bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the dynamics of spatial updating
Authors: Blouin Jean , Pialasse Jean-Philippe , Mouchnino Laurence , Simoneau Martin 
Published: October 2021

AbstractMost of our knowledge on the human neural bases of spatial updating comes from fMRI studies in which recumbent participants moved in virtual environments. As a result, little is known about the dynamic of spatial updating during real body motion. Here, we exploited the high temporal resolution of electroencephalography (EEG) to investigate the dynamics of cortical activation in a spatial updating task where participants had to remember their initial orientation while they were passively rotated about their vertical axis in the dark. After the rotations, the participants pointed towards their initial orientation. We contrasted the EEG signals with those recorded in a control condition in which participants had no cognitive task to perform during body rotations. We found that the amplitude of the P1N1 complex of the rotation-evoked potential (RotEPs) (recorded over the vertex) was significantly greater in the Updating task. The analyses of the cortical current in the source space revealed that the main significant task-related cortical activities started during the N1P2 interval (136-303 ms after rotation onset). They were essentially localised in the temporal and frontal (supplementary motor complex, dorsolateral prefrontal cortex, anterior prefrontal cortex) regions. During this time-window, the right superior posterior parietal cortex (PPC) also showed significant task-related activities. The increased activation of the PPC became bilateral over the P2N2 component (303-470 ms after rotation onset). In this late interval, the cuneus and precuneus started to show significant task-related activities. Together, the present results are consistent with the general scheme that the first task-related cortical activities during spatial updating are related to the encoding of spatial goals and to the storing of spatial information in working memory. These activities would precede those involved in higher order processes also relevant for updating body orientation during rotations linked to the egocentric and visual representations of the environment.
Virally Encoded Connectivity Transgenic Overlay RNA sequencing (VECTORseq) defines projection neurons involved in sensorimotor integration
Authors: Cheung Victoria , Chung Philip , Bjorni Max , Shvareva Varvara A. , Lopez Yesenia C. , Feinberg Evan H. 
Published: October 2021

SummaryBehavior arises from concerted activity throughout the brain. Consequently, a major focus of modern neuroscience is defining the physiology and behavioral roles of projection neurons linking different brain areas. Single-cell RNA sequencing has facilitated these efforts by revealing molecular determinants of cellular physiology and markers that enable genetically targeted perturbations such as optogenetics, but existing methods for sequencing of defined projection populations are low-throughput, painstaking, and costly. We developed a straightforward, multiplexed approach, Virally Encoded Connectivity Transgenic Overlay RNA sequencing (VECTORseq). VECTORseq repurposes commercial retrogradely infecting viruses typically used to express functional transgenes, e.g., recombinases and fluorescent proteins, by treating viral transgene mRNA as barcodes within single-cell datasets. VECTORseq is compatible with different viral families, resolves multiple populations with different projection targets in one sequencing run, and identifies cortical and subcortical excitatory and inhibitory projection populations. Our study provides a roadmap for high-throughput identification of neuronal subtypes based on connectivity.
Comparative analysis of zooplankton diversity in freshwaters: What can we gain from metagenomic analysis?
Authors: Monchamp Marie-Ève , Walsh David A. , Garner Rebecca E. , Kraemer Susanne A. , Beisner Beatrix E. , Cristescu Melania E. , Gregory-Eaves Irene 
Published: October 2021

AbstractMolecular genetic approaches applied to environmental DNA have great potential for biodiversity research and ecosystem monitoring. A metagenome contains genetic information from all organisms captured in an environmental sample. It has been primarily used to study bacteria and archaea, but promising reports focusing on metazoan diversity are emerging. However, methodological uncertainties remain, and studies are required to validate the power and the limitations of such an approach when applied to macro-eukaryotes. Here, we analyzed water sample metagenomes to estimate zooplankton diversity in 22 freshwater lakes across Eastern Canada. We tested the coherence of data based on morphologically identified zooplankton taxa and molecular genetic data derived from shotgun sequencing of environmental DNA collected at the same time. RV coefficients showed a significant correlation between the relative abundance of zooplankton families derived from small subunit rRNA genes extracted from the metagenomes and morphologically identified zooplankton. However, differences in congruence with morphological counts were detected when varied bioinformatic approaches were applied to presence-absence data. This study presents one of the first diversity assessments of a group of aquatic metazoans using metagenomes and validates the coherence of the community composition derived from genetic and classical species surveys. Overall, our results suggest that metagenomics has the potential to be further developed to describe metazoan biodiversity in aquatic ecosystems, and to advance this area we provide key recommendations for workflow improvement.
Phylogeography of Lanius senator reveals conflicts between alpha taxonomy, subspecies ranges and genetics
Authors: Nasuelli Martina , Ilahiane Luca , Boano Giovanni , Cucco Marco , Galimberti Andrea , Pavia Marco , Pioltelli Emiliano , Shafaeipour Arya , Voelker Gary , Pellegrino Irene 
Published: October 2021

AbstractImplementing the effort in understanding biogeographic distribution patterns and taxonomic limits within animal groups is crucial for addressing several challenges of modern zoology. Although avian phylogeography has been deeply investigated within Western Palearctic, several families, such as shrikes, still display complicated or neglected biogeographic patterns both between and within species, thus requiring further investigations. The Woodchat Shrike (Lanius senator) is a long-distance migratory species that exhibits three morphologically well-recognizable subspecies, whose boundaries have never been molecularly investigated. Here, we aimed to define the phylogeographic structure of Lanius senator throughout its breeding range and assess the genetic coherence with the phenotypically described subspecies. We assembled a collection of 34 samples mainly from breeding populations of each subspecies and analyzed them at four mtDNA and two nuDNA markers. We did not find a clear phylogenetic structure with nuclear Ornithine Decarboxylase (ODC) and myoglobin intron 2 (MYO), while all the four mtDNA loci (i.e., ND2, COI, cytb and Control Region) highlighted two main haplogroups, one including both the nominate subspecies L. s. senator and L. s. badius and the second consistent with L. s. niloticus only from the easternmost part of the range. Surprisingly, individuals phenotypically assigned to L. s. niloticus from Israel were genetically assigned to the senator/badius haplogroup. Moreover, genetic distances showed intermediate values between inter-intraspecies diversity usually found in Passerines. We estimated a divergence time among the two haplogroups around 800 kya (549 - 1.259 kya HPD). Our findings showed a mismatch in subspecies assignment using morphology and genetic information and a marked differentiation between the eastern L.s. niloticus and all the other L. senator populations.
Spontaneous emergence of music detectors in a deep neural network
Authors: Kim Gwangsu , Kim Dong-Kyum , Jeong Hawoong 
Published: October 2021

AbstractMusic exists in almost every society, has universal acoustic features, and is processed by distinct neural circuits in humans even with no experience of musical training. These characteristics suggest an innateness of the sense of music in our brain, but it is unclear how this innateness emerges and what functions it has. Here, using an artificial deep neural network that models the auditory information processing of the brain, we show that units tuned to music can spontaneously emerge by learning natural sound detection, even without learning music. By simulating the responses of network units to 35,487 natural sounds in 527 categories, we found that various subclasses of music are strongly clustered in the embedding space, and that this clustering arises from the music-selective response of the network units. The music-selective units encoded the temporal structure of music in multiple timescales, following the population-level response characteristics observed in the brain. We confirmed that the process of generalization is critical for the emergence of music-selectivity and that music-selectivity can work as a functional basis for the generalization of natural sound, thereby elucidating its origin. These findings suggest that our sense of music can be innate, universally shaped by evolutionary adaptation to process natural sound.One-sentence summaryMusic-selectivity can arise spontaneously in deep neural networks trained for natural sound detection without learning music.
Benchmarking phasing software with a whole-genome sequenced cattle pedigree
Authors: Oget-Ebrad Claire , Kadri Naveen Kumar , Moreira Gabriel Costa Monteiro , Karim Latifa , Coppieters Wouter , Georges Michel , Druet Tom 
Published: October 2021

AbstractBackgroundAccurate haplotype reconstruction is required in many applications in quantitative and population genomics. Different phasing methods are available but their accuracy must be evaluated for samples with different properties (population structure, marker density, etc.). We herein took advantage of whole-genome sequence data available for a Holstein cattle pedigree containing 264 individuals, including 98 trios, to evaluate several population-based phasing methods. This data represents a typical example of a livestock population, with low effective population size, high levels of relatedness and long-range linkage disequilibrium.ResultsAfter stringent filtering of our sequence data, we evaluated several population-based phasing programs including one or more versions of AlphaPhase, ShapeIT, Beagle, Eagle and FImpute. To that end we used 98 individuals having both parents sequenced for validation. Their haplotypes reconstructed based on Mendelian segregation rules were considered the gold standard to assess the performance of population-based methods in two scenarios. In the first one, only these 98 individuals were phased, while in the second one, all the 264 sequenced individuals were phased simultaneously, ignoring the pedigree relationships. We assessed phasing accuracy based on switch error counts (SEC) and rates (SER), lengths of correctly phased haplotypes and pairwise SNP phasing accuracies (the probability that a pair of SNPs is correctly phased as a function of their distance). For most evaluated metrics or scenarios, the best software was either ShapeIT4.1 or Beagle5.2, both methods resulting in particularly high phasing accuracies. For instance, ShapeIT4.1 achieved a median SEC of 50 per individual and a mean haplotype block length of 24.1 Mb in the second scenario. These statistics are remarkable since the methods were evaluated with a map of 8,400,000 SNPs, and this corresponds to only one switch error every 40,000 phased informative markers. When more relatives were included in the data, FImpute3.0 reconstructed extremely long segments without errors.ConclusionsWe report extremely high phasing accuracies in a typical livestock sample of 100 sequenced individuals. ShapeIT4.1 and Beagle5.2 proved to be the most accurate, particularly for phasing long segments. Nevertheless, most tools achieved high accuracy at short distances and would be suitable for applications requiring only local haplotypes.
Automated hyperspectral vegetation index derivation using a hyperparameter optimization framework for high-throughput plant phenotyping
Authors: Koh Joshua C.O. , Banerjee Bikram P. , Spangenberg German , Kant Surya 
Published: October 2021

SummaryHyperspectral vegetation indices (VIs) are widely deployed in agriculture remote sensing and plant phenotyping to estimate plant biophysical and biochemical traits. However, existing VIs consist mainly of simple 2-band indices which limits the net performance and often do not generalize well for other traits than they were originally designed for.We present an automated hyperspectral vegetation index (AutoVI) system for the rapid generation of novel 2- to 6-band trait-specific indices in a streamlined process covering model selection, optimization and evaluation driven by the tree parzen estimator algorithm. Its performance was tested in generating novel indices to estimate chlorophyll and sugar contents in wheat.Results show that AutoVI can rapidly generate complex novel VIs (≥4-band index) which correlated strongly (R2 > 0.8) with measured chlorophyll and sugar contents in wheat. AutoVI-derived indices were used as features in simple and stepwise multiple linear regression for chlorophyll and sugar content estimation, and outperformed results achieved with existing 47 VIs and those provided by partial least squares regression.The AutoVI system can deliver novel trait-specific VIs readily adoptable in high-throughput plant phenotyping platforms and should appeal to plant scientists and breeders. A graphical user interface of AutoVI is herein provided.
TET2-mediated epigenetic reprogramming of breast cancer cells impairs lysosome biogenesis
Authors: Laurent Audrey , Madigou Thierry , Bizot Maud , Turpin Marion , Palierne Gaëlle , Mahé Elise , Guimard Sarah , Métivier Raphaël , Avner Stéphane , Le Péron Christine , Salbert Gilles 
Published: October 2021

ABSTRACTMethylation and demethylation of cytosines in DNA are believed to act as keystones of cell-specific gene expression through controlling chromatin structure and accessibility to transcription factors. Cancer cells have their own transcriptional programs and we sought to alter such a cancer-specific program by enforcing expression of the catalytic domain (CD) of the methylcytosine dioxygenase TET2 in breast cancer cells. TET2 CD decreased the tumorigenic potential of cancer cells through both activation and repression of a repertoire of genes that, interestingly, differed in part from the one observed upon treatment with the hypomethylating agent decitabine. In addition to promoting the establishment of an antiviral state, TET2 activated 5mC turnover at thousands of MYC binding motifs and down-regulated a panel of known MYC-repressed genes involved in lysosome biogenesis and function. Thus, an extensive cross-talk between TET2 and the oncogenic transcription factor MYC establishes a lysosomal storage disease-like state that contributes to an exacerbated sensitivity to autophagy inducers.
Specific ATPases drive compartmentalized glycogen utilization in rat skeletal muscle
Authors: Nielsen Joachim , Dubillot Peter , Stausholm Marie-Louise H. , Ørtenblad Niels 
Published: October 2021

AbstractGlycogen is a key energy substrate in excitable tissue and especially in skeletal muscle fibers it contributes with a substantial, but also local energy production. A heterogenic subcellular distribution of three distinct glycogen pools in skeletal muscle is proved by transmission electron microscopy (TEM), which is thought to represent the requirements for local energy stores at the subcellular level. Here, we show that the three main energy-consuming ATPases in skeletal muscles (Ca2+-, Na+,K+-, and myosin ATPases) utilize different local pools of glycogen. These results clearly demonstrate compartmentalized glycogen metabolism and emphasize that spatially distinct pools of glycogen particles act as energy substrate for separated energy requiring processes, suggesting a new paradigm for understanding glycogen metabolism in working muscles, muscle fatigue and metabolic disorders.
Implementation of a novel optogenetic tool in mammalian cells based on a split T7 RNA polymerase
Authors: Dionisi Sara , Piera Karol , Baumschlager Armin , Khammash Mustafa 
Published: October 2021

ABSTRACTOptogenetic tools are widely used to control gene expression dynamics both in prokaryotic and eukaryotic cells. These tools are used in a variety of biological applications from stem cell differentiation to metabolic engineering. Despite some tools already available in bacteria, no light-inducible system currently exists to orthogonally control gene expression in mammalian cells. Such a tool would be particularly important in synthetic biology, where orthogonality is advantageous to achieve robust activation of synthetic networks. Here we implement, characterize and optimize a new orthogonal optogenetic tool in mammalian cells based on a previously published system in bacteria called Opto-T7RNAPs. The tool consists of a split T7 RNA polymerase coupled with the blue light-inducible magnets system (mammalian OptoT7 – mOptoT7). In our study we exploited the T7 polymerase’s viral origins to tune our system’s expression level, reaching up to 20-fold change activation over the dark control. mOptoT7 is used here to generate mRNA for protein expression, shRNA for protein inhibition and Pepper aptamer for RNA visualization. Moreover, we show that mOptoT7 can mitigate gene expression burden when compared to other optogenetic constructs. These properties make mOptoT7 a new powerful tool to use when orthogonality and viral-like RNA species are desired in both synthetic biology and basic science applications.
Weakly migratory metastatic breast cancer cells activate fibroblasts via microvesicle-Tg2 to facilitate dissemination and metastasis
Authors: Schwager Samantha C. , Hapach Lauren A. , Carlson Caroline M. , Mosier Jenna A. , McArdle Tanner J. , Wang Wenjun , Jayathilake Anissa L. , Bordeleau Francois , Antonyak Marc A. , Cerione Richard A. , Reinhart-King Cynthia A. 
Published: October 2021

AbstractCancer cell migration is highly heterogeneous, and the migratory capability of cancer cells is thought to be an indicator of metastatic potential. It is becoming clear that a cancer cell does not have to be inherently migratory to metastasize, with weakly migratory cancer cells often found to be highly metastatic. However, the mechanism through which weakly migratory cells escape from the primary tumor remains unclear. Here, utilizing phenotypically sorted highly and weakly migratory breast cancer cells, we demonstrate that weakly migratory metastatic cells disseminate from the primary tumor via communication with stromal cells. While highly migratory cells are capable of single cell migration, weakly migratory cells rely on cell-cell signaling with fibroblasts to escape the primary tumor. Weakly migratory cells release microvesicles rich in tissue transglutaminase 2 (Tg2) which activate fibroblasts and lead weakly migratory cancer cell migration in vitro. These microvesicles also induce tumor stiffening and fibroblast activation in vivo and enhance the metastasis of weakly migratory cells. Our results identify microvesicles and Tg2 as potential therapeutic targets for metastasis and reveal a novel aspect of the metastatic cascade in which weakly migratory cells release microvesicles which activate fibroblasts to enhance cancer cell dissemination.
Eicosanoids in the pancreatic tumor microenvironment – a multicellular, multifaceted progression
Authors: Gubbala Vikas B. , Jytosana Nidhi , Trinh Vincent Q. , Maurer H. Carlo , Naeem Razia F. , Lytle Nikki K. , Ma Zhibo , Zhao Steven , Lin Wei , Han Haiyong , Shi Yu , Hunter Tony , Singh Pankaj K. , Olive Kenneth P. , Tan Marcus C.B. , Kaech Susan M. , Wahl Geoffrey M. , DelGiorno Kathleen E. 
Published: October 2021

ABSTRACTEicosanoids, oxidized fatty acids that serve as cell-signaling molecules, have been broadly implicated in tumorigenesis. To identify eicosanoids relevant to pancreatic tumorigenesis, we profiled normal pancreas and pancreatic ductal adenocarcinoma (PDAC) in mouse models and patient samples using mass spectrometry. We interrogated RNA sequencing datasets for eicosanoid synthase or receptor expression. Findings were confirmed by immunostaining. In murine models, we identified elevated levels of PGD2, prostacyclin, and thromboxanes in neoplasia while PGE2, 12-HHTre, HETEs, and HDoHEs are elevated specifically in tumors. Analysis of scRNA-seq datasets suggests that PGE2and prostacyclins are derived from fibroblasts, PGD2and thromboxanes from myeloid cells, and PGD2and 5-HETE from tuft cells. In patient samples, we identified a transition from PGD2to PGE2-producing enzymes in the epithelium during the transition to PDAC, fibroblast/tumor expression of PTGIS, and myeloid/tumor cell expression of TBXAS1. Altogether, our analyses identify key changes in eicosanoid species during pancreatic tumorigenesis and the cell types responsible for their synthesis.
A Locus Coeruleus- dorsal CA1 dopaminergic circuit modulates memory linking
Authors: Chowdhury Ananya , Luchetti Alessandro , Fernandes Giselle , Filho Daniel Almeida , Kastellakis George , Tzilivaki Alexandra , Ramirez Erica M , Tran Mary Y , Poirazi Panayiota , Silva Alcino J 
Published: October 2021

SummaryIndividual memories are often linked so that the recall of one triggers the recall of another. For example, contextual memories acquired close in time can be linked, and this is known to depend on temporary increase in excitability that drive the overlap between dorsal CA1 (dCA1) hippocampal ensembles encoding the linked memories. Here, we show that the Locus Coeruleus (LC) cells projecting to dCA1 have a key permissive role in contextual memory linking, without affecting contextual memory formation, and that this effect is mediated by dopamine and not by noradrenaline. Additionally, we found that LC to dCA1 projecting neurons modulate the excitability of dCA1 neurons, and the extent of overlap between dCA1 memory ensembles, as well as the stability of coactivity patterns within these ensembles. This discovery of a neuromodulatory system that specifically affects memory linking without affecting memory formation, reveals a fundamental separation between the brain mechanisms that modulate these two distinct processes.