bluuebunny/crossref_metadata_2025_split huggingface dataset:
Normalisation of SARS-CoV-2 concentrations in wastewater: the use of flow, conductivity and CrAssphage
Authors: Langeveld Jeroen , Schilperoort Remy , Heijnen Leo , Elsinga Goffe , Schapendonk Claudia E.M. , Fanoy Ewout , de Schepper Evelien I.T. , Koopmans Marion P. G. , de Graaf Miranda , Medema Gertjan 
Published: December 2021

AbstractOver the course of the COVID-19 pandemic in 2020-2021, monitoring of SARS-CoV-2 RNA in wastewater has rapidly evolved into a supplementary surveillance instrument for public health. Short term trends (2 weeks) are used as a basis for policy and decision making on measures for dealing with the pandemic. Normalization is required to account for the varying dilution rates of the domestic wastewater, that contains the shedded virus RNA. The dilution rate varies due to runoff, industrial discharges and extraneous waters. Three normalization methods using flow, conductivity and CrAssphage, have been investigated on 9 monitoring locations between Sep 2020 and Aug 2021, rendering 1071 24-hour flow-proportional samples. In addition, 221 stool samples have been analyzed to determine the daily CrAssphage load per person. Results show that flow normalization supported by a quality check using conductivity monitoring is the advocated normalization method in case flow monitoring is or can be made available. Although Crassphage shedding rates per person vary greatly, the CrAssphage loads were very consistent over time and space and direct CrAssphage based normalization can be applied reliably for populations of 5600 and above.
Emergent multilevel selection in a simple spatial model of the evolution of altruism
Authors: Hermsen Rutger 
Published: December 2021

AbstractTheories on the evolutionary origins of altruistic behavior have a long history and have become a canonical part of the theory of evolution. Nevertheless, the mechanisms that allow altruism to appear and persist are still incompletely understood. It is well known, however, that the spatial structure of populations is an important determinant. In both theoretical and experimental studies, much attention has been devoted to populations that are subdivided into discrete groups. Such studies typically imposed the structure and dynamics of the groups by hand. Here, we instead present a simple individual-based model in which altruistic organisms spontaneously self-organize into spatially separated colonies that themselves reproduce by binary fission and hence behave as Darwinian entities in their own right. Using software to automatically track the rise and fall of colonies, we are able to apply formal theory on multilevel selection and thus quantify the within- and among-group dynamics. This reveals that individual colonies inevitably succumb to defectors in a within-colony “tragedy of the commons”. Even so, altruism persists in the population because more altruistic colonies reproduce more frequently and drive less altruistic ones to extinction. Evidently, the colonies promote the selection of altruism but in turn depend on altruism for their existence; the selection of altruism hence involves a kind of evolutionary bootstrapping. The emergence of the colonies also depends crucially on the length scales of motility, altruism, and competition. This reconfirms the general relevance of these scales for social evolution, but also stresses that their impact can only be understood fully in the light of the emergent eco-evolutionary spatial patterns. The results also suggest that emergent spatial population patterns can function as a starting point for transitions of individuality.
Spatiotemporal NF-κB dynamics encodes the position, amplitude and duration of local immune inputs
Authors: Son Minjun , Frank Tino , Holst-Hansen Thomas , Wang Andrew , Junkin Michael , Kashaf Sara S , Trusina Ala , Tay Savaş 
Published: December 2021

SummaryInfected cells communicate through secreted signaling molecules like cytokines, which inform nearby cells about the type, severity and location of pathogens. How differences in cytokine secretion affect inflammatory signaling over space and time, and how responding cells decode information from propagating cytokine signals are not understood. By computationally and experimentally studying NF-κB dynamics in co-cultures of signal sending cells (macrophages) and receiving cells (fibroblasts), we found that cytokine signals are transmitted by wave-like propagation of NF-κB activity and create well-defined cellular activation zones in a responding cell population. Remarkably, NF-κB dynamics in responding cells can simultaneously encode information about cytokine dose, duration, and distance to the cytokine source. Spatially-resolved transcriptional analysis revealed that responding cells transmit local cytokine information to distance specific pro-inflammatory gene expression patterns, creating “gene expression zones” in the population. Despite single-cell variability, the size and duration of the signaling zone is tightly controlled by the macrophage cytokine secretion profile. Our results highlight how macrophages tune their cytokine secretion dynamics to control signal transmission distance, and how NF-κB interprets these signals to coordinate inflammatory response in space and time.
Euler method can outperform more complex ODE solvers in the numerical implementation of the Izhikevich artificial Spiking Neuron Model given the allocated FLOPS
Authors: de Alteriis Giuseppe , Cataldo Enrico , Mazzoni Alberto , Oddo Calogero Maria 
Published: December 2021

AbstractThe Izhikevich artificial spiking neuron model is among the most employed models in neuromorphic engineering and computational neuroscience, due to the affordable computational effort to discretize it and its biological plausibility. It has been adopted also for applications with limited computational resources in embedded systems. It is important therefore to realize a compromise between error and computational expense to solve numerically the model’s equations. Here we investigate the effects of discretization and we study the solver that realizes the best compromise between accuracy and computational cost, given an available amount of Floating Point Operations per Second (FLOPS). We considered three fixed-step solvers for Ordinary Differential Equations (ODE), commonly used in computational neuroscience: Euler method, the Runge-Kutta 2 method and the Runge-Kutta 4 method. To quantify the error produced by the solvers, we used the Victor Purpura spike train Distance from an ideal solution of the ODE. Counterintuitively, we found that simple methods such as Euler and Runge Kutta 2 can outperform more complex ones (i.e. Runge Kutta 4) in the numerical solution of the Izhikevich model if the same FLOPS are allocated in the comparison. Moreover, we quantified the neuron rest time (with input under threshold resulting in no output spikes) necessary for the numerical solution to converge to the ideal solution and therefore to cancel the error accumulated during the spike train; in this analysis we found that the required rest time is independent from the firing rate and the spike train duration. Our results can generalize in a straightforward manner to other spiking neuron models and provide a systematic analysis of fixed step neural ODE solvers towards an accuracy-computational cost tradeoff.
Insights into energy balance dysregulation from a mouse model of methylmalonic aciduria
Authors: Lucienne Marie , Gerlini Raffaele , Rathkolb Birgit , Calzada-Wack Julia , Forny Patrick , Wueest Stephan , Kaech Andres , Traversi Florian , Forny Merima , Bürer Céline , Aguilar-Pimentel Antonio , Irmler Martin , Beckers Johannes , Sauer Sven , Kölker Stefan , Dewulf Joseph P. , Bommer Guido T. , Hoces Daniel , Gailus-Durner Valerie , Fuchs Helmut , Rozman Jan , Froese D Sean , Baumgartner Matthias R. , de Angelis Martin Hrabě 
Published: December 2021

AbstractInherited disorders of mitochondrial metabolism, including isolated methylmalonic aciduria (MMAuria), present unique challenges to energetic homeostasis by disrupting energy producing pathways. To better understand global responses to energy shortage, we investigated a hemizygous mouse model of methylmalonyl-CoA mutase (Mmut) type MMAuria. We found Mmut mutant mice to have reduced appetite, energy expenditure and body mass compared to littermate controls, along with a relative reduction in lean mass but increase in fat mass. Brown adipose tissue showed a process of whitening, in line with lower body surface temperature and lesser ability to cope with cold challenge. Mutant mice had dysregulated plasma glucose, delayed glucose clearance and a lesser ability to regulate energy sources when switching from the fed to fasted state, while liver investigations indicated metabolite accumulation and altered expression of peroxisome proliferator-activated receptor and Fgf21-controlled pathways. Together, these indicate hypometabolism, energetic inflexibility and increased stores at the expense of active tissue as energy shortage consequences.
Thymosin β4 preserves vascular smooth muscle phenotype in atherosclerosis via regulation of Low Density Lipoprotein Related Protein 1 (LRP1)
Authors: Munshaw Sonali , Redpath Andia , Pike Benjamin , Smart Nicola 
Published: December 2021

AbstractObjectiveAtherosclerosis is a progressive, degenerative vascular disease and a leading cause of morbidity and mortality. In response to endothelial damage, platelet derived growth factor (PDGF)-BB induced phenotypic modulation of medial smooth muscle cells (VSMCs) promotes atherosclerotic lesion formation and destabilisation of the vessel wall. VSMC sensitivity to PDGF-BB is determined by endocytosis of Low density lipoprotein receptor related protein 1 (LRP1)-PDGFRβ complexes to balance receptor recycling with lysosomal degradation. Consequently, LRP1 is implicated in various arterial diseases. Having identified Tβ4 as a regulator of LRP1-mediated endocytosis to protect against aortic aneurysm, we sought to determine whether Tβ4 may additionally function to protect against atherosclerosis, by regulating LRP1-mediated growth factor signalling.Approach and ResultsBy single cell transcriptomic analysis, Tmsb4x, encoding Tβ4, strongly correlated with contractile gene expression and was significantly down-regulated in cells that adopted a modulated phenotype in atherosclerosis. We assessed susceptibility to atherosclerosis of global Tβ4 knockout mice using the ApoE-/- hypercholesterolaemia model. Inflammation, elastin integrity, VSMC phenotype and signalling were analysed in the aortic root and descending aorta. Tβ4KO; ApoE-/- mice develop larger atherosclerotic plaques than control mice, with medial layer degeneration characterised by accelerated VSMC phenotypic modulation. Defects in Tβ4KO; ApoE-/- mice phenocopied those in VSMC-specific LRP1 nulls and, moreover, were underpinned by hyperactivated LRP1-PDGFRβ signalling.ConclusionsWe identify an atheroprotective role for endogenous Tβ4 in maintaining differentiated VSMC phenotype via LRP1-mediated PDGFRβ signalling.
Rapid and efficient adaptation of the dTAG system in mammalian development reveals stage specific requirements of NELF
Authors: Abuhashem Abderhman , Hadjantonakis Anna-Katerina 
Published: December 2021

SUMMARYTargeted protein degradation methods offer a unique avenue to assess a protein’s function in a variety of model systems. Recently, these approaches have been applied to mammalian cell culture models, enabling unprecedented temporal control of protein function. However, the efficacy of these systems at the tissue and organismal levels in vivo is not well established. Here, we tested the functionality of the degradation tag (dTAG) degron system in mammalian development. We generated a homozygous knock-in mouse with a FKBPF36V tag fused to Negative elongation factor b (Nelfb) locus, a ubiquitously expressed protein regulator of transcription. In the first validation of targeted endogenous protein degradation across mammalian development, we demonstrate that irrespective of the route of administration the dTAG system is safe, rapid, and efficient in embryos from the zygote to midgestation stages. Additionally, acute early depletion of NELFB revealed a specific role in zygote-to-2-cell development and Zygotic Genome Activation (ZGA).HIGHLIGHTSgenetically engineered mouse model harboring a FKBPF36V knock-in to evaluate kinetics and efficacy of the dTAG degron system in vivosystem is non-toxic, and allows acute and efficient degradation of a FKBPF36V- tagged endogenous protein during in utero embryo developmentsystem nables fine temporal degradation and reversibility of depletion across embryonic stagesstage-specific depletion reveals a role for NELFB during mouse ZGA
Rolling Circle RNA Synthesis Catalysed by RNA
Authors: Kristoffersen Emil Laust , Burman Matthew , Noy Agnes , Holliger Philipp 
Published: December 2021

AbstractRNA-catalysed RNA replication is widely considered a key step in the emergence of life’s first genetic system. However, RNA replication can be impeded by the extraordinary stability of duplex RNA products, which must be dissociated for re-initiation of the next replication cycle. Here we have explored rolling circle synthesis (RCS) as a potential solution to this strand separation problem. RCS on small circular RNAs - as indicated by molecular dynamics simulations - induces a progressive build-up of conformational strain with destabilisation of nascent strand 5’ and 3’ ends. At the same time, we observe sustained RCS by a triplet polymerase ribozyme on small circular RNAs over multiple orbits with strand displacement yielding concatemeric RNA products. Furthermore, we show RCS of a circular Hammerhead ribozyme capable of self-cleavage and re-circularisation. Thus, all steps of a viroid-like RNA replication pathway can be catalysed by RNA alone. Our results have implications for the emergence of RNA replication and for understanding the potential of RNA to support complex genetic processes.
Microglial MorphOMICs unravel region- and sex-dependent morphological phenotypes from postnatal development to degeneration
Authors: Colombo Gloria , Cubero Ryan John A. , Kanari Lida , Venturino Alessandro , Schulz Rouven , Scolamiero Martina , Agerberg Jens , Mathys Hansruedi , Tsai Li-Huei , Chachólski Wojciech , Hess Kathryn , Siegert Sandra 
Published: December 2021

AbstractMicroglia contribute to tissue homeostasis in physiological conditions with environmental cues influencing their ever-changing morphology. Strategies to identify these changes usually involve user-selected morphometric features, which, however, have proved ineffective in establishing a spectrum of context-dependent morphological phenotypes. Here, we have developed MorphOMICs, a topological data analysis approach to overcome feature-selection-based biases and biological variability. We extracted a spatially heterogeneous and sexually-dimorphic morphological phenotype for seven adult brain regions, with ovariectomized females forming their own distinct cluster. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration models, 5xFAD and CK-p25. Females show an earlier morphological shift in the immediately-affected brain regions. Finally, we demonstrate that both the primary- and the short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs maps microglial morphology into a spectrum of cue-dependent phenotypes in a minimally-biased and semi-automatic way.
Detecting DNA of novel fungal pathogens using ResNets and a curated fungi-hosts data collection
Authors: Bartoszewicz Jakub M. , Nasri Ferdous , Nowicka Melania , Renard Bernhard Y. 
Published: December 2021

AbstractBackgroundEmerging pathogens are a growing threat, but large data collections and approaches for predicting the risk associated with novel agents are limited to bacteria and viruses. Pathogenic fungi, which also pose a constant threat to public health, remain understudied. Relevant data remains comparatively scarce and scattered among many different sources, hindering the development of sequencing-based detection workflows for novel fungal pathogens. No prediction method working for agents across all three groups is available, even though the cause of an infection is often difficult to identify from symptoms alone.ResultsWe present a curated collection of fungal host range data, comprising records on human, animal and plant pathogens, as well as other plant-associated fungi, linked to publicly available genomes. We show that it can be used to predict the pathogenic potential of novel fungal species directly from DNA sequences with either sequence homology or deep learning. We develop learned, numerical representations of the collected genomes and visualize the landscape of fungal pathogenicity. Finally, we train multi-class models predicting if next-generation sequencing reads originate from novel fungal, bacterial or viral threats.ConclusionsThe neural networks trained using our data collection enable accurate detection of novel fungal pathogens. A curated set of over 1,400 genomes with host and pathogenicity metadata supports training of machine learning models and sequence comparison, not limited to the pathogen detection task.AvailabilityThe data, models and code are hosted at https://zenodo.org/record/5846345, https://zenodo.org/record/5711877, and https://gitlab.com/dacs-hpi/deepac.
Functional analysis of the polar amino acid in the TatA transmembrane helix
Authors: Hao Binhan , Zhou Wenjie , Theg Steven M. 
Published: December 2021

AbstractThe twin-arginine translocation (Tat) pathway utilizes the proton-motive force (pmf) to transport folded proteins across cytoplasmic membranes in bacteria and archaea, as well as across the thylakoid membrane in plants and the inner membrane in mitochondria. In most species, the minimal components required for Tat activity consist of three subunits, TatA, TatB, and TatC. Previous studies have shown that a polar amino acid is present at the N-terminus of the TatA transmembrane helix (TMH) across many different species. In order to systematically assess the functional importance of this polar amino acid in the TatA TMH in Escherichia coli, a complete set of 19-amino-acid substitutions was examined. Unexpectedly, although being preferred overall, our experiments suggest that the polar amino acid is not necessary for a functional TatA. Hydrophobicity and helix stabilizing properties of this polar amino acid were found to be highly correlated with the Tat activity. Specifically, change in charge status of the amino acid side chain due to pH resulted in a shift in hydrophobicity, which was demonstrated to impact the Tat transport activity. Furthermore, a four-residue motif at the N-terminus of the TatA TMH was identified by sequence alignment. Using a biochemical approach, the N-terminal motif was found to be functionally significant, with evidence indicating a potential role in the preference for utilizing different pmf components. Taken together, these findings yield new insights into the functionality of TatA and its potential role in the Tat transport mechanism.
Heterogeneous Tissue Modulus Improved Prediction of Mechanical Behavior in Osteoporotic Vertebral Cancellous Bone
Authors: Cox Jason M. , Smith Joshua D. , van der Meulen Marjolein C. H. , Cole Jacqueline H. 
Published: December 2021

AbstractThe structural integrity of cancellous bone, which is essential to its skeletal load-bearing capacity, is governed chiefly by apparent density, trabecular architecture, and tissue material properties. Metabolic bone disorders such as osteoporosis can affect each of these factors, resulting in compromised load-bearing function and fracture. While the impact of apparent density and architecture on bone structural behavior is well-documented, much less is known about the influence of tissue material properties, particularly in osteoporotic bone. In this work, we isolated the influence of tissue modulus on normal and osteoporotic cancellous bone structural integrity, indicated by the apparent elastic modulus under uniaxial compression and patterns of internal tissue strain. Finite element (FE) models derived from 3D micro-computed tomography images were compared to physical testing data of the same samples. Three sets of FE models with increasing material detail were studied: 1) universal tissue elastic modulus (20 GPa), 2) specimen-specific average tissue modulus, and 3) heterogeneous tissue modulus. Applying a universal modulus resulted in overestimation of osteoporotic bone apparent modulus; applying specimen-specific material properties, either as a single average tissue modulus or heterogeneous distribution of tissue moduli, prevented significant apparent modulus overestimation. The greatest improvement in apparent modulus prediction resulted from incorporating a specimen-specific average tissue modulus, though using a specimen-specific heterogeneous tissue modulus provided the most reliable prediction of apparent modulus overall. In addition, median element strain in heterogeneous models also trended lower than in homogeneous models. This finding suggests that heterogeneous material properties may play a role in protective strain-concentrating mechanisms observed in cancellous bone. We conclude that future work exploring trabecular bone mechanics through finite element analysis should incorporate specimen-specific average tissue modulus at a minimum, but heterogeneous tissue modulus is recommended to maximize the functional similarity of boneinsilico with bonein vivo.
Structural predictions of the SNX-RGS proteins suggest they belong to a new class of lipid transfer proteins
Authors: Paul Blessy , Weeratunga Saroja , Tillu Vikas A. , Hariri Hanaa , Henne W. Mike , Collins Brett M. 
Published: December 2021

SummaryRecent advances in protein structure prediction using machine learning such as AlphaFold2 and RosettaFold presage a revolution in structural biology. Genome-wide predictions of protein structures are providing unprecedented insights into their architecture and intradomain interactions, and applications have already progressed towards assessing protein complex formation. Here we present detailed analyses of the sorting nexin proteins that contain regulator of G-protein signalling domains (SNX-RGS proteins), providing a key example of the ability of AlphaFold2 to reveal novel structures with previously unsuspected biological functions. These large proteins are conserved in most eukaryotes and are known to associate with lipid droplets (LDs) and sites of LD-membrane contacts, with key roles in regulating lipid metabolism. They possess five domains, including an N-terminal transmembrane domain that anchors them to the endoplasmic reticulum, an RGS domain, a lipid interacting phox homology (PX) domain and two additional domains named the PXA and PXC domains of unknown structure and function. Here we report the crystal structure of the RGS domain of sorting nexin 25 (SNX25) and show that the AlphaFold2 prediction closely matches the experimental structure. Analysing the full-length SNX-RGS proteins across multiple homologues and species we find that the distant PXA and PXC domains in fact fold into a single unique structure that notably features a large and conserved hydrophobic pocket. The nature of this pocket strongly suggests a role in lipid or fatty acid binding, and we propose that these molecules represent a new class of conserved lipid transfer proteins.