bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reproducing Human Motor Adaptation in Spiking Neural Simulation and known Synaptic Learning Rules
Authors: Wu Yufei , Haar Shlomi , Faisal Aldo 
Published: June 2021

AbstractSensorimotor adaptation enables us to adjust our goal-oriented movements in response to external perturbations. These phenomena have been studied experimentally and computationally at the level of human and animals reaching movements, and have clear links to the cerebellum as evidenced by cerebellar lesions and neurodegeneration. Yet, despite our macroscopic understanding of the high-level computational mechanisms it is unclear how these are mapped and are implemented in the neural substrates of the cerebellum at a cellular-computational level. We present here a novel spiking neural circuit model of the sensorimotor system including a cerebellum which control physiological muscle models to reproduce behaviour experiments. Our cerebellar model is composed of spiking neuron populations reflecting cells in the cerebellar cortex and deep cerebellar nuclei, which generate motor correction to change behaviour in response to perturbations. The model proposes two learning mechanisms for adaptation: predictive learning and memory formation, which are implemented with synaptic updating rules. Our model is tested in a force-field sensorimotor adaptation task and successfully reproduce several phenomena arising from human adaptation, including well-known learning curves, aftereffects, savings and other multi-rate learning effects. This reveals the capability of our model to learn from perturbations and generate motor corrections while providing a bottom-up view for the neural basis of adaptation. Thus, it also shows the potential to predict how patients with specific types of cerebellar damage will perform in behavioural experiments. We explore this by in silico experiments where we selectively incapacitate selected cerebellar circuits of the model which generate and reproduce defined motor learning deficits.Author summaryA rich body of work in human motor neuroscience developed high-level computational theories of sensorimotor control, learning and adaptation. But there is a gap in understanding how this may be implemented and learn on the level of neurons, synapses and spikes. Conversely, studies of patients with cerebellar lesions or neurological disease highlight the essential role the cerebellum plays in our ability to perform motor learning. Yet, how these anatomical and molecular defects play out in terms of human movement have to date not been linked to a model that spans multiple level of biological organisation from neural circuits to reproducing human motor experiments. To address this gap, we present a spiking neuron of the sensorimotor system focused on the cerebellum, with which we can on the one side reproduce the high-level behaviour learning phenomena observed in healthy subjects, as well as quantitatively predicting the putative effects on human movement trajectories of cerebellar lesions implemented at the cellular level.
Migration pulsedness alters patterns of allele fixation and local adaptation in a mainland-island model
Authors: Aubree Flora , Lac Baptiste , Mailleret Ludovic , Calcagno Vincent 
Published: June 2021

AbstractGeneflow across populations is a critical determinant of population genetic structure, divergence and local adaptation. While evolutionary theory typically envisions geneflow as a continuous connection among populations, many processes make it fluctuating and intermittent. We analyze a mainland-island model in which migration occurs as recurrent “pulses”. We derive mathematical predictions regarding how the level of migration pulsedness affects the effective migration rate, for neutral and selected mainland alleles. We find that migration pulsedness can either decrease or increase geneflow, depending on the selection regime. Migration increases gene-flow for sufficiently (counter)selected alleles (s < s1), but reduces it otherwise. We provide a mathematical approximation of the threshold selection s1, which is verified in stochastic simulations. Migration pulsedness thus affects the fixation rate at different loci in opposite ways, in a way that cannot be described as a change in effective population size. We show that migration pulsedness would generally reduce the level of local adaptation, and introduce an additional genetic load: the “pulsedness load”. Our results indicate that migration pulsedness can be detrimental to the adaptation and persistence of small peripheral populations, with implications in management and conservation. Our results highlight temporally variable migration as an important process for evolutionary and population genetics.
Searching sequence databases for functional homologs using profile HMMs: how to set bit score thresholds?
Authors: Srivastava Jaya , Hembrom Ritu , Kumawat Ankita , Balaji Petety V. 
Published: June 2021

ABSTRACTMotivationUniProt and BFD databases together have 2.5 billion protein sequences. A large majority of these proteins have been electronically annotated. Automated annotation pipelines, vis-à-vis manual curation, have the advantage of scale and speed but are fraught with relatively higher error rates. This is because sequence homology does not necessarily translate to functional homology, molecular function specification is hierarchic and not all functional families have the same amount of experimental data that one can exploit for annotation. Consequently, customization of annotation workflow is inevitable to minimize annotation errors.ResultsWe discuss possible ways of customizing the search of sequence databases for functional homologs using profile HMMs. Choosing an optimal bit score threshold is a critical step in the application of HMMs, which is illustrated using four Case Studies; the single domain nucleotide sugar 6-dehydrogenase and lysozyme-C families, and SH3 and GT-A domains which are typically found as a part of multi-domain proteins. We also discuss the limitations of using profile HMMs for functional annotation and suggests some possible ways to partially overcome such limitations.Supplementary informationSupplementary_material containing Figures S1-S7 and Tables S1 and S2Supplementary_dataset.xlsx
Motility Control Through an Anti-Activation Mechanism in Agrobacterium tumefaciens
Authors: Alakavuklar Melene A. , Heckel Brynn C. , Stoner Ari M. , Stembel Joseph A. , Fuqua Clay 
Published: June 2021

SummaryMany bacteria can migrate from a free-living, planktonic state to an attached, biofilm existence. One factor regulating this transition in the facultative plant pathogen Agrobacterium tumefaciens is the ExoR-ChvG-ChvI system. Periplasmic ExoR regulates activity of the ChvG-ChvI two-component system in response to environmental stress, most notably low pH. ChvI impacts hundreds of genes, including those required for type VI secretion, virulence, biofilm formation, and flagellar motility. Previous studies revealed that activated ChvG-ChvI represses expression of most of class II and class III flagellar biogenesis genes, but not the master motility regulators visN, visR, and rem. In this study, we characterized the integration of the ExoR-ChvG-ChvI and VisNR-Rem pathways. We isolated motile suppressors of the non-motile ΔexoR mutant and thereby identified the previously unannotated mirA gene encoding a 76 amino acid protein. We report that the MirA protein interacts directly with the Rem DNA-binding domain, sequestering Rem and preventing motility gene activation. The ChvG-ChvI pathway activates mirA expression and elevated mirA is sufficient to block motility. This study reveals how the ExoR-ChvG-ChvI pathway prevents flagellar motility in A. tumefaciens. MirA is also conserved among other members of the Rhizobiales suggesting similar mechanisms of motility regulation.Plain language summaryAgrobacterium tumefaciens is a plant pathogen that responds to low pH, stressful environments via a complex two-component regulatory system. This regulatory system can completely inhibit bacterial locomotion by flagella, and in this study we define the mechanism for this inhibition and identify a novel small protein regulator that blocks flagellar gene expression.
Development and Validation of an LC-MS/MS Based Quantitative Assay for Marmoset Insulin
Authors: Goy Robinson W. , Shrestha Hemanta K. , Ziegler Toni E. , Dukes Natalie J. , Colman Ricki J. , Kapoor Amita 
Published: June 2021

ABSTRACTIntroductionInsulin is a peptide hormone that is secreted by the β cells of the pancreas and is essential to the metabolism of carbohydrates, fats, and proteins in the body. The marmoset insulin peptide is not homologous with human insulin and therefore commonly available assays do not work for this species. Due to the increasing popularity of marmoset research, a simple, specific assay for the quantitation of marmoset insulin is needed. This study aimed to develop and validate a bottom-up proteomic workflow with trypsin digestion and analysis using LC coupled with triple quadrupole mass spectrometry (LC-MS/MS).MethodsMarmoset serum proteins were subjected to denaturation, reduction, and enzymatic cleavage to extract a unique, 7 amino acid peptide for quantitation of marmoset insulin.Resolution of the peptide was achieved by LC-MS/MS using electrospray ionization operating in positive mode. Calibration was achieved by aliquot dilution of fully synthetic marmoset insulin tryptic peptide into macaque serum. A stable-isotope labeled (13C, 15N) synthetic marmoset insulin tryptic peptide was used as internal standard.ResultsThe assay was fully validated according to bioanalytical method validation guidelines for linearity, precision, and dilution linearity using purified marmoset insulin. The limit of detection was 4.28 pmol/L and the limit of quantitation was 8.62 pmol/L. Biological validation was achieved by comparison of samples previously run by radioimmunoassay and measurement of the marmoset insulin response to glucose via an oral glucose tolerance test (OGTT). The physiological range of marmoset insulin was shown to be 84.5 to 1222 pmol/L.ConclusionsThis paper presents a simple, reproducible method to measure marmoset insulin using LC-MS/MS.
Comparison of Transformations for Single-Cell RNA-Seq Data
Authors: Ahlmann-Eltze Constantin , Huber Wolfgang 
Published: June 2021

AbstractThe count table, a numeric matrix of genes × cells, is the basic input data structure in the analysis of single-cell RNA-seq data. A common preprocessing step is to adjust the counts for variable sampling efficiency and to transform them so that the variance is similar across the dynamic range. These steps are intended to make subsequent application of generic statistical methods more palatable. Here, we describe four transformation approaches based on the delta method, model residuals, inferred latent expression state, and factor analysis. We compare their strengths and weaknesses and find that the latter three have appealing theoretical properties. However, in benchmarks using simulated and real-world data, it turns out that a rather simple approach, namely, the logarithm with a pseudo-count followed by principal component analysis, performs as well or better than the more sophisticated alternatives.SoftwareThe R packagetransformGamPoiimplementing the delta method- and residuals-based variance-stabilizing transformations is available via Bioconductor. We provide an interactive website to explore the benchmark results atshiny-portal.embl.de/shinyapps/app/08_single-cell_transformation_benchmark.Contactconstantin.ahlmann@embl.de
Macrophage metabolism in the intestine is compartment-specific and regulated by the microbiota
Authors: Scott Nicholas A. , Lawson Melissa A. E. , Hodgetts Ryan James , Hall Lindsay J. , Mann Elizabeth R. 
Published: June 2021

ABSTRACTIntestinal macrophages play a vital role in the maintenance of gut homeostasis through signals derived from the microbiota. We previously demonstrated that microbial-derived metabolites can shape the metabolic functions of macrophages. Here, we show that antibiotic-induced disruption of the intestinal microbiota dramatically alters both the local metabolite environment, and the metabolic functions of macrophages in the colon. Broad-spectrum antibiotic administration in mice increased expression of the large neutral amino acid transporter and accordingly, amino acid uptake. Subsequently, antibiotic administration enhanced the metabolic functions of colonic macrophages, increasing phosphorylation of components of mammalian/mechanistic target of rapamycin (mTOR) signalling pathways, increasing expression of genes involved in glycolysis and oxidative phosphorylation (OXPHOS), increasing mitochondrial function and increased levels of ECAR and OCR as a direct measure of glycolysis and OXPHOS. Small bowel macrophages were less metabolically active than in the colon, with macrophage metabolism being independent of the microbiota. Finally, we reveal tissue resident Tim4+CD4+macrophages exhibit enhanced fatty acid uptake alongside reduced fatty acid synthesis compared to their recruited counterparts. Thus the microbiota shapes gut macrophage metabolism in a compartment-specific manner, with important implications for functions when monocyte recruitment and macrophage differentiation.
Methods forin situquantitative root biology
Authors: Pasternak Taras , Pérez-Pérez José Manuel 
Published: June 2021

ABSTRACTWhen dealing with plant roots, a multi-scale description of the functional root structure is needed. Since the beginning of XXI century, new devices like laser confocal microscopes have been accessible for coarse root structure measurements, including 3D reconstruction. Most researchers are familiar with using simple 2D geometry visualization that does not allow quantitatively determination of key morphological features from an organ-like perspective. We provide here a detailed description of the quantitative methods available for three-dimensional (3D) analysis of root features at single cell resolution, including root asymmetry, lateral root analysis, xylem and phloem structure, cell cycle kinetics, and chromatin determination. Quantitative maps of the distal and proximal root meristems are shown for different species, includingArabidopsis thaliana,Nicotiana tabacumandMedicago sativa. A 3D analysis of the primary root tip showed divergence in chromatin organization and cell volume distribution between cell types and precisely mapped root zonation for each cell file. Detailed protocols are also provided. Possible pitfalls in the usage of the marker lines are discussed. Therefore, researchers who need to improve their quantitative root biology portfolio can use them as a reference.
MELD-DNA: A new tool for capturing protein-DNA binding
Authors: Bauzá Antonio , Pérez Alberto 
Published: June 2021

AbstractHerein we present MELD-DNA, a novel computational approach to address the problem of protein-DNA structure prediction. This method addresses well-known issues hampering current computational approaches to bridge the gap between structural and sequence knowledge, such as large conformational changes in DNA and highly charged electrostatic interaction during binding. MELD-DNA is able to: i) sample multiple binding modes, ii) identify the preferred binding mode from the ensembles, and iii) provide qualitative binding preferences between DNA sequences. We expect the results presented herein will have impact in the field of biophysics (through new software development), structural biology (by complementing DNA structural databases) and supramolecular chemistry (by bringing new insights into protein-DNA interactions).
Persistent DNA damage rewires lipid metabolism and promotes histone hyperacetylation via MYS-1/Tip60
Authors: Hamsanathan Shruthi , Anthonymuthu Tamil , Mullett Steven J. , Wendell Stacy G. , Han Suhao , Shinglot Himaly , Siefken Ella , Sims Austin , Sen Payel , Pepper Hannah L , Snyder Nathaniel W. , Bayir Hulya , Kagan Valerian , Gurkar Aditi U. 
Published: June 2021

ABSTRACTNuclear DNA damage is intricately linked to cellular metabolism. However, the underlying mechanisms and full range of metabolic alterations that occur in response to persistent DNA damage are not well understood. Here, we use a DNA repair-deficient model of ERCC1-XPF in Caenorhabditis elegans (C. elegans), that accumulates physiologically relevant, endogenous DNA damage, to gain molecular insights on how persistent genotoxic stress drives biological aging. Using an integrated multi-omic approach, we discover that persistent genotoxic stress rewires lipid metabolism. In particular, nuclear DNA damage promotes mitochondrial β-oxidation and leads to a global loss of fat depots. This metabolic shift to β-oxidation generates acetyl-CoA and drives histone hyperacetylation. Concomitantly, we observe an associated change in gene expression of immune-effector and cytochrome (CYP) genes. We identify MYS-1, the ortholog of mammalian histone acetyltransferase TIP60, as a critical regulator of this metabolic-epigenetic axis. Moreover, we show that in response to persistent DNA damage, polyunsaturated fatty acids (PUFAs), especially arachidonic acid (AA) and AA-related lipid mediators are elevated. This elevation of PUFA species requires mys-1/Tip60. Together, these findings reveal that persistent nuclear DNA damage alters the metabolic-epigenetic axis to drive an immune-like response that can promote age-associated decline.
Macrosystem community assembly patterns are predicted by foundation tree species genetic connectivity and environment across the American Southwest
Authors: Bothwell Helen M. , Keith Arthur R. , Hull Julia B. , Cooper Hillary F. , Andrews Lela V. , Wehenkel Christian , Hultine Kevin R. , Gehring Catherine A. , Cushman Samuel A. , Whitham Thomas G. , Allan Gerard J. 
Published: June 2021

AbstractMacrosystems ecology is an emerging science that aims to integrate traditionally distinct disciplines to predict how hierarchical interacting processes influence the emergence of complex patterns across local to regional and global scales. Despite increased focus on cross-scale relationships and cross-disciplinary integration, few macroecology studies incorporate genetic-based processes. Here we used a community genetics approach to investigate the pattern-process relationships underlying the emergence of macroscale biodiversity patterns. We tested the hypothesis that environmental variation, geography, and genetic connectivity in a foundation tree species differentially predict associated community assembly patterns from local to continental scales. Using genome-wide SNP data, we assessed genetic connectivity as a function of genetic similarity and structure in Fremont cottonwood (Populus fremontii) across its distribution throughout the southwestern US and México. For the same trees, we measured community composition, diversity, and abundance of leaf modifying arthropods and sequenced targeted amplicons of twig fungal endophytes. Five key findings emerged. (1) We identified three primary and six secondary population genetic groups withinP. fremontii, which occupy distinct climate niches. (2) Both the leaf modifying arthropod and fungal endophyte communities were significantly differentiated across host tree ecotypes, with genetic distance among sampling locations explaining 13-17% of respective macroscale community structure. (3) For arthropods, environmental distance was the strongest driver of community similarity. (4) Conversely, host genetic connectivity was the most important contributor to macroscale endophyte community structure, with no significant contribution of environmental distance. (5) Furthermore, we observed a shift in the strength of interspecific relationships, with host genetics most strongly influencing associated communities at the intermediate population scale. Our findings suggest that genetic connectivity and environmental variation play integrated roles in macroscale community assembly, and their relative importance changes with scale. Thus, conservation genetic management of the diversity harbored within foundation species is vital for sustaining associated regional biodiversity.
Dynamics and variability in the pleiotropic effects of adaptation in laboratory budding yeast populations
Authors: Bakerlee Christopher W. , Phillips Angela M. , Nguyen Ba Alex N. , Desai Michael M. 
Published: June 2021

ABSTRACTEvolutionary adaptation to a constant environment is driven by the accumulation of mutations which can have a range of unrealized pleiotropic effects in other environments. These pleiotropic consequences of adaptation can influence the emergence of specialists or generalists, and are critical for evolution in temporally or spatially fluctuating environments. While many experiments have examined the pleiotropic effects of adaptation at a snapshot in time, very few have observed the dynamics by which these effects emerge and evolve. Here, we propagated hundreds of diploid and haploid laboratory budding yeast populations in each of three environments, and then assayed their fitness in multiple environments over 1000 generations of evolution. We find that replicate populations evolved in the same condition share common patterns of pleiotropic effects across other environments, which emerge within the first several hundred generations of evolution. However, we also find dynamic and environment-specific variability within these trends: variability in pleiotropic effects tends to increase over time, with the extent of variability depending on the evolution environment. These results suggest shifting and overlapping contributions of chance and contingency to the pleiotropic effects of adaptation, which could influence evolutionary trajectories in complex environments that fluctuate across space and time.