bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic evolution reshapes cell type diversification in the amniote brain
Authors: Chen Duoyuan , Zhuang Zhenkun , Huang Maolin , Huang Yunqi , Yan Yuting , Zhang Yanru , Lin Youning , Jin Xiaoying , Wang Yuanmei , Huang Jinfeng , Xu Wenbo , Pan Jingfang , Wang Hong , Huang Fubaoqian , Liao Kuo , Cheng Mengnan , Zhu Zhiyong , Bai Yinqi , Niu Zhiwei , Zhang Ze , Xiang Ya , Wei Xiaofeng , Yang Tao , Zeng Tao , Dong Yuliang , Lei Ying , Sun Yangang , Wang Jian , Yang Huanming , Sun Yidi , Cao Gang , Poo Muming , Liu Longqi , Naumann Robert K. , Xu Chun , Wang Zhenlong , Xu Xun , Liu Shiping 
Published: June 2024

SummaryOver 320 million years of evolution, amniotes have developed complex brains and cognition through largely unexplored genetic and gene expression mechanisms. We created a comprehensive single-cell atlas of over 1.3 million cells from the telencephalon and cerebellum of turtles, zebra finches, pigeons, mice, and macaques, employing single-cell resolution spatial transcriptomics to validate gene expression patterns across species. Our study revealed significant species-specific variations in cell types, highlighting their conservation and diversification in evolution. We found pronounced differences in telencephalon excitatory neurons (EX) and cerebellar cell types between birds and mammals. Birds predominantly expressSLC17A6in EX, whereas mammals expressedSLC17A7in neocortex andSLC17A6elsewhere, possibly due to loss ofSLC17A7function loss in birds. Additionally, we identified a novel bird-specific Purkinje cell subtype (SVIL+), implicating the LSD11/KDM1A pathway in learning and circadian rhythms, and related numerous positively selected genes in birds, suggesting an evolutionary optimization of cerebellar functions for ecological and behavioral adaptation. Our findings elucidate the complex interplay between genetic evolution and environmental adaptation, underscoring the role of genetic diversification in the development of specialized cell types across amniotes.
GelMA as scaffold material for epithelial cells to emulate the small intestinal microenvironment
Authors: Roegiers Inez , Gheysens Tom , Vanbeversluys Kim , Rać Nikoletta , Stroka Grzegorz , de Croock Jana , Van de Wiele Tom , Dubruel Peter , Arroyo Marta Calatayud 
Published: June 2024

AbstractHost-microbe interactions in the intestine play a significant role in health and disease. Novel scaffolds for host cells, capable of potentially supporting ese intricate interactions, are necessary to improve our current systems for mimicking host-microbiota interplayin vitro/ex vivo. In this research paper, we study the application of gelatin methacrylamide (GelMA) as scaffold material for intestinal epithelial cells in terms of permeability, mechanical strength, and biocompatibility. We investigated whether the degree of substitution (DS) of GelMA influences the permeability and found that both high and low DS GelMA show sufficient permeability of biorelevant transport markers. Additionally, we researched epithelial cell adherence and viability, as well as mechanical characteristics of different concentrations of GelMA. All concentrations of hydrogel show long-term biocompatibility for the mono- and co-cultures, despite the goblet-like cells (LS174T) showing lower performance than enterocyte-like cells (Caco-2). The mechanical strength of all hydrogel concentrations was in a physiologically relevant range to be used as scaffold material for intestinal cells. Based on these results, we conclude that GelMA is a suitable material as a scaffold for intestinal cell types in terms of permeability, mechanical strength and biocompatibility. These findings contribute to the growing field ofin vitromodeling of the gut and moves the field further to ensuring more translatable research on host-microbe interactions.
Distinct pathway for evolution of enhanced receptor binding and cell entry in SARS-like bat coronaviruses
Authors: Tse Alexandra L. , Acreman Cory M. , Ricardo-Lax Inna , Berrigan Jacob , Lasso Gorka , Balogun Toheeb , Kearns Fiona L. , Casalino Lorenzo , McClain Georgia L. , Chandran Amartya Mudry , Lemeunier Charlotte , Amaro Rommie E. , Rice Charles M. , Jangra Rohit K. , McLellan Jason S. , Chandran Kartik , Miller Emily Happy 
Published: June 2024

ABSTRACTUnderstanding the zoonotic risks posed by bat coronaviruses (CoVs) is critical for pandemic preparedness. Herein, we generated recombinant vesicular stomatitis viruses (rVSVs) bearing spikes from divergent bat CoVs to investigate their cell entry mechanisms. Unexpectedly, the successful recovery of rVSVs bearing the spike from SHC014, a SARS-like bat CoV, was associated with the acquisition of a novel substitution in the S2 fusion peptide-proximal region (FPPR). This substitution enhanced viral entry in both VSV and coronavirus contexts by increasing the availability of the spike receptor-binding domain to recognize its cellular receptor, ACE2. A second substitution in the spike N–terminal domain, uncovered through forward-genetic selection, interacted epistatically with the FPPR substitution to synergistically enhance spike:ACE2 interaction and viral entry. Our findings identify genetic pathways for adaptation by bat CoVs during spillover and host-to-host transmission, fitness trade-offs inherent to these pathways, and potential Achilles’ heels that could be targeted with countermeasures.
A Zero-Inflated Hierarchical Generalized Transformation Model to Address Non-Normality in Spatially-Informed Cell-Type Deconvolution
Authors: Melton Hunter J. , Bradley Jonathan R. , Wu Chong 
Published: June 2024

AbstractOral squamous cell carcinomas (OSCC), the predominant head and neck cancer, pose significant challenges due to late-stage diagnoses and low five-year survival rates. Spatial transcriptomics offers a promising avenue to decipher the genetic intricacies of OSCC tumor microenvironments. In spatial transcriptomics, Cell-type deconvolution is a crucial inferential goal; however, current methods fail to consider the high zero-inflation present in OSCC data. To address this, we develop a novel zero-inflated version of the hierarchical generalized transformation model (ZI-HGT) and apply it to the Conditional AutoRegressive Deconvolution (CARD) for cell-type deconvolution. The ZI-HGT serves as an auxiliary Bayesian technique for CARD, reconciling the highly zero-inflated OSCC spatial transcriptomics data with CARD’s normality assumption. The combined ZI-HGT + CARD framework achieves enhanced cell-type deconvolution accuracy and quantifies uncertainty in the estimated cell-type proportions. We demonstrate the superior performance through simulations and analysis of the OSCC data. Furthermore, our approach enables the determination of the locations of the diverse fibroblast population in the tumor microenvironment, critical for understanding tumor growth and immunosuppression in OSCC.
Semi-Automatic Detection of Errors in Genome-Scale Metabolic Models
Authors: Moyer Devlin C. , Reimertz Justin , Segrè Daniel , Fuxman Bass Juan I. 
Published: June 2024

AbstractBackgroundGenome-Scale Metabolic Models (GSMMs) are used for numerous tasks requiring computational estimates of metabolic fluxes, from predicting novel drug targets to engineering microbes to produce valuable compounds. A key limiting step in most applications of GSMMs is ensuring their representation of the target organism’s metabolism is complete and accurate. Identifying and visualizing errors in GSMMs is complicated by the fact that they contain thousands of densely interconnected reactions. Furthermore, many errors in GSMMs only become apparent when considering pathways of connected reactions collectively, as opposed to examining reactions individually.ResultsWe present Metabolic Accuracy Check and Analysis Workflow (MACAW), a collection of algorithms for detecting errors in GSMMs. The relative frequencies of errors we detect in manually curated GSMMs appear to reflect the different approaches used to curate them. Changing the method used to automatically create a GSMM from a particular organism’s genome can have a larger impact on the kinds of errors in the resulting GSMM than using the same method with a different organism’s genome. Our algorithms are particularly capable of identifying errors that are only apparent at the pathway level, including loops, and nontrivial cases of dead ends.ConclusionsMACAW is capable of identifying inaccuracies of varying severity in a wide range of GSMMs. Correcting these errors can measurably improve the predictive capacity of a GSMM. The relative prevalence of each type of error we identify in a large collection of GSMMs could help shape future efforts for further automation of error correction and GSMM creation.
HyDRA: a pipeline for integrating long- and short-read RNAseq data for custom transcriptome assembly
Authors: Almeida Isabela , Lu Xue , Edwards Stacey L. , French Juliet D. , Bitar Mainá 
Published: June 2024

ABSTRACTBackgroundShort-read RNA sequencing (RNAseq) has widely been used to sequence RNA from a wide range of different tissues, developmental stages and species. However, the technology is limited by inherent biases and its inability to capture full-length transcripts. Long-read RNAseq overcomes these issues by providing reads that can span multiple exons, resolve complex repetitive regions and the capability to cover entire transcripts. Unfortunately, this technology is still prone to higher error rates. Noncoding RNA transcripts are highly specific to different cell types and tissues and remain underrepresented in current reference annotations. This problem is exacerbated by the dismissal of sequenced reads that align to genomic regions that do not contain annotated transcripts, resulting in approximately half of the expressed transcripts being overlooked in transcriptional studies.ResultsWe have developed a pipeline, named HyDRA (Hybridde novoRNAassembly), which combines the precision of short reads with the structural resolution of long reads, enhancing the accuracy and reliability of custom transcriptome assemblies. Deep, short- and long-read RNAseq data derived from ovarian and fallopian tube samples were used to develop, validate and assess the efficacy of HyDRA. We identified more than 50,000 high-confidence long noncoding RNAs, most of which have not been previously detected using traditional methods.ConclusionsHyDRA’s assembly performed more than 40% better than a similar assembly obtained with the top-ranked stand-alonede novotranscriptome short-read-only assembly tool and over 30% better than one obtained with the best-in-class multistep short-read-only approach. Although long-read sequencing is rapidly advancing, the vast availability of short-read RNAseq data will ensure that hybrid approaches like the one implemented in HyDRA continue to be relevant, allowing the discovery of high-confidence transcripts within specific cell types and tissues. As the practice of performing hybridde novotranscriptome assemblies becomes commonplace, HyDRA will advance the annotation of coding and noncoding transcripts and expand our knowledge of the noncoding genome.
Detecting Data Embedding Spatial Patterns and Identifying Biomarkers with BioRSP
Authors: Yao Zeyu , Chen Jake Y. 
Published: June 2024

AbstractMotivationHigh-dimensional data embedding has become an essential tool in bioinformatics, particularly for single-cell data analysis, as it aids in characterizing cells with complex gene expression patterns based on projected low-dimensional data point spatial distributions. However, traditional methods often fall short in distinguishing subtle changes within cell populations. To address this, we developed BioRSP (BiologicalRadarScanningPlots), an innovative open-source software designed to enhance the characterization of single-cell gene expression patterns by simulating radar beam scanning across defined clusters from a fixed coordinate, referred to as the “vantage point.”ResultsBioRSP enables users to analyze the distribution of each gene within and across cell clusters using a quantitative measure known as the RSP plot. These plots categorize genes and spatial embedding patterns into four distinct groups based on combinations of gene coverage (high/low) and RSP values (high/low), reflecting spatial distribution regularities in the embedding space. This novel approach allows BioRSP to distinguish subtle differences between background cells and those expressing specific markers above a preset threshold, significantly improving upon traditional gene-to-gene correlation analyses. A case study utilizing a neonatal mouse heart tissue dataset from the Mouse Cell Atlas demonstrates BioRSP’s capability to identify spatially distinct and functionally significant gene expression patterns.AvailabilityThe Python package and its comprehensive documentation are publicly available athttps://github.com/cytronicoder/biorsp.Contactcytronicoder@gmail.com
Drivers of spatio-temporal variability in a marine foundation species
Authors: Giraldo-Ospina Anita , Bell Tom , Carr Mark H. , Caselle Jennifer E. 
Published: June 2024

AbstractMarine foundation species are critical for the structure and functioning of ecosystems and constitute the pillar of trophic chains while also providing a variety of ecosystem services. In recent decades many foundation species have declined in abundance, sometimes threatening their current geographical distribution. Kelps (Laminariales) are the primary foundation species in temperate coastal systems worldwide. Kelp ecosystems are notoriously variable and identifying the key factors that control the dynamics of kelp abundance is key to predicting the fate of kelp ecosystems under climatic change and informing management and conservation decisions such as forest restoration. Here, we usedin situdata from long-term monitoring programs across 1,350 km of coast spanning multiple biogeographic regions in the state of California (USA) to identify the major regional drivers of density of two dominant canopy-forming kelp species and to elucidate the spatial and temporal scales over which they operate. We used generalized additive models to identify the key drivers of density of two dominant kelp species (Nereocystis luetkeanaandMacrocystis pyrifera) across four ecological regions of the state of California (north, central, south-west and south-east) and for the past two decades (2004-2021). Our study identified that the dominant drivers of kelp density varied between regions and species but always included some combination of nitrate availability, wave energy and exposure, density of purple sea urchins, and temperature as the most important predictors explaining 63% of the variability of bull kelp in the north and central regions, and 45% and 51.4% of the variability in giant kelp for the central/south-west and south-east regions, respectively. These large-scale analyses infer that a combination of lower nutrient availability, changes in wave energy and exposure, and increases in temperature and purple sea urchin counts have contributed to the decline of kelp observed in the last decade. Understanding the drivers of kelp dynamics can be used to identify regions and periods of significant change and historical stability, ultimately informing resource management and conservation decisions such as site selection for kelp protection and restoration.Open research statementData (Giraldo-Ospina et al. 2023) are available in DataOne at doi:10.25494/P6/When_where_and_how_kelp_restoration_guidebook_2.
Guidelines for evaluating the success of large carnivore reintroductions
Authors: Briers-Louw Willem D. , Lindsey Peter , Gaylard Angela , Cristescu Bogdan , Verschueren Stijn , Plessis Cole du , Drouilly Marine , Bantlin Drew , Kendon Tamar A. , Evers Emma E.M. , Curry Caitlin J. , Almeida João , Gaynor David , Leslie Alison J. , Naude Vincent N. 
Published: June 2024

AbstractAnthropogenic impacts have led to widespread species decline and extirpation, thereby compelling a global movement to protect and regenerate biodiversity through holistic ecosystem restoration including reintroductions. Yet, despite the increasing practice of conservation-driven reintroduction efforts over the past century, peer-reviewed literature and policy providing criteria with which to evaluate reintroduction stages and efficacy remain limited. Without these comprehensive and quantifiable metrics of relative success, such drastic conservation intervention strategies cannot be objectively evaluated nor compared, hindering the advancement of restoration as a discipline. Herein, we systematically reviewed 227 large carnivore reintroductions of 14 terrestrial mammal species across 23 countries since 1930 to contextualize global efforts to date, and from these, have developed a standardized framework to evaluate reintroduction success. We further retrospectively determined the extent to which existing studies met these criteria towards identifying current knowledge gaps and guide future reintroduction efforts. Most large carnivore records were of Felidae (70%) reintroduced into ‘closed’ systems (69%) across southern Africa (70%). Our proposed framework provides a full suite of stages, indicators, and targets for reintroduction evaluation, which, when retrospectively applied to reviewed studies, indicated that at least one-third lacked sufficient information to effectively evaluate and compare reintroduction outcomes. This comprehensive and prioritized framework provides novel transparency and scalability to large carnivore reintroduction programs, which is increasingly required to secure the sustained support of impacted communities and stakeholder networks. Moreover, the incorporation of this framework into future practice and policy as an applied tool may directly benefit the recovery of at least 30 large carnivore species, while its principles may be applied more broadly across taxonomic groups for faunal rewilding and global ecosystem restoration.
Creating a genetic toolbox for the carbon-fixing, nitrogen-fixing and dehalogenating bacteriumXanthobacter autotrophicus
Authors: Van Voorhis Alexa F. , Sherbo Rebecca S. 
Published: June 2024

AbstractX. autotrophicusis a metabolically flexible microorganism with two key features: 1) The organism has adapted to grow on a wide variety of carbon sources including CO2, methanol, formate, propylene, haloalkanes and haloacids; and 2)X. autotrophicuswas the first chemoautotroph identified that could also simultaneously fix N2, meaning the organism can utilize CO2, N2, and H2for growth. This metabolic flexibility has enabled use ofX. autotrophicusfor gas fixation, the creation of fertilizers and foods from gases, and the dehalogenation of environmental contaminants. Despite the wide variety of applications that have already been demonstrated for this organism, there are few genetic tools available to explore and exploit its metabolism. Here, we report a genetic toolbox for use inX. autotrophicus. We first identified suitable origins of replication and quantified their copy number, and identified antibiotic resistance cassettes that could be used as selectable markers. We then tested several constitutive and inducible promoters and terminators and quantified their promoter strengths and termination efficiencies. Finally, we demonstrated that gene expression tools remain effective under both autotrophic and dehalogenative metabolic conditions to show that these tools can be used in the environments that makeX. autotrophicusunique. Our extensive characterization of these tools inX. autotrophicuswill enable genetic and metabolic engineering to optimize production of fertilizers and foods from gases, and enable bioremediation of halogenated environmental contaminants.
Genomic Convergence in Hibernating Mammals Elucidates the Genetics of Metabolic Regulation in the Hypothalamus
Authors: Ferris Elliott , Murcia Josue D. Gonzalez , Rodriguez Adriana Cristina , Steinwand Susan , Hörndli Cornelia Stacher , Traenkner Dimitri , Maldonado-Catala Pablo J , Gregg Christopher 
Published: June 2024

AbstractElucidating the genetic basis of mammalian metabolism could help define mechanisms central to health and disease. Here, we define conservedcis-regulatory elements (CREs) and programs for mammalian metabolic control. We delineate gene expression and chromatin responses in the mouse hypothalamus for 7 steps of the Fed-to-Fasted-to-Refed (FFR) response process. Comparative genomics of hibernating versus non-hibernating lineages then illuminatescis-elements showing convergent changes in hibernators. Hibernators accumulated loss-of-function effects for specific CREs regulating hypothalamic FFR responses. Multi-omics approaches pinpoint key CREs, genes, regulatory programs, and cell types in the divergence of hibernating and homeothermic lineages. The refeeding period after extended fasting is revealed as one critical period of chromatin remodeling with convergent genomic changes. This genetic framework is a step toward harnessing hibernator adaptations in medicine.One sentence summaryConvergent signals definecis-regulatory mechanisms behind food scarcity responses and hibernator-homeotherm divergence.
Computational Mechanisms Underlying Multi-Step Planning Deficits in Methamphetamine Use Disorder
Authors: Lavalley Claire A. , Mehta Marishka M. , Taylor Samuel , Chuning Anne E. , Stewart Jennifer L. , Huys Quentin J. M. , Khalsa Sahib S. , Paulus Martin P. , Smith Ryan 
Published: June 2024

AbstractCurrent theories suggest individuals with methamphetamine use disorder (iMUDs) have difficulty considering long-term outcomes in decision-making, which could contribute to risk of relapse. Aversive interoceptive states (e.g., stress, withdrawal) are also known to increase this risk. The present study analyzed computational mechanisms of planning in iMUDs, and examined the potential impact of an aversive interoceptive state induction. A group of 40 iMUDs and 49 healthy participants completed two runs of a multi-step planning task, with and without an anxiogenic breathing resistance manipulation. Computational modeling revealed that iMUDs had selective difficulty identifying the best overall plan when this required enduring negative short-term outcomes – a mechanism referred to as aversive pruning. Increases in reported craving before and after the induction also predicted greater aversive pruning in iMUDs. These results highlight a novel mechanism that could promote poor choice in recovering iMUDs and create vulnerability to relapse.