bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sphingomyelin suppresses Hedgehog signaling by restricting cholesterol accessibility at the ciliary membrane
Authors: Kinnebrew Maia , Iverson Ellen J. , Patel Bhaven B. , Pusapati Ganesh V. , Kong Jennifer H. , Johnson Kristen A. , Luchetti Giovanni , Covey Douglas F. , Siebold Christian , Radhakrishnan Arun , Rohatgi Rajat 
Published: July 2019

AbstractTransmission of the Hedgehog signal across the plasma membrane by Smoothened is proposed to be triggered by its direct interaction with cholesterol. But how is cholesterol, an abundant lipid, regulated tightly enough to control a signaling system that can cause birth defects and cancer? Using toxin-based sensors that distinguish between distinct pools of cholesterol, we find here that Smoothened activation and Hedgehog signaling are driven by a biochemically defined fraction of membrane cholesterol, termed accessible cholesterol. Increasing accessible cholesterol levels by depletion of sphingomyelin, which sequesters cholesterol in complexes, potentiates Hedgehog signaling. By inactivating the transporter-like protein Patched 1, Hedgehog ligands trigger an increase in cholesterol accessibility in the ciliary membrane, the subcellular location for Smoothened signaling. Thus, compartmentalization of Hedgehog signaling in the primary cilium may allow cholesterol accessibility to be used as a second messenger to mediate the communication between Patched 1 and Smoothened, without causing collateral effects on other cellular processes.
Adaptive evolution of nontransitive fitness in yeast
Authors: Buskirk Sean W. , Rokes Alecia B. , Lang Gregory I. 
Published: July 2019

AbstractNontransitivity – commonly illustrated by the rock-paper-scissors game – is well documented among extant species as a contributor to biodiversity. However, it is unclear if nontransitive interactions also arise by way of genealogical succession, and if so, through what mechanisms. Here we identify a nontransitive evolutionary sequence in the context of yeast experimental evolution in which a 1,000-generation evolved clone outcompetes a recent ancestor but loses in direct competition with a distant ancestor. We show that nontransitivity arises due to the combined forces of adaptation in the yeast nuclear genome and the stepwise deterioration of an intracellular virus. We show that, given the initial conditions of the experiment, this outcome likely to arise: nearly half of all populations experience multilevel selection, fixing adaptive mutations in both the nuclear and viral genomes. In contrast to conventional views of virus-host coevolution, we find no evidence that viral mutations (including loss of the virus) increase the fitness of the host. Instead, the evolutionary success of evolved viral variants results from their selective advantage over viral competitors within the context of individual cells. Our results provide the first mechanistic case-study of the adaptive evolution of nontransitivity, in which a series of adaptive replacements produce organisms that are less fit when compared to a distant genealogical ancestor.
Connectivity Gradient in the Human Left Inferior Frontal Gyrus: Intraoperative Cortico-Cortical Evoked Potential Study
Authors: Nakae Takuro , Matsumoto Riki , Kunieda Takeharu , Arakawa Yoshiki , Kobayashi Katsuya , Shimotake Akihiro , Yamao Yukihiro , Kikuchi Takayuki , Aso Toshihiko , Matsuhashi Masao , Yoshida Kazumichi , Ikeda Akio , Takahashi Ryosuke , Lambon Ralph Matthew A. , Miyamoto Susumu 
Published: July 2019

AbstractIn the dual-stream model of language processing, the exact connectivity of the ventral stream to the anterior temporal lobe remains elusive. To investigate the connectivity among the inferior frontal gyrus (IFG) and the lateral part of the temporal and parietal lobes, we integrated spatiotemporal profiles of cortico-cortical evoked potentials (CCEPs) recorded intraoperatively from 14 patients who had had resective surgeries for brain tumor or epileptic focus. The 4D visualization of the combined CCEP data showed that the pars opercularis (Broca’s area) connected to the posterior temporal cortices and the supramarginal gyrus, while the pars orbitalis connected to the anterior lateral temporal cortices and the angular gyrus. Quantitative topographical analysis of CCEP connectivity confirmed an anterior-posterior gradient of connectivity from IFG stimulus sites to the temporal response sites. Reciprocality analysis indicated that the anterior part of the IFG is bi-directionally connected to the temporal or parietal area. The present study revealed that each IFG subdivision has a different connectivity to the temporal lobe with an anterior-posterior gradient and supports the classical connectivity concept of Dejerine that the frontal lobe is connected to the temporal lobe through the arcuate fasciculus and also a double-fan-shaped structure, anchored at the limen insulae.
Integration of transcriptome, proteome and phosphoproteome data elucidates the genetic control of molecular networks
Authors: Großbach Jan , Gillet Ludovic , Clément-Ziza Mathieu , Schmalohr Corinna L. , Schubert Olga T. , Barnes Christopher A. , Bludau Isabell , Aebersold Ruedi , Beyer Andreas 
Published: July 2019

AbstractGenomic variation affects cellular networks by altering diverse molecular layers such as RNA levels, protein abundance, and post-translational protein modifications. However, it remains unclear how these different layers are affected by genetic polymorphisms and give rise to complex physiological phenotypes. To address these questions, we generated high-quality transcriptome, proteome, and phosphoproteome data for a panel of 112 genetically diverse yeast strains. While genetic effects on transcript abundances were generally transmitted to the protein level, we found a significant uncoupling of the transcript-protein relationship for certain protein classes, such as subunits of protein complexes. The additional phosphoproteomics data suggests that the same genetic locus often affects distinct sets of genes within each of these layers. In particular, QTLs tended to affect upstream regulatory proteins at the phosphorylation layer, whereas downstream pathway targets were typically affected at the transcript and protein abundance layers. Underscoring the importance of regulatory protein phosphorylation in linking genetic to phenotypic variation is the finding that the number of protein phosphosites associated with a given genetic locus was more predictive for its influence on cellular growth traits than the number of transcripts or proteins.This study shows how multi-layered molecular networks mediate the effects of genomic variants to more complex physiological traits and highlights the important role of protein phosphorylation in mediating these effects.
Proteome-wide inference of protein kinase regulatory circuits
Authors: Invergo Brandon M. , Petursson Borgthor , Bradley David , Giudice Girolamo , Petsalaki Evangelia , Beltrao Pedro 
Published: July 2019

SummaryComplex networks of regulatory relationships between protein kinases comprise a major component of intracellular signaling. Although many kinase-kinase regulatory relationships have been described in detail, these are biased towards well-studied kinases while the majority of possible relationships remains unexplored. Here, we implement data-driven, unbiased methods to predict human kinase-kinase regulatory relationships and whether they have activating or inhibiting effects. We incorporate high-throughput data, kinase specificity profiles, and structural information to produce our predictions. The results successfully recapitulate previously annotated regulatory relationships and can reconstruct known signaling pathways from the ground up. The full network of predictions is relatively sparse, with the vast majority of relationships assigned low probabilities. However, it nevertheless suggests denser modes of inter-kinase regulation than normally considered in intracellular signaling research.
A simple approach for accurate peptide quantification in MS-based proteomics
Authors: Maia Teresa Mendes , Staes An , Plasman Kim , Pauwels Jarne , Boucher Katie , Argentini Andrea , Martens Lennart , Montoye Tony , Gevaert Kris , Impens Francis 
Published: July 2019

ABSTRACTDespite its growing popularity and use, bottom-up proteomics remains a complex analytical methodology. Its general workflow consists of three main steps: sample preparation, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and computational data analysis. Quality assessment of the different steps and components of this workflow is instrumental to identify technical flaws and to avoid loss of precious measurement time and sample material. However, assessment of the extent of sample losses along the sample preparation protocol, in particular after proteolytic digestion, is not yet routinely implemented because of the lack of an accurate and straightforward method to quantify peptides. Here, we report on the use of a microfluidic UV/visible spectrophotometer to quantify MS-ready peptides directly in MS loading solvent, consuming only 2 μl of sample. We determined the optimal peptide amount for LC-MS/MS analysis on a Q Exactive HF mass spectrometer using a dilution series of a commercial K562 cell digest. Careful evaluation of selected LC and MS parameters allowed us to define 3 μg as an optimal peptide amount to be injected on this particular LC-MS/MS system. Finally, using tryptic digests from human HEK293T cells, we showed that injecting equal peptide amounts, rather than approximated ones, results into less variable LC-MS/MS and protein quantification data. The obtained quality improvement together with easy implementation of the approach makes it possible to routinely quantify MS-ready peptides as a next step in daily proteomics quality control.
Coupling Day Length Data and Genomic Prediction tools for Predicting Time-Related Traits under Complex Scenarios
Authors: Jarquin Diego , Kajiya-Kanegae Hiromi , Taishen Chen , Yabe Shiori , Persa Reyna , Yu Jianming , Nakagawa Hiroshi , Yamasaki Masanori , Iwata Hiroyoshi 
Published: July 2019

AbstractGenomic selection (GS) has proven to be an efficient tool for predicting crop-rank performance of untested genotypes; however, when the traits have intermediate optima (phenology stages) this implementation might not be the most convenient. GS might deliver high rank correlations but incurring in serious bias. Days to heading (DTH) is a crucial development stage in rice for regional adaptability with significant impact in yield potential. The objectives of this research consisted in the development of a method that accurately predicts time related traits like DTH in unobserved environments. For this, we developed an implementation that incorporate day length information (DL) in the prediction process for two relevant scenarios: CV0, predicting tested genotypes in unobserved environments (C method); and CV00, predicting untested genotypes in unobserved environments (CB method). The use of DL has advantages over weather data since it can be determined in advance just by knowing the location and planting date. The proposed methods showed that DL information significantly helps to improve the predictive ability of DTH in unobserved environments. Under CV0, the C method returned an root-mean-square-error (RMSE) of 3.9 days, a Pearson Correlation (PC) of 0.98 and the differences between the predicted and observed environmental means (EMD) ranged between −4.95 and 4.67 days. For CV00, the CB method returned an RMSE of 7.3 days, a PC of 0.93 and the EMD ranged between −6.4 and 4.1 days while the conventional GS implementation produced an RMSE of 18.1 days, a PC of 0.41 and the EMD ranged between −31.5 and 28.7 days.
Structural control energy of resting-state functional brain states reveals inefficient brain dynamics in psychosis vulnerability
Authors: Zöller Daniela , Sandini Corrado , Schaer Marie , Eliez Stephan , Bassett Danielle S. , Van De Ville Dimitri 
Published: July 2019

AbstractHow the brain’s white-matter anatomy constrains brain activity is an open question that might give insights into the mechanisms that underlie mental disorders such as schizophrenia. Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder with an extremely high risk for psychosis providing a test case to study developmental aspects of schizophrenia. In this study, we used principles from network control theory to probe the implications of aberrant structural connectivity for the brain’s functional dynamics in 22q11DS. We retrieved brain states from resting-state functional magnetic resonance images of 78 patients with 22q11DS and 85 healthy controls. Then, we compared them in terms of persistence control energy; i.e., the control energy that would be required to persist in each of these states based on individual structural connectivity and a dynamic model. Persistence control energy was altered in a broad pattern of brain states including both energetically more demanding and less demanding brain states in 22q11DS. Further, we found a negative relationship between persistence control energy and resting-state activation time, which suggests that the brain reduces energy by spending less time in energetically demanding brain states. In patients with 22q11DS, this behavior was less pronounced, suggesting a dynamic inefficiency of brain function in the disease. In summary, our results provide initial insights into the dynamic implications of altered structural connectivity in 22q11DS, which might improve our understanding of the mechanisms underlying the disease.
Imaging invasive fungal growth and inflammation in NADPH oxidase-deficient zebrafish
Authors: Schoen Taylor J. , Rosowski Emily E. , Knox Benjamin P. , Bennin David , Keller Nancy P. , Huttenlocher Anna 
Published: July 2019

AbstractNeutrophils are primary cells of the innate immune system that generate reactive oxygen species (ROS) and mediate host defense. Deficient phagocyte NADPH oxidase (PHOX) function leads to chronic granulomatous disease (CGD) that is characterized by invasive infections including those by the generally non-pathogenic fungusAspergillus nidulans. The role of neutrophil ROS in this specific host-pathogen interaction remains unclear. Here, we exploit the optical transparency of zebrafish to image the effects of neutrophil ROS on invasive fungal growth and neutrophil behavior in response toAspergillus nidulans. In a wild-type host,A. nidulansgerminates rapidly and elicits a robust inflammatory response with efficient fungal clearance. PHOX-deficient larvae have increased susceptibility to invasiveA. nidulansinfection despite robust neutrophil infiltration. Expression of p22phoxspecifically in neutrophils does not affect fungal germination but instead limits the area of fungal growth and excessive neutrophil inflammation and is sufficient to restore host survival in p22phox-deficient larvae. These findings suggest that neutrophil ROS limits invasive fungal growth and has immunomodulatory activities that contribute to the specific susceptibility of PHOX-deficient hosts to invasiveA. nidulansinfection.
Adaptive Estimation for Epidemic Renewal and Phylogenetic Skyline Models
Authors: Parag Kris V , Donnelly Christl A 
Published: July 2019

AbstractEstimating temporal changes in a target population from phylogenetic or count data is an important problem in ecology and epidemiology. Reliable estimates can provide key insights into the climatic and biological drivers influencing the diversity or structure of that population and evidence hypotheses concerning its future growth or decline. In infectious disease applications, the individuals infected across an epidemic form the target population. The renewal model estimates the effective reproduction number,R, of the epidemic from counts of its observed cases. The skyline model infers the effective population size,N, underlying a phylogeny of sequences sampled from that epidemic. Practically,Rmeasures ongoing epidemic growth whileNinforms on historical caseload. While both models solve distinct problems, the reliability of their estimates depends onp-dimensional piecewise-constant functions. Ifpis misspecified, the model might underfit significant changes or overfit noise and promote a spurious understanding of the epidemic, which might misguide intervention policies or misinform forecasts. Surprisingly, no transparent yet principled approach for optimisingpexists. Usually,pis heuristically set, or obscurely controlled via complex algorithms. We present a computable and interpretablep-selection method based on the minimum description length (MDL) formalism of information theory. Unlike many standard model selection techniques, MDL accounts for the additional statistical complexity induced by how parameters interact. As a result, our method optimisespso thatRandNestimates properly adapt to the available data. It also outperforms comparable Akaike and Bayesian information criteria on several classification problems. Our approach requires some knowledge of the parameter space and exposes the similarities between renewal and skyline models.
Dirac mixture distributions for the approximation of mixed effects models⋆
Authors: Wang Dantong , Stapor Paul , Hasenauer Jan 
Published: July 2019

AbstractMixed effect modeling is widely used to study cell-to-cell and patient-to-patient variability. The population statistics of mixed effect models is usually approximated using Dirac mixture distributions obtained using Monte-Carlo, quasi Monte-Carlo, and sigma point methods. Here, we propose the use of a method based on the Cramér-von Mises Distance, which has been introduced in the context of filtering. We assess the accuracy of the different methods using several problems and provide the first scalability study for the Cramér-von Mises Distance method. Our results indicate that for a given number of points, the method based on the modified Cramér-von Mises Distance method tends to achieve a better approximation accuracy than Monte-Carlo and quasi Monte-Carlo methods. In contrast to sigma-point methods, the method based on the modified Cramér-von Mises Distance allows for a flexible number of points and a more accurate approximation for nonlinear problems.
Inferring genome-wide correlations of mutation fitness effects between populations
Authors: Huang Xin , Fortier Alyssa Lyn , Coffman Alec J. , Struck Travis J. , Irby Megan N. , James Jennifer E. , Léon-Burguete José E. , Ragsdale Aaron P. , Gutenkunst Ryan N. 
Published: July 2019

AbstractThe effect of a mutation on fitness may differ between populations depending on environmental and genetic context, but little is known about the factors that underlie such differences. To quantify genome-wide correlations in mutation fitness effects, we developed a novel concept called a joint distribution of fitness effects (DFE) between populations. We then proposed a new statisticwto measure the DFE correlation between populations. Using simulation, we showed that inferring the DFE correlation from the joint allele frequency spectrum is statistically precise and robust. Using population genomic data, we inferred DFE correlations of populations in humans,Drosophila melanogaster, and wild tomatoes. In these specices, we found that the overall correlation of the joint DFE was inversely related to genetic differentiation. In humans andD. melanogaster, deleterious mutations had a lower DFE correlation than tolerated mutations, indicating a complex joint DFE. Altogether, the DFE correlation can be reliably inferred, and it offers extensive insight into the genetics of population divergence.
Insights into the molecular mechanisms underlying the inhibition of acid-sensing ion channel 3 gating by Stomatin
Authors: Klipp Robert C. , Cullinan Megan M. , Bankston John R. 
Published: July 2019

AbstractStomatin is a monotopic integral membrane protein found in all classes of life that has been shown to regulate members of the Acid-Sensing Ion Channel (ASIC) family. However, the mechanism by which Stomatin alters ASIC function is not known. Using chimeric channels, we combined patch clamp electrophysiology and FRET to search for regions of ASIC3 critical for binding to and regulation by Stomatin. With this approach, we found that regulation requires two distinct sites on ASIC3: the distal C-terminus and the first transmembrane domain. Mutation of the C-terminal site disrupts binding and regulation whereas disruption of the transmembrane site eliminates functional regulation. We then showed that Stomatin does not alter surface expression using fluorescence imaging and a surface biotinylation assay. Based on these findings, we propose a model whereby STOM is anchored to the channel via a site on the distal C-terminus but alters ASIC3 gating through action on TM1.
Supercentenarian and remarkable age records exhibit patterns indicative of clerical errors and pension fraud
Authors: Newman Saul Justin 
Published: July 2019

AbstractThe observation of individuals attaining remarkable ages, and their concentration into geographic sub-regions or ‘blue zones’, has generated considerable scientific interest. Proposed drivers of remarkable longevity include high vegetable intake, strong social connections, and genetic markers. Here, we reveal new predictors of remarkable longevity and ‘supercentenarian’ status. In the United States, supercentenarian status is predicted by the absence of vital registration. The state-specific introduction of birth certificates is associated with a 69-82% fall in the number of supercentenarian records. In Italy, England, and France, which have more uniform vital registration, remarkable longevity is instead predicted by poverty, low per capita incomes, shorter life expectancy, higher crime rates, worse health, higher deprivation, fewer 90+ year olds, and residence in remote, overseas, and colonial territories. In England and France, higher old-age poverty rates alone predict more than half of the regional variation in attaining a remarkable age. Only 18% of ‘exhaustively’ validated supercentenarians have a birth certificate, falling to zero percent in the USA, and supercentenarian birthdates are concentrated on days divisible by five: a pattern indicative of widespread fraud and error. Finally, the designated ‘blue zones’ of Sardinia, Okinawa, and Ikaria corresponded to regions with low incomes, low literacy, high crime rate and short life expectancy relative to their national average. As such, relative poverty and short lifespan constitute unexpected predictors of centenarian and supercentenarian status and support a primary role of fraud and error in generating remarkable human age records.