bluuebunny/crossref_metadata_2025_split huggingface dataset:
Attention please: modeling global and local context in glycan structure-function relationships
Authors: Dai Bowen , Mattox Daniel E , Bailey-Kellogg Chris 
Published: October 2021

ABSTRACTGlycans are found across the tree of life with remarkable structural diversity enabling critical contributions to diverse biological processes, ranging from facilitating host-pathogen interactions to regulating mitosis & DNA damage repair. While functional motifs within glycan structures are largely responsible for mediating interactions, thecontextsin which the motifs are presented can drastically impact these interactions and their downstream effects. Here, we demonstrate the first deep learning method to represent both local and global context in the study of glycan structure-function relationships. Our method, glyBERT, encodes glycans with a branched biochemical language and employs an attention-based deep language model to learn biologically relevant glycan representations focused on the most important components within their global structures. Applying glyBERT to a variety of prediction tasks confirms the value of capturing rich context-dependent patterns in this attention-based model: the same monosaccharides and glycan motifs are represented differently in different contexts and thereby enable improved predictive performance relative to the previous state-of-the-art approaches. Furthermore, glyBERT supports generative exploration of context-dependent glycan structure-function space, moving from one glycan to “nearby” glycans so as to maintain or alter predicted functional properties. In a case study application to altering glycan immunogenicity, this generative process reveals the learned contextual determinants of immunogenicity while yielding both known and novel, realistic glycan structures with altered predicted immunogenicity. In summary, modeling the context dependence of glycan motifs is critical for investigating overall glycan functionality and can enable further exploration of glycan structure-function space to inform new hypotheses and synthetic efforts.
A Golden Gate-based Plasmid Library for the Rapid Assembly of Biotin Ligase Constructs for Proximity Labelling
Authors: Goslin Kevin , Finocchio Andrea , Wellmer Frank 
Published: October 2021

ABSTRACTProximity-labelling has emerged as a powerful tool for the detection of weak and transient interactions between proteins as well as the characterization of subcellular proteomes. One proximity labelling approach makes use of a promiscuous bacterial biotin ligase, termed BioID. Expression of BioID (or of its derivates TurboID and MiniTurbo) fused to a bait protein results in the biotinylation of proximal proteins. These biotinylated proteins can then be isolated by affinity purification using streptavidin-coated beads and identified by mass spectrometry. To facilitate the use of proximity-labelling in plants, we have generated a collection of constructs that can be used for the rapid cloning of TurboID and MiniTurbo fusion proteins using the Golden Gate cloning method. To allow for the use of the constructs in a range of experiments we have designed assembly modules that encode the biotin ligases fused to different linkers as well as different commonly used subcellular localization sequences. We demonstrate the functionality of these vectors through biotinylation assays in tobacco (Nicotiana benthamiana) plants.
Open-source low-cost cardiac optical mapping system
Authors: Rybashlykov D. , Brennan J. , Lin Z. , Efimov I.R. , Syunyaev R. 
Published: October 2021

AbstractFluorescent imaging with voltage- or calcium-sensitive dyes, i.e. optical mapping, is one of the indispensable modern techniques to study cardiac electrophysiology, unsurpassed by temporal and spatial resolution. High-speed CMOS cameras capable of optical registration of action potential propagation are in general very costly. We present a complete solution priced below US$ 1,000 (including camera and lens) at the moment of publication with an open-source image acquisition and processing software. We demonstrate that the iDS UI-3130CP rev.2 camera we used in this study is capable of 200×200 977 frames per second (FPS) action potential recordings from rodent hearts. The signal-to-noise-ratio of a conditioned signal was 16 ± 10 for rodent hearts. A comparison with a specialized MiCAM Ultimate-L camera has shown that signal-to-noise ratio (SNR) is sufficient for accurate measurements of AP waveform, conduction velocity (± 0.04 m/s) and action potential duration (± 7ms) in mouse and rat hearts. We measured the action potential prolongation during 4-aminopyridine administration in mouse heart, showing that proposed system signal quality is adequate for drug studies.
PDXNet Portal: Patient-Derived Xenograft model, data, workflow, and tool discovery
Authors: Koc Soner , Lloyd Michael W. , Grover Jeffrey , Seepo Sara , Subramanian Sai Lakshmi , Ray Manisha , Frech Christian , DiGiovanna John , Webster Phillip , Neuhauser Steven , Srivastava Anuj , Woo Xing Yi , Sanderson Brian J. , White Brian , Lott Paul ,   PDXNet Consortium, Evrard Yvonne A. , Wallace Tiffany A. , Moscow Jeffrey A. , Doroshow James H. , Mitsiades Nicholas , Kaochar Salma , Pan Chong-xian , Chen Moon S. , Carvajal-Carmona Luis , Welm Alana L. , Welm Bryan E. , Lewis Michael T. , Govindan Ramaswamy , Ding Li , Li Shunquang , Herlyn Meenherd , Davies Mike , Roth Jack , Meric-Bernstam Funda , Robinson Peter N. , Bult Carol J. , Davis-Dusenbery Brandi , Dean Dennis A. , Chuang Jeffrey H. ,   for the PDXNet Consortium Members
Published: October 2021

AbstractWe created the PDX Network (PDXNet) Portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources (i.e., PDX models, sequencing data, treatment response data, and bioinformatics workflows), to facilitate collaboration among researchers, and to make resources easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols, and training materials for processing PDX data.The initial portal release highlights PDXNet model and data resources, including 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI’s Patient-Derived Model Repository (PDMR) for public access. These models have 2,822 associated sequencing files from 873 samples across 307 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal also includes results from standardized analysis workflows on PDXNet sequencing files and PDMR data (2,594 samples from 463 patients across 78 disease types). These 15 analysis workflows for whole-exome and RNA-Seq data are freely available, robust, validated, and standardized.The model and data lists will grow substantially over the next two years and will be continuously updated as new data are available. PDXNet models support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials. The PDXNet portal is a centralized location for these data and resources, which we expect to be of significant utility for the cancer research community.
Alpha cell dysfunction in early type 1 diabetes
Authors: Doliba Nicolai M , Rozo Andrea V , Roman Jeffrey , Qin Wei , Traum Daniel , Gao Long , Liu Jinping , Manduchi Elisabetta , Liu Chengyang , Golson Maria L , Vahedi Golnaz , Naji Ali , Matschinsky Franz M , Atkinson Mark A. , Powers Alvin C , Brissova Marcela , Kaestner Klaus H , Stoffers Doris A ,   for the HPAP Consortium
Published: October 2021

SummaryMultiple islet autoantibodies (AAb) predict type 1 diabetes (T1D) and hyperglycemia within 10 years. By contrast, T1D develops in just ∼15% of single AAb+ (generally against glutamic acid decarboxylase, GADA+) individuals; hence the single GADA+ state may represent an early stage of T1D amenable to interventions. Here, we functionally, histologically, and molecularly phenotype human islets from non-diabetic, GADA+ and T1D donors. Similar to the few remaining beta cells in T1D islets, GADA+ donor islets demonstrated a preserved insulin secretory response. By contrast, alpha cell glucagon secretion was dysregulated in both T1D and GADA+ islets with impaired glucose suppression of glucagon secretion. Single cell RNA sequencing (scRNASeq) of GADA+ alpha cells revealed distinct abnormalities in glycolysis and oxidative phosphorylation pathways and a marked downregulation of PKIB, providing a molecular basis for the loss of glucose suppression and the increased effect of IBMX observed in GADA+ donor islets. The striking observation of a distinct early defect in alpha cell function that precedes beta cell loss in T1D suggests that not only overt disease, but also the progression to T1D itself, is bihormonal in nature.
CellTools algorithm for mapping scRNA-seq query cells to the reference dataset improves the classification of resilient and susceptible retinal ganglion cell types
Authors: Rheaume Bruce A. , Xing Jian , Theune William C. , DeRosa Samantha G. , Trakhtenberg Ephraim F. 
Published: October 2021

ABSTRACTThe clustering of single cell RNA-sequencing (scRNA-seq) data enables the classification of cell types, and the development of integration mapping algorithms has enabled the tracing of altered-from-baseline transcriptomes to their respective cell type origins. Here, we developed an algorithm that removes sources of noise from scRNA-seq reference dataset, and in the next step optimizes weight-assignment to anchors, cumulatively improving the accuracy of query cells mapping to reference dataset. The denoising step of our algorithm also improved the performance of other mapping algorithms. To further demonstrate biological relevance, using our algorithm we determined the type-origin of the 17% of injured retinal ganglion cells (RGCs) that a prior algorithm did not identify. As we found that most of the originally unassigned cells belonged to only some RGC types, a consequent change in the proportions of the surviving types resulted in an amended ranking of resiliency to injury. We also identified new cluster-markers for RGC types, validated two novel markers by immunostaining in retinas, and developed a website for cluster-by-cluster comparison of gene expression between uninjured and injured RGC types. Additional bioinformatic analyses contributed new insights into the global characteristics of RGC types and how axonal injury affects them, showing how dissimilarity between transcriptomes of RGC types increases during maturation and after injury. We further characterized the correspondence between the neonatal and adult RGC types, and showed which cluster markers change expression developmentally or after injury. We also show, for the first time, that global properties of the transcriptome can predict the resilience to injury of at least some cell types. The R-package, CellTools, for the algorithms we developed, will assist scRNA-seq studies across biological fields.
How low can you go? Driving down the DNA input requirements for nanopore sequencing
Authors: Heavens Darren , Chooneea Darren , Giolai Michael , Cuber Piotr , Aanstad Pia , Martin Samuel , Alston Mark , Misra Raju , Clark Matthew D. , Leggett Richard M. 
Published: October 2021

AbstractThe requirement for large amounts of purified DNA limits many sequencing experiments, especially when seeking to avoid pre-amplification or when using third generation technology to sequence molecules directly. We wanted to test the limits of current nanopore sequencing input requirements and devised a set of experiments to evaluate extraction and library preparation approaches for low inputs.We found an optimised bead beating approach combined with a magnetic bead protocol, rather than traditional spin columns for DNA extraction, improved both molecule length, integrity score and DNA yield. Through reducing the DNA input to as little as 6.25 % of recommended (25 ng versus 400 ng) and reaction volumes in half, library construction can be completed, and sequencing begun within 20 minutes of sample collection.Applying these approaches, we demonstrated that our pipeline can be used as a cheap and effective method to de novo assemble a genome and identify genes from low quantities and quality of DNA. With our rapid extraction protocol using transportable equipment and low input library construction we were able to generate a de novo assembly from a single insect (Drosophila melanogaster) spanning 125 Mbp / 85 % of the reference genome, over 96.9% complete BUSCO genes, with a contig N50 over 1.2 Mbp, including chromosome arm sized contigs, for a modest consumable cost under £600.
Assessing species coverage and assembly quality of rapidly accumulating sequenced genomes
Authors: Feron Romain , Waterhouse Robert M. 
Published: October 2021

AbstractAmbitious initiatives to coordinate genome sequencing of Earth’s biodiversity mean that the accumulation of genomic data is growing rapidly. In addition to cataloguing biodiversity, these data provide the basis for understanding biological function and evolution. Accurate and complete genome assemblies offer a comprehensive and reliable foundation upon which to advance our understanding of organismal biology at genetic, species, and ecosystem levels. However, ever-changing sequencing technologies and analysis methods mean that available data are often heterogeneous in quality. In order to guide forthcoming genome generation efforts and promote efficient prioritisation of resources, it is thus essential to define and monitor taxonomic coverage and quality of the data. Here we present an automated analysis workflow that surveys genome assemblies from the United States National Center for Biotechnology Information (NCBI), assesses their completeness using the relevant Benchmarking Universal Single-Copy Orthologue (BUSCO) datasets, and collates the results into an interactively browsable resource. We apply our workflow to produce a community resource of available assemblies from the phylum Arthropoda, the Arthropoda Assembly Assessment Catalogue. Using this resource, we survey current taxonomic coverage and assembly quality at the NCBI, we examine how key assembly metrics relate to gene content completeness, and we compare results from using different BUSCO lineage datasets. These results demonstrate how the workflow can be used to build a community resource that enables large-scale assessments to survey species coverage and data quality of available genome assemblies, and to guide prioritisations for ongoing and future sampling, sequencing, and genome generation initiatives.
Reward timing matters in motor learning
Authors: Vassiliadis Pierre , Lete Aegryan , Duque Julie , Derosiere Gerard 
Published: October 2021

AbstractReward can improve motor learning and the consolidation of motor memories. Identifying the features of reward feedback that are critical for motor learning is a necessary step for successful integration into rehabilitation programs. One central feature of reward feedback that may affect motor learning is its timing – that is, the delay after which reward is delivered following movement execution. In fact, research on associative learning has shown that short and long reward delays (e.g., 1 and 6 s following action execution) activate preferentially the striatum and the hippocampus, respectively, which both contribute with varying degrees to motor learning. Given the distinct functional role of these two areas, we hypothesized that reward timing could modulate how people learn and consolidate a new motor skill. In sixty healthy participants, we found that delaying reward delivery by a few seconds influenced motor learning dynamics. Indeed, training with a short reward delay (i.e., 1 s) induced slow, yet continuous gains in performance, while a long reward delay (i.e., 6 s) led to initially high learning rates that were followed by an early plateau in the learning curve and a lower endpoint performance. Moreover, participants who successfully learned the skill with a short reward delay displayed overnight consolidation, while those who trained with a long reward delay exhibited an impairment in the consolidation of the motor memory. Overall, our data show that reward timing affects motor learning, potentially by modulating the engagement of different learning processes, a finding that could be exploited in future rehabilitation programs.
Generative modeling of histology tissue reduces human annotation effort for segmentation model development
Authors: Lutnick Brendon , Sarder Pinaki 
Published: October 2021

ABSTRACTSegmentation of histology tissue whole side images is an important step for tissue analysis. Given enough annotated training data modern neural networks are capable accurate reproducible segmentation, however, the annotation of training datasets is time consuming. Techniques such as human in the loop annotation attempt to reduce this annotation burden, but still require a large amount of initial annotation. Semi-supervised learning, a technique which leverages both labeled and unlabeled data to learn features has shown promise for easing the burden of annotation. Towards this goal, we employ a recently published semi-supervised method:datasetGANfor the segmentation of glomeruli from renal biopsy images. We compare the performance of models trained usingdatasetGANand traditional annotation and show thatdatasetGANsignificantly reduces the amount of annotation required to develop a highly performing segmentation model. We also explore the usefulness of usingdatasetGANfor transfer learning and find that this greatly enhances the performance when a limited number of whole slide images are used for training.
Stratification in Microbial Communities with Depth and Redox Status in a Eutrophic Lake Across Two Years
Authors: Marick Robert A. , Peterson Benjamin D. , McMahon Katherine D. 
Published: October 2021

AbstractBacteria have a profound impact on many key biogeochemical cycles in freshwater lake ecosystems; in turn, the composition of bacteria in the lake is contingent on the chemistry of the water. Many parameters that affect bacterial growth in freshwater ecosystems, such as water temperature, nutrient levels, and redox status, exhibit notable inter-annual differences in addition to seasonal changes. However, little is known about the impact of these inter- and intra-annual differences on the freshwater microbiome, especially in anoxic bottom waters. In this study, we paired biogeochemical field data with 16S rRNA gene amplicon sequencing of depth-discrete samples from a dimictic lake across two open-water seasons to observe variation in the microbiome relative to differences in water chemistry between two years. We found differences in the timing anoxia onset and the redox status in the water column across the two years. Changes in redox status led to major shifts in the microbial community composition. While there was little variation between years in the microbial taxonomic composition at the phyla level, there was substantial interannual variation at more resolved taxonomic levels. Some interannual differences can be explained by links between the predicted metabolic potential of those lineages and the different redox conditions between the two years. These results emphasize the need for repeated monitoring to deduce long-term trends in microbial communities in natural ecosystems and the importance of a comprehensive evaluation of environmental conditions contemporary with any microbiome analysis.ImportanceThe results of this study add to the growing body of evidence that microbial communities in natural systems are temporally dynamic on multiple scales, and even more so at highly resolved taxonomic levels. By correlating our analysis of the microbial community with the redox status of the water column we find that many community differences between the years can be in part explained by these parameters. As collecting 16S rRNA data over many years is critical to understanding long term trends in microbial ecology, our study suggests that corresponding water chemistry data could be a powerful tool to help explain microbiome trends.
MspA Porin as a Local Nanopore Probe for Membrane-bound Proteins
Authors: Hoogerheide David P. , Gurnev Philip A. , Gundlach Jens , Laszlo Andrew , Rostovtseva Tatiana K. , Bezrukov Sergey M. 
Published: October 2021

AbstractNanopore sensing is based on detection and analysis of nanopore transient conductance changes induced by analyte capture. We have recently shown that α-Synuclein (αSyn), an intrinsically disordered, membrane-active, neuronal protein implicated in Parkinson disease, can be reversibly captured by the VDAC nanopore. The capture process is a highly voltage dependent complexation of the two proteins where transmembrane potential drives the polyanionic C-terminal domain of αSyn into VDAC—exactly the mechanism by which generic nanopore-based interrogation of proteins and polynucleotides proceeds. The complex formation, and the motion of αSyn in the nanopore, thus may be expected to be only indirectly dependent on the pore identity. Here, we confirm this prediction by demonstrating that when VDAC is replaced with a different transmembrane pore, the engineered mycobacterial porin M2MspA, all the qualitative features of the αSyn/nanopore interaction are preserved. The rate of αSyn capture by M2MspA rises exponentially with the applied field, while the residence time displays a crossover behavior, indicating that at voltages >50 mV M2MspA-bound αSyn largely undergoes translocation to the other side of the membrane. The translocation is directly confirmed using the selectivity tag method, in which the polyanionic C-terminal and neutral N-terminal regions of αSyn alter the selectivity of the M2MspA channel differently, allowing direct discrimination of translocation vs retraction for single αSyn molecules. We thus prove that the physical model of the motion of disordered protein chains in the nanopore confinement and the selectivity tag technique are not limited to VDAC but are broadly applicable to nanopore-based protein detection, analysis, and separation technologies.