bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rationalizing generation of broad spectrum antibiotics with the addition of a primary amine
Authors: Haloi Nandan , Vasan Archit Kumar , Geddes Emily , Prasanna Arjun , Wen Po-Chao , Metcalf William W. , Hergenrother Paul , Tajkhorshid Emad 
Published: August 2021

AbstractAntibiotic resistance of Gram-negative bacteria is largely attributed to the low permeability of their outer membrane (OM). Recently, we disclosed the eNTRy rules, a key lesson of which is that the introduction of a primary amine enhances OM permeation in certain contexts. To understand the molecular basis for this finding, we perform an extensive set of molecular dynamics (MD) simulations and free energy calculations comparing the permeation of aminated and amine-free antibiotic derivatives through the most abundant OM porin of E. coli, OmpF. To improve sampling of conformationally flexible drugs in MD simulations, we developed a novel, Monte Carlo and graph theory based algorithm to probe more efficiently the rotational and translational degrees of freedom visited during the permeation of the antibiotic molecule through OmpF. The resulting pathways were then used for free-energy calculations, revealing a lower barrier against the permeation of the aminated compound, substantiating its greater OM permeability. Further analysis revealed that the amine facilitates permeation by enabling the antibiotic to align its dipole to the luminal electric field of the porin and while forming favorable electrostatic interactions with specific, highly-conserved charged residues. The importance of these interactions in permeation was further validated with experimental mutagenesis and whole cell accumulation assays. Overall, this study provides insights on the importance of the primary amine for antibiotic permeation into Gram-negative pathogens that could help the design of future antibiotics. We also offer a new computational approach for calculating free-energy of processes where relevant molecular conformations cannot be efficiently captured.
MYCN mediates cysteine addiction and sensitizes to ferroptosis
Authors: Alborzinia Hamed , Flórez Andrés F. , Gogolin Sina , Brückner Lena M. , Shao Chunxuan , Gartlgruber Moritz , Nadler-Holly Michal , Ziehm Matthias , Paul Franziska , Steinhauser Sebastian , Bell Emma , Shaikhkarami Marjan , Hartlieb Sabine , Dreidax Daniel , Hess Elisa M. , Kreth Jochen , Poschet Gernot , Büttner Michael , Nicke Barbara , Stresemann Carlo , Reiling Jan H. , Fischer Matthias , Amit Ido , Selbach Matthias , Herrmann Carl , Wölfl Stefan , Henrich Kai-Oliver , Höfer Thomas , Westermann Frank 
Published: August 2021

AbstractAberrant expression of MYC family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYC induces massive lipid peroxidation upon depletion of cysteine, the rate-limiting amino acid for glutathione biosynthesis and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and irondependent type of cell death. In MYCN-amplified childhood neuroblastoma, MYCN mediates resistance to ferroptosis by activating transsulfuration of methionine to cysteine. MYCN may contribute to spontaneous tumor regression in low-risk neuroblastomas by promoting ferroptosis in cells with epigenetically silenced cystathionine-beta-synthase, the rate-limiting enzyme for transsulfuration. We identified enzymes and antiporter proteins crucial to ferroptotic escape, providing multiple previously unknown sites that may be acted on therapeutically.
geneBasis: an iterative approach for unsupervised selection of targeted gene panels from scRNA-seq
Authors: Missarova Alsu , Jain Jaison , Butler Andrew , Ghazanfar Shila , Stuart Tim , Brusko Maigan , Wasserfall Clive , Nick Harry , Brusko Todd , Atkinson Mark , Satija Rahul , Marioni John 
Published: August 2021

AbstractThe problem of selecting targeted gene panels that capture maximum variability encoded in scRNA-sequencing data has become of great practical importance. scRNA-seq datasets are increasingly being used to identify gene panels that can be probed using alternative molecular technologies, such as spatial transcriptomics. In this context, the number of genes that can be probed is an important limiting factor, so choosing the best subset of genes is vital. Existing methods for this task are limited by either a reliance on pre-existing cell type labels or by difficulties in identifying markers of rare cell types. We resolve this by introducing an iterative approach, geneBasis, for selecting an optimal gene panel, where each newly added gene captures the maximum distance between the true manifold and the manifold constructed using the currently selected gene panel. We demonstrate, using a variety of metrics and diverse datasets, that our approach outperforms existing strategies, and can not only resolve cell types but also more subtle cell state differences. Our approach is available as an open source, easy-to-use, documented R package (https://github.com/MarioniLab/geneBasisR).
Development of motor neurons and motor activity in zebrafish requires F-actin nucleation by Fmn2b
Authors: Nagar Dhriti , Carrington Blake , Burgess Shawn M , Ghose Aurnab 
Published: August 2021

ABSTRACTBackgroundCytoskeletal remodelling plays a pivotal role in the establishment of neuronal connectivity during development and in plasticity in adults. Mutations in the cytoskeleton regulatory protein Formin-2 (Fmn2) are associated with neurodevelopmental disorders like intellectual disability, though its function in neuronal morphogenesis has not been characterisedin vivo.ResultsHere we develop a loss-of-function model forfmn2b, the zebrafish orthologue of Fmn2, using CRISPR/Cas9-mediated gene editing.fmn2bmutants display motor deficits starting from the earliest motor responses in the embryo. We find thatfmn2bis expressed in spinal motor neurons and its loss reduces motor neuron innervation of the axial muscles without affecting myotome integrity. The translocation of caudal primary (CaP) motor neuron outgrowth is compromised infmn2bmutants, while rostral primary (RoP) motor neurons have missing soma or stall at the horizontal myoseptum. Strikingly, axon collateral branching of the motor neurons is severely compromised and results in reduced synaptic coverage of the myotome. Rescue experiments identify the requirement for Fmn2-mediated actin nucleation for motor neuron outgrowth and arborisation.ConclusionsThe zebrafish loss-of-function model of Fmn2 reveals the specific requirement of F-actin polymerisation by Fmn2 in neuromuscular development. It also underscores the role of Fmn2 in motor neuropathies, especially as a proportion of individuals harbouring mutations in Fmn2 present with hypotonia.
Estimating Intraclonal Heterogeneity and Subpopulation Changes from Perturbational Bulk Gene Expression Profiles in LINCS L1000 CMap by Premnas
Authors: Hsieh Chiao-Yu , Tu Ching-Chih , Hung Jui-Hung 
Published: August 2021

AbstractBackgroundThe connectivity among signatures upon perturbations curated in the CMap library provides a valuable resource for understanding therapeutic pathways and biological processes associated with the drugs and diseases.MotivationHowever, due to the nature of bulk-level expression profiling by the L1000 assay, intraclonal heterogeneity and subpopulation compositional change that could contribute to the responses to perturbations are largely neglected, hampering the interpretability and reproducibility of the connections.ResultsIn this work, we proposed a computational framework, Premnas, to estimate the abundance of undetermined subpopulations from L1000 profiles in CMap directly according to an ad hoc subpopulation representation learned from a well-normalized batch of single-cell RNA-seq datasets by the archetypal analysis. By recovering the information of subpopulation changes upon perturbation, the potentials of searching for drug cocktails and drug-resistant/susceptible subpopulations with CMap L1000 were further explored and examined.ConclusionsThe proposed framework enables a new perspective to understand the connectivity among cellular signatures and expands the scope of the CMAP and other similar perturbation datasets limited by the bulk profiling technology. The executable and source code of Premnas is freely available athttps://github.com/jhhung/Premnas.HighlightsA computational framework (i.e., Premnas) for learning subpopulation characteristics by the archetypal analysis and deconvoluting bulk expression profiles using the digital cytometry into subpopulation composition was proposed and validated.Intraclonal heterogeneity and subpopulation changes upon different perturbagen treatments in LINCS CMap L1000 datasets were estimated by Premnas.With Premnas, we introduced a new strategy of finding effective drug cocktails and further linked the drug-resistant subpopulation found in CMap L1000 to a known drug-resistant clone (i.e., the pre-adapted [PA] cell).To our best knowledge, this work is the first attempt to provide a new subpopulation perspective to CMap database.We believe Premnas can be applied to all the perturbation datasets, of which intraclonal/intratumoral heterogeneity was concealed by the bulk profiling and hereafter provides a new dimension of interpreting the connectivity.
CD155 and EndoA1 mediate growth and tissue invasion downstream of MAP4K4 in medulloblastoma cells
Authors: Capdeville Charles , Russo Linda , Penton David , Migliavacca Jessica , Zecevic Milica , Gries Alexandre , Neuhauss Stephan C.F. , Grotzer Michael A. , Baumgartner Martin 
Published: August 2021

AbstractThe composition of the plasma membrane (PM)-associated proteome of tumor cells determines cell-cell and cell-matrix interactions and the response to environmental cues. Whether the PM-associated proteome impacts the phenotype of Medulloblastoma (MB) tumor cells and how it adapts in response to growth factor cues is poorly understood. Using a spatial proteomics approach, we observed that hepatocyte growth factor (HGF)-induced activation of the receptor tyrosine kinase c-MET in MB cells changes the abundance of transmembrane and membrane-associated proteins. The depletion of MAP4K4, a pro-migratory effector kinase downstream of c-MET, leads to a specific decrease of the adhesion and immunomodulatory receptor CD155 and of components of the fast-endophilin-mediated endocytosis (FEME) machinery in the PM-associated proteome of HGF-activated MB cells. The decreased surface expression of CD155 or of the FEME effector Endophilin A1 reduces growth and invasiveness of MB tumor cells in the tissue context. These data thus describe a novel function of MAP4K4 in the control of the PM-associated proteome of tumor cells and identified two downstream effector mechanisms controlling proliferation and invasiveness of MB cells.Graphical abstractc-MET activation upon HGF stimulation induces c-MET internalization and induces downstream MAP4K4 activity. (1) MAP4K4 is required downstream of activated c-MET for the maintenance of surface presentation of CD155 in activated cells. CD155 expression is required for MB cell migration, invasion and proliferation in the tissue context. (2) MAP4K4 is required downstream of activated c-MET to maintain membrane depolarization, possibly by regulating the surface localization of several ion channels and transporters. (3) MAP4K4 is required downstream of activated c-MET cause PM-proximal localization of FEME effector CIP4, FBP17 and CIN85. The FEME effector endophilin A is necessary for MB cell migration, invasion and dissemination.
Echolocating whales use ultra-fast echo-kinetic responses to track evasive prey
Authors: Vance Heather Margaret , Madsen Peter Teglberg , Aguilar de Soto Natacha , Wisniewska Danuta Maria , Ladegaard Michael , Hooker Sascha Kate , Johnson Mark 
Published: August 2021

AbstractVisual predators rely on fast-acting optokinetic reflexes to track and capture agile prey. Most toothed whales, however, rely on echolocation for hunting and have converged on biosonar clicking rates reaching 500/s during prey pursuits. If echoes are processed on a click-by-click basis, as assumed, neural responses 100x faster than those in vision are required to keep pace with this information flow. Using high-resolution bio-logging of wild predator-prey interactions we show that toothed whales adjust clicking rates to track prey movement within 50-200ms of prey escape responses. Hypothesising that these stereotyped biosonar adjustments are elicited by sudden prey accelerations, we measured echo-kinetic responses from trained harbour porpoises to a moving target and found similar latencies. High biosonar sampling rates are, therefore, not supported by extreme speeds of neural processing and muscular responses. Instead, the neuro-kinetic response times in echolocation are similar to those of tracking reflexes in vision, suggesting a common neural underpinning.
Retinoids rescue ceruloplasmin secretion and alleviate oxidative stress in Wilson’s disease-specific hepatocytes
Authors: Song Dan , Takahashi Gou , Zheng Yun-Wen , Matsuo-Takasaki Mami , Li Jingyue , Takami Miho , An Yuri , Hemmi Yasuko , Miharada Natsumi , Fujioka Tsuyoshi , Noguchi Michiya , Nakajima Takashi , Saito Megumu K. , Nakamura Yukio , Oda Tatsuya , Miyaoka Yuichiro , Hayashi Yohei 
Published: August 2021

SummaryWilson’s disease (WD) is a copper metabolic disorder, which is caused by defective ATP7B function. Here, we have generated induced pluripotent stem cells (iPSCs) from WD patients carrying compound heterozygous mutations on ATP7B. ATP7B loss- and gain-of-functions were further manifested with ATP7B-deficient iPSCs and heterozygously-corrected R778L WD patient-derived iPSCs using CRISPR-Cas9-based gene editing. Transcriptome analysis identified abnormalities of retinoid signaling pathway and lipid metabolism in WD-specific hepatocytes. Although the expression level of ATP7B protein was variable among WD-specific hepatocytes, the expression and secretion of ceruloplasmin (Cp), which is a downstream copper carrier in plasma, were consistently decreased. Cp secretion-based drug screening identified all-trans retinoic acid (ATRA) as promising candidates for rescuing Cp secretion. ATRA also alleviated reactive oxygen species (ROS) production induced by lipid accumulation in WD-specific hepatocytes. Our patient-derived iPSC-based hepatic models provide potential therapeutics for liver steatosis in WD and other fatty liver diseases.
pOPIN-GG: A resource for modular assembly in protein expression vectors
Authors: Bentham Adam R. , Youles Mark , Mendel Melanie N. , Varden Freya A. , Concepcion Juan Carlos De la , Banfield Mark J. 
Published: August 2021

AbstractThe ability to recombinantly produce target proteins is essential to many biochemical, structural, and biophysical assays that allow for interrogation of molecular mechanisms behind protein function. Purification and solubility tags are routinely used to maximise the yield and ease of protein expression and purification from E. coli. A major hurdle in high-throughput protein expression trials is the cloning required to produce multiple constructs with different solubility tags. Here we report a modification of the well-established pOPIN expression vector suite to be compatible with modular cloning via Type IIS restriction enzymes. This allows users to rapidly generate multiple constructs with any desired tag, introducing modularity in the system and delivering compatibility with other modular cloning vector systems, for example streamlining the process of moving between expression hosts. We demonstrate these constructs maintain the expression capability of the original pOPIN vector suite and can also be used to efficiently express and purify protein complexes, making these vectors an excellent resource for high-throughput protein expression trials.HighlightspOPIN-GG expression vectors allow for modular cloning enabling rapid screening of purification and solubility tags at no loss of expression compared to previous vectors.Cloning into the pOPIN-GG vectors can be performed from PCR products or from level 0 vectors containing the required parts.Several vectors with different resistances and origins of replication have been generated allowing the effective co-expression and purification of protein complexes.All pOPIN-GG vectors generated here are available on Addgene, as well as level 0 acceptors and tags.
Pango lineage designation and assignment using SARS-CoV-2 spike gene nucleotide sequences
Authors: O’Toole Áine , Pybus Oliver G. , Abram Michael E. , Kelly Elizabeth J. , Rambaut Andrew 
Published: August 2021

AbstractMore than 2 million SARS-CoV-2 genome sequences have been generated and shared since the start of the COVID-19 pandemic and constitute a vital information source that informs outbreak control, disease surveillance, and public health policy. The Pango dynamic nomenclature is a popular system for classifying and naming genetically-distinct lineages of SARS-CoV-2, including variants of concern, and is based on the analysis of complete or near-complete virus genomes. However, for several reasons, nucleotide sequences may be generated that cover only the spike gene of SARS-CoV-2. It is therefore important to understand how much information about Pango lineage status is contained in spike-only nucleotide sequences. Here we explore how Pango lineages might be reliably designated and assigned to spike-only nucleotide sequences. We survey the genetic diversity of such sequences, and investigate the information they contain about Pango lineage status. Although many lineages, including the main variants of concern, can be identified clearly using spike-only sequences, some spike-only sequences are shared among tens or hundreds of Pango lineages. To facilitate the classification of SARS-CoV-2 lineages using subgenomic sequences we introduce the notion of designating such sequences to a “lineage set”, which represents the range of Pango lineages that are consistent with the observed mutations in a given spike sequence. These data provide a foundation for the development of software tools that can assign newly-generated spike nucleotide sequences to Pango lineage sets.
Trial by trial, machine learning approach identifies temporally discrete Aδ- and C-fibre mediated laser evoked potentials that predict pain behaviour in rats
Authors: Sales A.C. , Blockeel A.J. , Huxter J.R. , Dunham J.P. , Drake R.A.R. , Truini A. , Mouraux A. , Treede RD. , Phillips K.G. , Pickering A.E. 
Published: August 2021

AbstractLaser evoked potentials (LEPs) – the EEG response to temporally-discrete thermal stimuli – are commonly used in experimental pain studies in humans. Such stimuli selectively activate nociceptors and produce EEG features which correlate with pain intensity. The rodent LEP has been proposed to be a translational biomarker of nociception and pain, however its validity has been questioned because of reported differences in the classes of nociceptive fibres mediating the response. Here we use a machine learning, trial by trial analysis approach on wavelet-denoised LEPs generated by stimulation of the plantar hindpaw of rats. The LEP amplitude was more strongly related to behavioural response than to laser stimulus energy. A simple decision tree classifier using LEP features was able to predict behavioural responses with 73% accuracy. An examination of the features used by the classifier showed that mutually exclusive short and long latency LEP peaks were clearly seen in single-trial data, yet were not evident in grand average data pooled from multiple trials. This bimodal distribution of LEP latencies was mirrored in the paw withdrawal latencies which were preceded and predicted by the LEP responses. The proportion of short latency events was increased after intradermal application of high dose capsaicin (to defunctionalise TRPV1 expressing nociceptors), suggesting they were mediated by Aδ-fibres (specifically AMH-I). These findings demonstrate that both C- and Aδ-fibres contribute to rodent LEPs and concomitant behavioural responses, providing a real-time assay of specific fibre function in conscious animals. Single-trial analysis approaches can improve the utility of LEPs as a translatable biomarker of pain.
Clonal reconstruction from co-occurrence of vector integration sites allows accurate quantification of expanding clones in vivo
Authors: Wagner Sebastian , Baldow Christoph , Calabria Andrea , Rudilosso Laura , Gallina Pierangela , Montini Eugenio , Cesana Daniela , Glauche Ingmar 
Published: August 2021

AbstractHigh transduction rates of viral vectors in gene therapies (GT) and experimental hematopoiesis ensure a high frequency of gene delivery, although multiple integration events can occur in the same cell. Therefore, tracing of integration sites (IS) leads to misquantification of the true clonal spectrum and limits safety considerations in GT.Hence, we use correlations between repeated measurements of IS abundances to estimate their mutual similarity and identify clusters of co-occurring IS, for which we assume a clonal origin. We evaluate the performance, robustness and specificity of our methodology using clonal simulations. The reconstruction methods, implemented and provided as an R-package, are further applied to experimental clonal mixes and to a preclinical model of hematopoietic GT.Our results demonstrate that clonal reconstruction from IS data allows to overcome systematic biases in the clonal quantification as an essential prerequisite for the assessment of safety and long-term efficacy of GT involving integrative vectors.
Three-level Sleep Stage Classification Based on Wrist-worn Accelerometry Data Alone
Authors: Hu Jian , Shou Haochang 
Published: August 2021

ABSTRACTObjectiveThe use of wearable sensor devices on daily basis to track real-time movements during wake and sleep has provided opportunities for automatic sleep quantification using such data. Existing algorithms for classifying sleep stages often require large training data and multiple input signals including heart rate and respiratory data. We aimed to examine the capability of classifying sleep stages using sensible features directly from accelerometers only with the aid of advanced recurrent neural networks.Materials and MethodsWe analyzed a publicly available dataset with accelerometry data in 5s epoch length and polysomnography assessments. We developed long short-term memory (LSTM) models that take the 3-axis accelerations, angles, and temperatures from concurrent and historic observation windows to predict wake, REM and non-REM sleep. Leave-one-subject-out experiments were conducted to compare and evaluate the model performance with conventional nonsequential machine learning models using metrics such as multiclass training and testing accuracy, weighted precision, F1 score and area-under-the-curve (AUC).ResultsOur sequential analysis framework outperforms traditional non-sequential models in all aspects of model evaluation metrics. We achieved an average of 65% and a maximum of 81% validation accuracy for classifying three sleep labels even with a relatively small training sample of clinical visitors. The presence of two additional derived variables, local variability and range, have shown to strongly improve the model performance.DiscussionResults indicate that it is crucial to account for deep temporal dependency and assess local variability of the features. The post-hoc analysis of individual model performances on subjects’ demographic characteristics also suggest the need of including pathological samples in the training data in order to develop robust machine learning models that are capable of capturing normal and anomaly sleep patterns in the population.