bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Empiricist’s Guide to Modern Coexistence Theory for Competitive Communities
Authors: Godwin Casey M. , Chang Feng-Hsun , Cardinale Bradley 
Published: May 2019

AbstractWhile most ecological theories have historically invoked niche differences as the primary mechanism allowing species coexistence, we now know that species coexistence in competitive communities actually depends on the balance of two opposing forces: niche differences (ND) that determine how species limit their own growth rate versus that of their competitor, and relative fitness differences (RFD) that establish competitive hierarchies among species. Several different empirical methods have been proposed for measuring ND and RFD in order to make predictions about coexistence of species, yet it remains unclear which method(s) are appropriate for a given empirical study and whether or not those methods actually yield the same information. Here we summarize and compare five different empirical methods, with the aim of providing a practical guide for empiricists who want to predict coexistence among species. These include two phenomenological methods that estimate ND and RFD based on observing competitive interactions among species; two mechanistic methods that estimate ND and RFD based solely on information about species’ resource requirements; and a fifth method that does not yield ND and RFD but describes the impacts of those forces within communities. Based on the specific requirements, limitations, and assumptions of each approach, we offer a series of decision steps that can be used to determine which method(s) are best for a given study system. In particular, we show there are important tradeoffs between mechanistic methods, which require detailed understanding of species niches and physiology but are more tractable experimentally, and phenomenological methods which do not require this detailed information but can be impractical for some study designs. Importantly, we show that although each method can be used to estimate ND and RFD, the methods do not always yield the same values. Therefore we caution against future syntheses that compile these estimates from different empirical studies. Finally, we highlight several areas where modern coexistence theory could benefit from additional empirical work.
Single-Cell, Human Sperm Transcriptomes and Variants from Fathers of Autistic and Healthy Children
Authors: Tomoiaga Delia , Aguiar-Pulido Vanessa , Shrestha Shristi , Feinstein Paul , Levy Shawn E. , Rosenfeld Jeffrey A. , Mason Christopher E. 
Published: May 2019

AbstractThe human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. This is especially relevant for diseases such as Autism Spectrum Disorders (ASD), which have been correlated with advance paternal age. Historically, most studies of sperm have focused on the assessment of a bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10X Chromium single cell sequencing technology, we have assessed the RNA from >65,000 single sperm cells across 6 donors (scsperm-RNA-seq), including two of whom have autistic children and four that do not. Using multiple RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Moreover, by comparing the two groups, we have found expression changes that can separate out the two sets of donors. Finally, through our novel variant calling from single-cell RNA-seq methods, we have shown that we can detect mutation rates in sperm from ASD donors that is distinct from the controls, highlighting this method as a new means to characterize ASD risk.
Systematic interrogation of the distinct metabolic potential in gut microbiomes of inflammatory bowel disease patients with dysbiosis
Authors: Heinken Almut , Thiele Ines 
Published: May 2019

AbstractThe human gut microbiome plays an important role in human health. In order to investigate changes in metabolic activity associated with dysbiotic microbiomes, we retrieved strain-level relative abundances from metagenomics data from a cohort of pediatric Crohn’s Disease patients with and without dysbiosis, and healthy control children to construct a personalized microbiome model for each sample using the AGORA resource of genome-scale gut microbial reconstructions. Subsequently, we systematically profiled each individual microbiome by predicting the quantitative biosynthesis potential for all secreted metabolites as well as the strain-level contributions to each metabolite in each individual microbiome. The predicted fecal metabolomes and strain-metabolite contributions of microbiomes from patients with dysbiosis were distinct from healthy controls and patients without dysbiosis. Finally, we validated the predicted amino acid production profiles against fecal metabolomic measurements. Taken together, we presented an efficient, scalable, tractable computational approach to systematically interrogate the metabolic potential of individual microbiomes.
Hermes: an ensemble machine learning architecture for protein secondary structure prediction
Authors: Bliss Larry , Pascoe Ben , Sheppard Samuel K 
Published: May 2019

AbstractMotivationProtein structure predictions, that combine theoretical chemistry and bioinformatics, are an increasingly important technique in biotechnology and biomedical research, for example in the design of novel enzymes and drugs. Here, we present a new ensemble bi-layered machine learning architecture, that directly builds on ten existing pipelines providing rapid, high accuracy, 3-State secondary structure prediction of proteins.ResultsAfter training on 1348 solved protein structures, we evaluated the model with four independent datasets: JPRED4 - compiled by the authors of the successful predictor with the same name, and CASP11, CASP12 & CASP13 - assembled by the Critical Assessment of protein Structure Prediction consortium who run biannual experiments focused on objective testing of predictors. These rigorous, pre-established protocols included 7-fold cross-validation and blind testing. This led to a mean Hermes accuracy of 95.5%, significantly (p<0.05) better than the ten previously published models analysed in this paper. Furthermore, Hermes yielded a reduction in standard deviation, lower boundary outliers, and reduced dependency on solved structures of homologous proteins, as measured by NEFF score. This architecture provides advantages over other pipelines, while remaining accessible to users at any level of bioinformatics experience.Availability and ImplementationThe source code for Hermes is freely available at:https://github.com/HermesPrediction/Hermes. This page also includes the cross-validation with corresponding models, and all training/testing data presented in this study with predictions and accuracy.
Intragenomic variability and extended sequence patterns in the mutational signature of ultraviolet light
Authors: Lindberg Markus , Boström Martin , Elliott Kerryn , Larsson Erik 
Published: May 2019

ABSTRACTMutational signatures can reveal properties of underlying mutational processes and are important when assessing signals of selection in cancer. Here we describe the sequence characteristics of mutations induced by ultraviolet (UV) light, a major mutagen in several human cancers, in terms of extended (longer than trinucleotide) patterns as well as variability of the signature across chromatin states. Promoter regions display a distinct UV signature with reduced TCG>TTG transitions, and genome-wide mapping of UVB-induced DNA photoproducts (pyrimidine dimers) showed that this may be explained by decreased damage formation at hypomethylated promoter CpG sites. Further, an extended signature model encompassing additional information from longer patterns improves modeling of UV mutation rate, which may enhance discrimination between drivers and passenger events. Our study presents a refined picture of the UV signature and underscores that the characteristics of a single mutational process may vary across the genome.
A Hotspot Atop: Rivers of the Guyana Highlands Hold High Diversity of Endemic Pencil Catfish
Authors: Paz Holden J. , Hayes Malorie M. , Stout Carla C. , Werneke David C. , Armbruster Jonathan W. 
Published: May 2019

ABSTRACTAimThe Pakaraima Mountains are an ancient mountain range along the borders of Guyana, Brazil, and Venezuela. The high plateau is drained by multiple river systems in all directions. Although hypotheses have been presented for the biogeographic relationships of lowland rivers, the interconnectivity of rivers on the top of the plateau is unknown. With multiple complex rivers in a small, upland area we predicted a high level of endemism for stream fishes and complex biogeographic relationships. We explore this with the incredibly diverse pencil catfish genusTrichomycterus. Only two species are known from the region. In this study, we 1) confirm the discovery of multiple endemicTrichomycterusspecies in the region, 2) determine the phylogenetic placement of our samples to posit biogeographical scenarios, and 3) provide clarification for the identification ofT. guianensisbased on morphology.LocationPakaraima Mountains, a part of the Guiana Shield in Guyana, South AmericaTaxonPencil catfish genusTrichomycterusMethodsUsing collections from recent expeditions to the Pakaraima Mountains of Guyana, we amplified three mitochondrial (16S, COI, and cytb) and two nuclear markers (myh6 and RAG2). We constructed individual gene trees as well as a concatenated tree to determine the placement of these taxa within theTrichomycterusof the Trans-andean/Amazonian clade.ResultsOur results identify six unique lineages in the highlands of Guyana. Only two species,Trichomycterus guianensisandT. conradi, were previously known to science.Main ConclusionsThe Pakaraima Mountains of South America are a region of high endemism, as demonstrated here inTrichomycteruscatfishes. We find two species occupying multiple basins, suggesting that Pakaraima streams either maintain or had some degree of recent connectivity. We identify six endemic lineages ofTrichomycterusfrom the highlands of the Pakaraima Mountains. The upper portions of the study rivers have been connected either through surface flow or by stream capture. Both processes have occurred on multiple time scales and are independent of the patterns seen in the lowlands.
Small molecule inhibitors of G9a reactivate the maternal PWS genes in Prader-Willi-Syndrome patient derived neural stem cells and differentiated neurons
Authors: Wu Hao , Ng Carrie , Villegas Vivian , Chamberlain Stormy , Cacace Angela , Wallace Owen 
Published: May 2019

Abstract/SummaryPatients with Prader-Willi-Syndrome (PWS) display intellectual impairment, hyperphagia, and various behavioral problems during childhood that converge on a neurologic deficit. The majority of PWS patients have genetic deletions of the paternal 15q11–q13 chromosomal region, with their maternal PWS locus intact but epigenetically silenced by hypermethylation and repressive histone modulation of the PWS imprinting center (PWS-IC). Inhibition of the euchromatin histone methyltransferase G9a by small molecules has been recently reported to reactivate PWS genes in patient fibroblasts and a mouse model. However, it is unknown if inhibition of G9a could have similar effect in human PWS neural cells, the cell types that have direct pathophysiological relevance to PWS. Here, we use neural progenitor cells (NPCs) and cortical excitatory neurons derived from a patient iPSC to model PWS, and quantitatively profile the expression of PWS genes using a NanoString panel. We demonstrated that the methylation of the PWS-IC is stable during neuronal lineage conversion, and that the maternal PWS genes remain silenced in PWS NPCs and neurons. Multiple small molecule inhibitors of G9a activate maternal PWS genes in a dose dependent manner in both NPCs and neurons. In addition, G9a inhibitors induceGNRH1andHTR2C, two neuronal specific genes that contribute to PWS pathology in neurons. Interestingly, distinct from 5-Azacytidine, G9a inhibition does not induce methylation changes of the maternal PWS-IC, indicating that disruption of the histone repressive complex alone is sufficient to drive an open chromatin state at the PWS-IC that leads to partial reactivation of PWS genes.HighlightsModeling PWS disease in a dish using patient derived NPCs and neuronsG9a inhibition activates maternal PWS genes in patient-derived neural cellsG9a inhibition activates maternalSNORD116and other PWS genes in patient-derived neuronsInhibition of G9a induces PWS downstream genesGNRH1andHTR2Cin PWS neurons
Three points of consideration before testing the effect of patch connectivity on local species richness: patch delineation, scaling and variability of metrics
Authors: Laroche Fabien , Balbi Manon , Grébert Théophile , Jabot Franck , Archaux Frédéric 
Published: May 2019

AbstractThe Theory of Island Biogeography (TIB) promoted the idea that species richness within sites depends on site connectivity, i.e. its connection with surrounding potential sources of immigrants. TIB has been extended to a wide array of fragmented ecosystems, beyond archipelagoes, surfing on the analogy between habitat patches and islands and on the patch-matrix framework. However, patch connectivity often little contributes to explaining species richness in empirical studies. Before interpreting this trend as questioning the broad applicability of TIB principles, one first needs a clear identification of methods and contexts where strong effects of patch structural connectivity are likely to occur. Here, we use spatially explicit simulations of neutral metacommunities to show that patch connectivity effect on local species richness is maximized under a set of specific conditions: (i) patch delineation should be fine enough to ensure that no dispersal limitation occurs within patches, (ii) patch connectivity indices should be scaled according to target organisms’ dispersal distance and (iii) the habitat amount around sampled sites (within a distance adapted to organisms’ dispersal) should be highly variable. When those three criteria are met, the absence of an effect of connectivity on species richness should be interpreted as contradicting TIB hypotheses
Optogenetically-Induced Population Discharge Threshold as a Sensitive Measure of Network Excitability
Authors: Klorig D.C. , Alberto G.E. , Smith T. , Godwin D.W. 
Published: May 2019

AbstractNetwork excitability is governed by synaptic efficacy, intrinsic excitability, and the circuitry in which these factors are expressed. The complex interplay between these factors determines how circuits function, and at the extreme, their susceptibility to seizure. We have developed a novel optogenetic intensity response procedure that provides a sensitive, quantitative estimate of network excitability. By combining optogenetic stimulation of the hippocampus with chronic multi-site recordings in peri-hippocampal structures of awake behaving mice, we induced abnormal network-wide epileptiform population discharges (PD) that were nearly indistinguishable from spontaneously occurring interictal spikes. By systematically varying light intensity, and therefore the magnitude of the optogenetically-mediated current, we generated intensity-response curves using the probability of PD as the dependent variable. This probability curve was well fit by a Boltzmann function, from which we calculated the intensity that produces a half-maximal probability of discharge (I50). This novel metric, the I50, is correlated with the optogenetic after-discharge threshold (oADT) in the same mice. Manipulations known to increase excitability, such as sub-convulsive doses (20 mg/kg) of the chemoconvulsant pentylenetetrazol (PTZ), produced a leftward shift in the curve compared to baseline. The anti-epileptic drug levetiracetam (40 mk/kg), in combination with PTZ, produced a rightward shift. Optogenetically-induced population discharge threshold (oPDT) baselines were stable over time, suggesting the metric is appropriate for within-subject experimental designs with multiple pharmacological manipulations. The oPDT is a sensitive measure of subconvulsive network excitability, with broad applicability to a number of areas of investigation.Significance StatementNetwork excitability is carefully regulated by homeostatic mechanisms in the brain in order to maintain optimal functional conditions. Abnormal excitability is associated with a number of neurological disorders including epilepsy. Excitability can be measured in single cellsin vitro, but it is difficult to extrapolate from these values to the functional impact on the network as a whole. Epileptiform discharges are network wide events that represent a distinct transition from normal to abnormal functional modes. We developed a new technique that uses light intensity-response curves to precisely determine the threshold for this transition as a surrogate measure of network excitability and seizure susceptibility.
cRacle: R Tools for Estimating Climate from Vegetation
Authors: Harbert Robert S. , Baryiames Alex A. 
Published: May 2019

ABSTRACTPremise of the studyThe Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE) method for the estimation of climate from vegetation is a robust set of modeling tools for estimating climate and paleoclimate that makes use of large repositories of biodiversity data and open-access R software.MethodsHere we implement a new R library for the estimation of climate from vegetation. The ‘cRacle’ library implements functions for data access, aggregation, and models to estimate climate from plant community composition. ‘cRacle’ is modular and features many best-practice features.ResultsPerformance tests using modern vegetation survey data from North and South America shows that CRACLE outperforms alternative methods. CRACLE estimates of mean annual temperature (MAT) are usually within 1°C of the actual when optimal model parameters are used. Generalized Boosted Regression (GBR) model correction is also shown here to improve on CRACLE models by reducing bias.DiscussionCRACLE provides accurate estimates of climate from modern plant communities. Non-parametric CRACLE modeling coupled to GBR model correction produces the most accurate results to date. The ‘cRacle’ R library streamlines the estimation of climate from plant community data, and will make this modeling more accessible to a wider range of users.
BERMUDA: A novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes
Authors: Wang Tongxin , Johnson Travis S , Shao Wei , Lu Zixiao , Helm Bryan R , Zhang Jie , Huang Kun 
Published: May 2019

AbstractTo fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for cell lineation and identifyingbona fidetranscriptional signals, it is necessary to combine data from multiple experiments. We presentBERMUDA(Batch-Effect ReMoval Using Deep Autoencoders) — a novel transfer-learning-based method for batch-effect correction in scRNA-seq data.BERMUDAeffectively combines different batches of scRNA-seq data with vastly different cell population compositions and amplifies biological signals by transferring information among batches. We demonstrate thatBERMUDAoutperforms existing methods for removing batch effects and distinguishing cell types in multiple simulated and real scRNA-seq datasets.
Neuron subtype-specific effector gene expression in the Motor Ganglion of Ciona
Authors: Gibboney Susanne , Kim Kwantae , Johnson Christopher J. , Orvis Jameson , Martínez-Feduchi Paula , Lowe Elijah K. , Sharma Sarthak , Stolfi Alberto 
Published: May 2019

AbstractThe central nervous system of theCionalarva contains only 177 neurons. The precise regulation of neuron subtype-specific morphogenesis and differentiation observed in during the formation of this minimal connectome offers a unique opportunity to dissect gene regulatory networks underlying chordate neurodevelopment. Here we compare the transcriptomes of two very distinct neuron types in the hindbrain/spinal cord homolog ofCiona, the Motor Ganglion (MG): the Descending decussating neuron (ddN, proposed homolog of Mauthner Cells in vertebrates) and the MG Interneuron 2 (MGIN2). Both types are invariantly represented by a single bilaterally symmetric left/right pair of cells in every larva. Supernumerary ddNs and MGIN2s were generated in synchronized embryos and isolated by fluorescence-activated cell sorting for transcriptome profiling. Differential gene expression analysis revealed ddN- and MGIN2-specific enrichment of a wide range of genes, including many encoding potential “effectors” of subtype-specific morphological and functional traits. More specifically, we identified the upregulation of centrosome-associated, microtubule-stabilizing/bundling proteins and extracellular matrix proteins and axon guidance cues as part of a single intrinsic regulatory program that might underlie the unique polarization of the ddNs, the only descending MG neurons that cross the midline.
Composition of estuarine sediment microbiome from a chronosequence of restored urban salt marshes
Authors: Morris Nathan , Alldred Mary , Zarnoch Chester , Alter Elizabeth 
Published: May 2019

ABSTRACTSalt marshes play an important role in the global nutrient cycle. The sediments in these systems harbor diverse and complex bacterial communities possessing metabolic capacities that provide ecosystem services such as nutrient cycling and removal. On the East Coast of the United States, salt marshes have been experiencing degradation due to anthropogenic stressors. Salt marsh islands within Jamaica Bay, New York City (USA), are surrounded by a large highly urbanized watershed and have declined in area. Restoration efforts have been enacted to reduce further loss, but little is known about how microbial communities develop following restoration activities, or how processes such as nitrogen cycling are impacted. Sediment samples were collected at two sampling depths from five salt marsh islands to characterize the bacterial communities found in marsh sediment including a post-restoration chronosequence of 3-12 years. We used 16s rRNA amplicon sequencing to define alpha and beta diversity, taxonomic composition, and predicted metabolic profile of each sediment sample. We found significant differences in alpha diversity between sampling depths, and significant differences in beta diversity, taxonomic composition, and predicted metabolic capacity among the five sampling locations. The youngest restored site and the degraded natural sampling site exhibited the most distinct communities among the five sites. Our findings suggest that while the salt marsh islands are located in close proximity to each other, they harbor distinct bacterial communities that can be correlated with the post-restoration age, marsh health, and other environmental factors such as availability of organic carbon.IMPORTANCESalt marshes play a critical role in the global nutrient cycle due to sediment bacteria and their metabolic capacities. Many East Coast salt marshes have experienced significant degradation over recent decades, thought largely to be due to anthropogenic stressors such as nitrogen loading, urban development, and sea-level rise. Salt marsh islands in Jamaica Bay (Queens/Brooklyn NY) are exposed to high water column nitrogen due to wastewater effluent. Several receding marsh islands have been subjected to restoration efforts to mitigate this loss. Little is known about the effect marsh restoration has on bacterial communities, their metabolic capacity, or how they develop post-restoration. Here we describe the bacterial communities found in marsh islands including a post-restoration chronosequence of 3-12 years and one degraded marsh island that remains unrestored.