bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing high resolution ribosome profiling for the global investigation of gene expression inChlamydomonas
Authors: Gotsmann Vincent Leon , Ting Michael Kien Yin , Haase Nadin , Rudorf Sophia , Zoschke Reimo , Willmund Felix 
Published: February 2023

AbstractRibosome profiling (Ribo-seq) is a powerful method for the deep analysis of translation mechanisms and regulatory circuits during gene expression. Here, we established an optimized and high resolution Ribo-seq protocol for the unicellular model algaChlamydomonas reinhardtii(Chlamydomonas). Comparing different nuclease treatments for the extraction and sequencing of ribosome-protected fragments (RPFs) and parallel RNA-seq, provided deep insight into translational dynamics and post-transcriptional control of gene expression, thoroughly covering more than 10,000 different transcripts. Our high quality Ribo-seq protocol captures the 3-nucleotide movement of elongating ribosomes along nuclear and chloroplast transcripts. Detailed analysis of the ribosomal offsets on transcripts uncovers presumable transition states during translocation of elongating ribosomes within the 5’- and 3’-sections of transcripts and features of eukaryotic translation termination. These offsets reveal drastic differences between the nature of cytosolic and chloroplast translation mechanisms. Chloroplast translation is further characterized by heterogenous RPF size distribution. We found that local accumulation of small RPFs correlates with local slowdown ofpsbAtranslation, possibly revealing an uncharacterized regulator step during PsbA/D1 synthesis. Further analyses of RPF distribution along specific cytosolic transcripts revealed characteristic patterns of translation elongation exemplified for the major light harvesting complex proteins, LHCs. Moreover, our Ribo-seq data can be utilized to survey coding sequence annotations and the expression preference of alternatively spliced transcripts in Chlamydomonas. We made these features easily accessible for the research community by attaching our Ribo-seq data to the most recent Chlamydomonas reference genome.
Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA)
Authors: Schiebout Courtney , Lust Hannah E. , Huang Yina H. , Frost H. Robert 
Published: February 2023

AbstractMotivationDoublets are usually considered an unwanted artifact of single-cell RNA-sequencing (scRNA-seq) and are only identified in datasets for the sake of removal. However, if cells have a juxtacrine attachment to one another in situ and maintain this association through an scRNA-seq processing pipeline that only partially dissociates the tissue, these doublets can provide meaningful biological information regarding the interactions and cell processes occurring in the analyzed tissue. This is especially true for cases such as the immune compartment of the tumor microenvironment, where the frequency and type of immune cell juxtacrine interactions can be a prognostic indicator.ResultsWe developed Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA) as a pipeline for identifying and analyzing biological doublets in scRNA-seq data. CIcADA identifies putative doublets using multi-label cell type scores and characterizes interaction dynamics through a comparison against synthetic doublets of the same cell type composition. In performing CIcADA on several scRNA-seq tumor datasets, we found that the identified doublets were consistently upregulating expression of immune response genes.ContactCourtney.T.Schiebout.GR@Dartmouth.edu,Hildreth.R.Frost@Dartmouth.edu
Explainable Fuzzy Clustering Framework Reveals Divergent Default Mode Network Connectivity Dynamics in Schizophrenia
Authors: Ellis Charles A. , Miller Robyn L. , Calhoun Vince D. 
Published: February 2023

AbstractDynamic functional network connectivity (dFNC) analysis of resting state functional magnetic resonance imaging data has yielded insights into many neurological and neuropsychiatric disorders. A common dFNC analysis approach uses hard clustering methods like k-means clustering to assign samples to states that summarize network dynamics. However, hard clustering methods obscure network dynamics by assuming (1) that all samples within a cluster are equally like their assigned centroids and (2) that samples closer to one another in the data space than to their centroids are well-represented by their centroids. In addition, it can be hard to compare subjects, as in some cases an individual may not manifest a state strongly enough to enter a hard cluster. Approaches that allow a dimensional approach to connectivity patterns (e.g., fuzzy clustering) can mitigate these issues. In this study, we present an explainable fuzzy clustering framework by combining fuzzy c-means clustering with several explainability metrics. We apply our framework for schizophrenia (SZ) default mode network analysis, identifying 5 states and characterizing those states with a new explainability approach. While also showing that features typically used in hard clustering can be extracted in our framework, we present a variety of unique features to quantify state dynamics and identify effects of SZ upon network dynamics. We further uncover relationships between symptom severity and interactions of the precuneus with the anterior and posterior cingulate cortex. Given the ease of implementing our framework and its enhanced insight into network dynamics, it has great potential for use in future dFNC studies.
Quantification and modeling of turnover dynamics ofde novotranscripts inDrosophila melanogaster
Authors: Grandchamp Anna , Czuppon Peter , Bornberg-Bauer Erich 
Published: February 2023

AbstractMost of the transcribed eukaryotic genomes are composed of non-coding transcripts. Among these transcripts, some are newly transcribed when compared to outgroups and are referred to asde novotranscripts.De novotranscripts have been shown to play a major role inde novogene emergence. However, little is known about the rates at whichde novotranscripts are gained and lost in individuals of the same species. Here, we address this gap and estimate for the first time thede novotranscript turnover rate. We use DNA long reads and RNA short reads from seven samples of inbred individuals ofDrosophila melanogasterto detectde novotranscripts that are (transiently) gained on a short evolutionary time scale. Overall, each sampled individual contains between 2,320 and 2,809 unsplicedde novotranscripts with most of them being sample specific. We estimate that around 0.15 transcripts are gained per year, and that each gained transcript is lost at a rate around 5×10−5per year. This high turnover of transcripts suggests frequent exploration of new genomic sequences within species. These rates provide first empirical estimates to better predict and comprehend the process ofde novogene birth.
Unraveling Spatial Gene Associations with SEAGAL: a Python Package for Spatial Transcriptomics Data Analysis and Visualization
Authors: Wang Linhua , Liu Chaozhong , Liu Zhandong 
Published: February 2023

AbstractSummaryIn the era where transcriptome profiling moves towards single-cell and spatial resolutions, the traditional co-expression analysis lacks the power to fully utilize such rich information to unravel spatial gene associations. Here we present a Python package called Spatial Enrichment Analysis of Gene Associations using L-index (SEAGAL) to detect and visualize spatial gene correlations at both single-gene and gene-set levels. Our package takes spatial transcriptomics data sets with gene expression and the aligned spatial coordinates as input. It allows for analyzing and visualizing spatial correlations at both single-gene and gene-set levels. The output could be visualized as volcano plots and heatmaps with a few lines of code, thus providing an easy-yet-comprehensive tool for mining spatial gene associations.Availability and ImplementationThe Python package SEAGAL can be installed using pip:https://pypi.org/project/seagal/. The source code and step-by-step tutorials are available at:https://github.com/linhuawang/SEAGAL.Contactlinhuaw@bcm.edu
Quantification of ligand and mutation-induced bias in EGFR phosphorylation in direct response to ligand binding
Authors: Wirth Daniel , Özdemir Ece , Hristova Kalina 
Published: February 2023

ABSTRACTThe 58 receptor tyrosine kinases (RTKs) are critically important for human development, and are implicated in many growth disorders and cancers. Here we introduce a methodology to identify and quantify bias in RTK signal transduction across the plasma membrane, and to quantify phosphorylation efficiencies, without contributions from feedback loops and system bias. We show that RTK biased signaling can occur in the first step of signal transduction not only in response to different ligands, but as a consequence of RTK pathogenic mutations as well. Ligand bias and mutation-induced bias are uncoupled here based on a comprehensive data set of dose response curves acquired for three ligands, EGF, TGFα and epiregulin, for wild-type EGFR and for the oncogenic L834R EGFR mutant found in patients with non-small-cell lung cancer (NSCLC). Ligand bias has been extensively studied for GPCRs, and has revolutionized the GPCR field. The demonstration of pathogenic mutation-induced bias in RTK signal transduction across the plasma membrane will open new avenues for the exploration of RTK biased inhibitors as highly specific anti-cancer therapies.
SARS-CoV-2 Neutralizing Antibodies After Bivalent vs. Monovalent Booster
Authors: Wang Qian , Bowen Anthony , Tam Anthony R. , Valdez Riccardo , Stoneman Emily , Mellis Ian A. , Gordon Aubree , Liu Lihong , Ho David D. 
Published: February 2023

AbstractBivalent mRNA vaccine boosters expressing Omicron BA.5 spike and ancestral D614G spike were introduced to attempt to boost waning antibody titers and broaden coverage against emerging SARS-CoV-2 lineages. Previous reports showed that peak serum neutralizing antibody (NAb) titers against SARS-CoV-2 variants following bivalent booster were similar to peak titers following monovalent booster. It remains unknown whether these antibody responses would diverge over time. We assessed serum virus-neutralizing titers in 41 participants who received three monovalent mRNA vaccine doses followed by bivalent booster, monovalent booster, or BA.5 breakthrough infection at one month and three months after the last vaccine dose or breakthrough infection using pseudovirus neutralization assays against D614G and Omicron subvariants (BA.2, BA.5, BQ.1.1, and XBB.1.5). There was no significant difference at one month and three months post-booster for the two booster cohorts. BA.5 breakthrough patients exhibited significantly higher NAb titers at three months against all Omicron subvariants tested compared against monovalent and bivalent booster cohorts. There was a 2-fold drop in mean NAb titers in the booster cohorts between one and three month time points, but no discernible waning of titers in the BA.5 breakthrough cohort over the same period. Our results suggest that NAb titers after boosting with one dose of bivalent mRNA vaccine are not higher than boosting with monovalent vaccine. Perhaps inclusion of D614G spike in the bivalent booster exacerbates the challenge posed by immunological imprinting. Hope remains that a second bivalent booster could induce superior NAb responses against emerging variants.
Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast
Authors: Chen Jingxuan , Basting Preston J. , Han Shunhua , Garfinkel David J. , Bergman Casey M. 
Published: February 2023

AbstractBackgroundMany computational methods have been developed to detect non-reference transposable element (TE) insertions using short-read whole genome sequencing data. The diversity and complexity of such methods often present challenges to new users seeking to reproducibly install, execute or evaluate multiple TE insertion detectors.ResultsWe previously developed the McClintock meta-pipeline to facilitate the installation, execution, and evaluation of six first-generation short-read TE detectors. Here, we report a completely re-implemented version of McClintock written in Python using Snakemake and Conda that improves its installation, error handling, speed, stability, and extensibility. McClintock 2 now includes 12 short-read TE detectors, auxiliary pre-processing and analysis modules, interactive HTML reports, and a simulation framework to reproducibly evaluate the accuracy of component TE detectors. When applied to the model microbial eukaryoteSaccharomyces cerevisiae, we find substantial variation in the ability of McClintock 2 components to identify the precise locations of non-reference TE insertions, with RelocaTE2 showing the highest recall and precision in simulated data. We find that RelocaTE2, TEMP, TEMP2 and TEBreak provide a consistent and biologically meaningful view of non-reference TE insertions in a species-wide panel of ~1000 yeast genomes, as evaluated by coverage-based abundance estimates and expected patterns of tRNA promoter targeting. Finally, we show that best-in-class predictors for yeast have sufficient resolution to reveal a dyad pattern of integration in nucleosome-bound regions upstream of yeast tRNA genes for Ty1, Ty2, and Ty4, allowing us to extend knowledge about fine-scale target preferences first revealed experimentally for Ty1 to natural insertions and related copia-superfamily retrotransposons in yeast.ConclusionMcClintock (https://github.com/bergmanlab/mcclintock/) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors for other species.
Polyether ionophore antibiotics target drug-resistant clinical isolates, persister cells, and biofilms
Authors: Wollesen Malene , Mikkelsen Kasper , Tvilum Marie Selch , Vestergaard Martin , Wang Mikala , Meyer Rikke L. , Ingmer Hanne , Poulsen Thomas B. , Tørring Thomas 
Published: February 2023

ABSTRACTPolyether ionophores are complex natural products known to transport various cations across biological membranes. While several members of this family are used in agriculture, e.g. as anti-coccidiostats, and have potent antibacterial activity, they are not currently pursued as antibiotics for human use. Polyether ionophores are typically grouped as having similar functions, despite the fact that they differ significantly in structure, and for this reason, it remains unclear how structure and activity are related. To triage whether certain members of the family constitute particularly interesting springboards for in-depth investigations, and future synthetic optimization, we here conduct a systematic comparative study of nine different polyether ionophores for their potential as antibiotics. This includes clinical isolates from bloodstream infections and studies of the compounds’ effects on bacterial biofilms and persister cells. We uncover distinct differences within the compound class and identify the compounds lasalocid, calcimycin, and nanchangmycin as having particularly interesting activity profiles for further development.
Propylene glycol inactivates respiratory viruses and prevents airborne transmission
Authors: Styles Christine T. , Zhou Jie , Flight Katie E. , Brown Jonathan C. , Vanden Oever Michael , Peacock Thomas P. , Wang Ziyin , Millns Rosie , O’Neill John S. , Barclay Wendy S. , Tregoning John S. , Edgar Rachel S. 
Published: February 2023

AbstractViruses are vulnerable as they transmit between hosts and we aimed to exploit this critical window. We found that the ubiquitous, safe, inexpensive and biodegradable small molecule propylene glycol (PG) has robust virucidal activity. Propylene glycol rapidly inactivates influenza, SARS-CoV-2 and a broad range of other enveloped viruses, and reduces disease burden in mice when administered intranasally at concentrations commonly found in nasal sprays. Most critically, aerosolized PG efficiently abolishes influenza and SARS-CoV-2 infectivity within airborne droplets, potently preventing infection at levels significantly below those well-tolerated by mammals. We present PG vapor as a first-in-class non-toxic airborne virucide, to prevent transmission of existing and emergent viral pathogens, with clear and immediate implications for public health.One-sentence summaryPropylene glycol is a potent and safe virucidal compound that could be used to limit and control infections.
HIV Pharmacology Data Repository (PDR): Setting the New Information Sharing Standard for Pharmacokinetic Studies
Authors: Tompkins Lauren A.R. , Kapeljushnik Oleg , Hubal Robert , Khoei Adrian , Dumond Julie , Kashuba Angela D.M. , Tropsha Alexander , Cottrell Mackenzie L. 
Published: February 2023

AbstractClinical therapeutics are becoming increasingly reliant on data science and computational data analytical tools to predict drug behavior in unobserved conditions or populations. Thesein silicoapproaches, collectively termed “pharmacometrics”, derive biological meaning from the analysis of pooled drug concentration vs. time (CvT) datasets. However, the field lacks standardization for pharmacokinetic (PK) data description and sharing, instead requiring deep dives into the literature and expert data annotation for aggregate data mining. Here we introduce a minimum information sharing standard for PK studies composed of three categories (Intervention, System, and Effects) and implement this standard in the development of a web-based PK database: the HIV Pharmacology Data Repository (PDR). We demonstrate the utility of the HIV PDR by computational modeling of aggregated and curated CvT data extracted from the HIV PDR.
Hyperpolarization-activated cation channels shape the spiking frequency preference of human cortical layer 5 pyramidal neurons
Authors: Inibhunu Happy , Chameh Homeira Moradi , Skinner Frances K , Rich Scott , Valiante Taufik A 
Published: February 2023

AbstractDiscerning the contribution of specific ionic currents to complex neuronal dynamics is a difficult, but important, task. This challenge is exacerbated in the human setting, although the widely-characterized uniqueness of the human brain as compared to preclinical models necessitates the direct study of human neurons. Neuronal spiking frequency preference is of particular interest given its role in rhythm generation and signal transmission in cortical circuits. Here, we combine the frequency-dependent gain (FDG), a measure of spiking frequency preference, and novelin silicoanalyses to dissect the contributions of individual ionic currents to key FDG features of human L5 neurons. We confirm that a contemporary model of such a neuron, primarily constrained to capture subthreshold activity driven by the hyperpolarization-activated cyclic nucleotide gated (h-) current, replicates key features of thein vitroFDG both with and without h-current activity. With the model confirmed as a viable approximation of the biophysical features of interest, we applied new analysis techniques to quantify the activity of each modeled ionic current in the moments prior to spiking, revealing unique dynamics of the h-current. These findings motivated patch-clamp recordings in analogous rodent neurons to characterize their FDG, which confirmed that a biophysically-detailed model of these neurons captures key inter-species differences in the FDG. These differences are correlated with distinct contributions of the h-current to neuronal activity. Together, this interdisciplinary and multi-species study provides new insights directly relating the dynamics of the h-current to neuronal spiking frequency preference in human L5 neurons.Significance StatementUnderstanding the contributions of individual ionic currents to neuronal activity is vital, considering the established role of ion channel modifications in neuropsychiatric conditions. We combinein vitrocharacterization of the spiking frequency preference of human L5 cortical pyramidal neurons via the frequency-dependent gain (FDG) with new analyses of a biophysically-detailed computational model of such a neuron to delineate the connection between the dynamics of the hyperpolarization-activated cyclic nucleotide gated (h-) current prior to spiking and key properties of the FDG. By further determining that both these FDG properties and h-current dynamics are distinct in analogous rodent neurons, we provide convincing evidence for the key role of the h-current in the frequency preference of human L5 cortical neurons.
Unraveling Chamber-specific Differences in Intercalated Disc Ultrastructure and Molecular Organization and Their Impact on Cardiac Conduction
Authors: Struckman Heather L. , Moise Nicolae , King D. Ryan , Soltisz Andrew , Buxton Andrew , Dunlap Izabella , Chen Zhenhui , Radwański Przemysław B. , Weinberg Seth H. , Veeraraghavan Rengasayee 
Published: February 2023

ABSTRACTDuring each heartbeat, the propagation of action potentials through the heart coordinates the contraction of billions of individual cardiomyocytes and is thus, a critical life process. Unsurprisingly, intercalated discs, which are cell-cell contact sites specialized to provide electrical and mechanical coupling between adjacent cardiomyocytes, have been the focus of much investigation. Slowed or disrupted propagation leads to potentially life-threatening arrhythmias in a wide range of pathologies, where intercalated disc remodeling is a common finding. Hence, the importance and urgency of understanding intercalated disc structure and its influence on action potential propagation. Surprisingly, however, conventional modeling approaches cannot predict changes in propagation elicited by perturbations that alter intercalated disc ultrastructure or molecular organization, owing to lack of quantitative structural data at subcellular through nano scales. In order to address this critical gap in knowledge, we sought to quantify intercalated disc structure at these finer spatial scales in the healthy adult mouse heart and relate them to function in a chamber-specific manner as a precursor to understanding the impacts of pathological intercalated disc remodeling. Using super-resolution light microscopy, electron microscopy, and computational image analysis, we provide here the first ever systematic, multiscale quantification of intercalated disc ultrastructure and molecular organization. By incorporating these data into a rule-based model of cardiac tissue with realistic intercalated disc structure, and comparing model predictions of electrical propagation with experimental measures of conduction velocity, we reveal that atrial intercalated discs can support faster conduction than their ventricular counterparts, which is normally masked by inter-chamber differences in myocyte geometry. Further, we identify key ultrastructural and molecular organization features underpinning the ability of atrial intercalated discs to support faster conduction. These data provide the first stepping stone to elucidating chamber-specific impacts of pathological intercalated disc remodeling, as occurs in many arrhythmic diseases.