNAPS can detect shedding in chimeras of diverse cell surface receptors, leading to new, testable hypotheses. Finally, we establish that the assay can be used to measure modulation of proteolysis by potential therapeutics.
RegTools: Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer
Authors: Cotto Kelsy C. , Feng Yang-Yang , Ramu Avinash , Richters Megan , Freshour Sharon L. , Skidmore Zachary L. , Xia Huiming , McMichael Joshua F. , Kunisaki Jason , Campbell Katie M. , Chen Timothy Hung-Po , Rozycki Emily B. , Adkins Douglas , Devarakonda Siddhartha , Sankararaman Sumithra , Lin Yiing , Chapman William C. , Maher Christopher A. , Arora Vivek , Dunn Gavin P. , Uppaluri Ravindra , Govindan Ramaswamy , Griffith Obi L. , Griffith Malachi 
Published: October 2018

AbstractSomatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools (www.regtools.org), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. RegTools was applied to over 9,000 tumor samples with both tumor DNA and RNA sequence data. We discovered 235,778 events where a splice-associated variant significantly increased the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotated them with the Variant Effect Predictor (VEP), SpliceAI, and Genotype-Tissue Expression (GTEx) junction counts and compared our results to other tools that integrate genomic and transcriptomic data. While many events were corroborated by the aforementioned tools, the flexibility of RegTools also allowed us to identify novel splice-associated variants and previously unreported patterns of splicing disruption in known cancer drivers, such asTP53, CDKN2A, andB2M, as well as in genes not previously considered cancer-relevant.
Exploratory Gene Ontology Analysis with Interactive Visualization
Authors: Zhu Junjie , Zhao Qian , Katsevich Eugene , Sabatti Chiara 
Published: October 2018

AbstractThe Gene Ontology (GO) is a central resource for functional-genomics research. Scientists rely on the functional annotations in the GO for hypothesis generation and couple it with high-throughput biological data to enhance interpretation of results. At the same time, the sheer number of concepts (>30,000) and relationships (>70,000) presents a challenge: it can be difficult to draw a comprehensive picture of how certain concepts of interest might relate with the rest of the ontology structure. Here we present new visualization strategies to facilitate the exploration and use of the information in the GO. We rely on novel graphical display and software architecture that allow significant interaction. To illustrate the potential of our strategies, we provide examples from high-throughput genomic analyses, including chromatin immunoprecipitation experiments and genome-wide association studies. The scientist can also use our visualizations to identify gene sets that likely experience coordinated changes in their expression and use them to simulate biologically-grounded single cell RNA sequencing data, or conduct power studies for differential gene expression studies using our built-in pipeline. Our software and documentation are available athttp://aegis.stanford.edu.
Trait evolution and historical biogeography shape assemblages of annual killifish
Authors: Helmstetter Andrew J. , Van Dooren Tom J. M. , Papadopulos Alexander S. T. , Igea Javier , Leroi Armand M. , Savolainen Vincent 
Published: October 2018

ABSTRACTReconstructions of evolutionary and historical biogeographic processes can improve our understanding of how species ssemblages developed and permit inference of ecological drivers affecting coexistence. We explore this approach inAustrolebias, a genus of annual fishes possessing a wide range of body sizes. Regional assemblages composed of different species with similar size distributions are found in four areas of eastern South America. Using phylogenetic trees, species distribution models and size data we show how trait evolution and historical biogeography have affected the composition of species assemblages. We extend age-range correlations to improve estimates of local historical biogeography. We find that size variation principally arose in a single area and infer that ecological interactions drove size divergence. This large-size lineage spread to two other areas. One of these assemblages was likely shaped by adaptation to a new environment, but this was not associated with additional size divergence. We found only weak evidence that environmental filtering has been important in the construction of the remaining assemblage with the smallest range of sizes. The repeated assemblage structures were the result of different evolutionary and historical processes. Our approach sheds light on how species assemblages were built when typical clustering approaches may fall short.
Establishing a causal role for medial prefrontal cortex in reality monitoring
Authors: Subramaniam Karuna , Kothare Hardik , B. Hinkley Leighton , Tarapore Phiroz , S. Nagarajan Srikantan 
Published: October 2018

AbstractReality monitoring is defined as the ability to distinguish internally self-generated information from externally-derived information. Functional imaging studies have consistently found that the medial prefrontal cortex (mPFC) is a key brain region subserving reality monitoring. The aim of this study was to determine a causal role for mPFC in reality monitoring using navigated repetitive transcranial magnetic stimulation (nrTMS). In a subject-blinded sham-controlled crossover design, healthy individuals received either active or sham nrTMS targeting mPFC. Active modulation of mPFC using nrTMS at a frequency of 10 Hz, significantly improved identification of both self-generated and externally-derived information during reality monitoring, when compared to sham or baseline. Targeted excitatory modulation of mPFC also improved positive mood ratings, reduced negative mood ratings and increased overall alertness/arousal. These results establish optimal nrTMS dosing parameters that maximized tolerability/comfort and induced significant neuromodulatory effects in the mPFC target. Importantly, this is a proof-of-concept study that establishes the mPFC as a novel brain target that can be stimulated with nrTMS to causally impact both mood and higher-order reality monitoring.
Integrated analysis of genomics, longitudinal metabolomics, and Alzheimer’s risk factors among 1,111 cohort participants
Authors: Darst Burcu F. , Lu Qiongshi , Johnson Sterling C. , Engelman Corinne D. 
Published: October 2018

AbstractAlthough Alzheimer’s disease (AD) is highly heritable, genetic variants known to be associated with AD only explain a small proportion of its heritability. Genetic factors may only convey disease risk in individuals with certain environmental exposures, suggesting that a multi-omics approach could reveal underlying mechanisms contributing to complex traits, such as AD. We developed an integrated network to investigate relationships between metabolomics, genomics, and AD risk factors using Wisconsin Registry for Alzheimer’s Prevention participants. Analyses included 1,111 non-Hispanic Caucasian participants with whole blood expression for 11,376 genes (imputed from dense genome-wide genotyping), 1,097 fasting plasma metabolites, and 17 AD risk factors. A subset of 155 individuals also had 364 fasting cerebral spinal fluid (CSF) metabolites. After adjusting each of these 12,854 variables for potential confounders, we developed an undirected graphical network, representing all significant pairwise correlations upon adjusting for multiple testing. There were many instances of genes being indirectly linked to AD risk factors through metabolites, suggesting that genes may influence AD risk through particular metabolites. Follow-up analyses suggested that glycine mediates the relationship between CPS1 and measures of cardiovascular and diabetes risk, including body mass index, waist-hip ratio, inflammation, and insulin resistance. Further, 38 CSF metabolites explained more than 60% of the variance of CSF levels of tau, a detrimental protein that accumulates in the brain of AD patients and is necessary for its diagnosis. These results further our understanding of underlying mechanisms contributing to AD risk while demonstrating the utility of generating and integrating multiple omics data types.
Object boundary detection in natural images may depend on ‘incitatory’ cell-cell interactions
Authors: Mel Gabriel C. , Ramachandra Chaithanya A. , Mel Bartlett W. 
Published: October 2018

AbstractDetecting object boundaries is crucial for recognition, but how the process unfolds in visual cortex remains unknown. To study the problem faced by a hypothetical boundary cell, and to predict how cortical circuitry could produce a boundary cell from a population of conventional “simple cells”, we labeled 30,000 natural image patches and used Bayes’ rule to help determine how a simple cell should influence a nearby boundary cell depending on its relative offset in receptive field position and orientation. We identified three basic types of cell-cell interactions: rising and falling interactions with a range of slopes and saturation rates, as well as non-monotonic (bump-shaped) interactions with varying modes and amplitudes. Using simple models we show that a ubiquitous cortical circuit motif consisting of direct excitation and indirect inhibition – a compound effect we call “incitation” – can produce the entire spectrum of simple cell-boundary cell interactions found in our dataset. Moreover, we show that the synaptic weights that parameterize an incitation circuit can be learned by a single-layer “delta” rule. We conclude that incitatory interconnections are a generally useful computing mechanism that the cortex may exploit to help solve difficult natural classification problems.Significance statement:Simple cells in primary visual cortex (V1) respond to oriented edges, and have long been supposed to detect object boundaries, yet the prevailing model of a simple cell – a divisively normalized linear filter – is a surprisingly poor natural boundary detector. To understand why, we analyzed image statistics on and off object boundaries, allowing us to characterize the neural-style computations needed to perform well at this difficult natural classification task. We show that a simple circuit motif known to exist in V1 is capable of extracting high-quality boundary probability signals from local populations of simple cells. Our findings suggest a new, more general way of conceptualizing cell-cell interconnections in the cortex.
Pre-stimulus feedback connectivity biases the content of visual experiences
Authors: Rassi Elie , Wutz Andreas , Müller-Voggel Nadia , Weisz Nathan 
Published: October 2018

AbstractOngoing fluctuations in neural excitability and in network-wide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms, i.e. whether an object is perceived or not. Here, we investigated the impact of pre-stimulus neural fluctuations on the content of perception, i.e. whether one or another object is perceived. We recorded neural activity with magnetoencephalography before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation on each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the post-stimulus period. Applying source localization to the classifier weights suggested early recruitment of V1 and ~160 ms recruitment of category-sensitive FFA. These post-stimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs vase reports. In pre-stimulus intervals, we found no differences in oscillatory power between face vs. vase reports neither in V1 nor in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA prior to face reports for low-frequency oscillations. Specifically, the strength of pre-stimulus feedback connectivity (i.e. Granger causality) from FFA to V1 predicted not only the category of the upcoming percept, but also the strength of post-stimulus neural activity associated with the percept. Our work shows that pre-stimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.
BIN1 genetic risk factor for Alzheimer is sufficient to induce early structural tract alterations in entorhinal-hippocampal area and memory-related hippocampal multi-scale impairments
Authors: Daudin R , Marechal D , Golgolab R , Wang Q , Abe Y , Tsurugizawa T. , Bourg N , Sartori M , Loe-Mie Y , Lipecka J , Guerrera C , McKenzie A , Potier B , Dutar P , Viard J , Lepagnol-Bestel A.M , Winkeler A , Uszynski I. , Hindié V , Birling MC , Lindner L , Chevalier C , Pavlovic G , Reiss M , Kranz H , Dupuis G , Lévêque-Fort S , Diaz J , Davenas E , Dembele D , Atas-Ozcan H. , Laporte J , Thibault-Carpentier C , Malissen B , Rain J.C , Poupon C. , Le Bihan D , Zhang B , Herault Y , Ciobanu L. , Simonneau M 
Published: October 2018

AbstractGenetic factors are known to contribute to Late Onset Alzheimer’s disease (LOAD) but their contribution to pathophysiology, specially to prodomic phases accessible to therapeutic approaches are far to be understood.To translate genetic risk of Alzheimer’s disease (AD) into mechanistic insight, we generated transgenic mouse lines that express a ∼195 kbp human BAC that includes only BIN1, a gene associated to LOAD. This model gives a modest BIN1 overexpression, dependent of the number of BAC copies. At 6 months of age, we detected impaired entorhinal cortex (EC)-hippocampal pathways with specific impairments in EC-dentate gyrus synaptic long-term potentiation, dendritic spines of granular cells and recognition episodic memory. Structural changes were quantified using MRI. Their whole-brain functional impact were analyzed using resting state fMRI with a hypoconnectivity centered on entorhinal cortex.These early phenotype defects independent of any changes in A-beta can be instrumental in the search for new AD drug targets.
Cytoskeletal tension actively sustains the migratory T cell synaptic contact
Authors: Kumari Sudha , Mak Michael , Poh Yehchuin , Tohme Mira , Watson Nicki , Melo Mariane , Janssen Erin , Dustin Michael , Geha Raif , Irvine Darrell J. 
Published: October 2018

SummaryWhen migratory T cells encounter antigen presenting cells (APCs), they arrest and form radially symmetric, stable intercellular junctions termed immunological synapses which facilitate exchange of crucial biochemical information and are critical for T cell immunity. While the cellular processes underlying synapse formation have been well-characterized, those that maintain the symmetry, and thereby the stability of the synapse remain unknown. Here we identify an antigen-triggered mechanism that actively promotes T cell synapse symmetry by generating cytoskeletal tension in the plane of the synapse through focal nucleation of actin via Wiskott -Aldrich syndrome Protein (WASP), and contraction of the resultant actin filaments by myosin II. Following T cell activation, WASP is degraded, leading to cytoskeletal rearrangement and tension decay, which result in synapse breaking. Thus, our study identifies and characterizes a mechanical program within otherwise highly motile T cells that sustains the symmetry and stability of the T cell-APC synaptic contact.
Beta-band activity in medial prefrontal cortex predicts source memory encoding and retrieval accuracy
Authors: Subramaniam Karuna , Hinkley Leighton B.N. , Mizuiri Danielle , Kothare Hardik , Garrett Coleman , Findlay Anne , Houde John F. , Nagarajan Srikantan S. 
Published: October 2018

AbstractReality monitoring is defined as the ability to distinguish internally self-generated information from externally-derived information. The medial prefrontal cortex (mPFC) is a key brain region subserving reality monitoring and has been shown to be activated specifically during the retrieval of self-generated information. However, it is unclear if mPFC is activated during the encoding of self-generated information into memory. If so, it is important to understand whether successful retrieval of self-generated information critically depends on enhanced neural activity within mPFC during initial encoding of this self-generated information.We used magnetoencephalographic imaging (MEGI) to determine the timing and location of cortical activity during a reality-monitoring task involving self generated contextual source memory encoding and retrieval. We found both during encoding and retrieval of self-generated information, when compared to externally-derived information, mPFC showed significant task induced oscillatory power modulation in the beta-band. During initial encoding of self-generated information, greater mPFC beta-band power reductions occurred within a time window of −700ms to −500ms prior to vocalization, activity in mPFC that was not observed during encoding of externally-derived information. This mPFC activity during encoding of self-generated information predicted subsequent retrieval accuracy of self-generated information. Beta-band activity in mPFC was also observed during the initial retrieval of self-generated information within a time window of 300 to 500ms following stimulus onset and correlated with accurate retrieval performance of self-generated information. Together, these results further highlight the importance of mPFC in mediating the initial generation and awareness of participants’ internal thoughts.
Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach
Authors: Ribeiro Fernanda L. , Santos Felipe R. C. dos , Sato João R. , Pinaya Walter H. L. , Biazoli Claudinei E. 
Published: October 2018

AbstractRecent evidence suggests that the human functional connectome is stable at different time scales and unique. These characteristics posit the functional connectome not only as an individual marker but also as a powerful discriminatory measure characterized by high intersubject variability. Among distinct sources of intersubject variability, the long-term sources include functional patterns that emerge from genetic factors. Here, we sought to investigate the contribution of additive genetic factors to the variability of functional networks by determining the heritability of the connectivity strength in a multivariate fashion. First, we reproduced and extended the connectome fingerprinting analysis to the identification of twin pairs. Then, we estimated the heritability of functional networks by a multivariate ACE modeling approach with bootstrapping. Twin pairs were identified above chance level using connectome fingerprinting, with monozygotic twin identification accuracy equal to 57.2% on average for whole-brain connectome. Additionally, we found that a visual (0.37), the medial frontal (0.31) and the motor (0.30) functional networks were the most influenced by additive genetic factors. Our findings suggest that genetic factors not only partially determine intersubject variability of the functional connectome, such that twins can be identified using connectome fingerprinting, but also differentially influence connectivity strength in large-scale functional networks.