bluuebunny/crossref_metadata_2025 huggingface dataset:
A standard area diagram for Fusarium yellows rating in sugar beet (Beta vulgaris L.)
Authors: Todd Olivia E. , Hanson Linda E. , Dorn Kevin
Published: April 2024

Members of theFusarium oxysporumspecies complex are pathogens of sugar beet causing Fusarium yellows. Fusarium yellows can reduce plant stand, yield, and extractable sugar. Improving host plant resistance againstFusarium-induced diseases, like Fusarium yellows, represents an important long-term breeding target in sugar beet breeding programs. Current methods for rating Fusarium yellows disease severity rely on an ordinal scale, which limits precision for intermediate phenotypes. In this study, we aimed to improve the accuracy and precision of rating Fusarium yellows by developing a standard area diagram (SAD). Two SAD versions were created using images of sugar beets infected withFusarium oxysporumstrain F19. Each version was tested using inexperienced raters. Comparing both the pilot and improved version showed no statistical differences in Lin’s Concordance Correlation Coefficient (LCC) values to assess accuracy and precision between the two versions (Cb = 0.99 for both versions, ρc= 0.97 and 0.96 for version 1 and 2, respectively). In addition, five naïve Bayesian machine learning models which used pixel classification to determine disease score, were tested for congruency to human estimates in version 2. Root mean square error was lowest compared to the “true” values for the unweighted model and a model where necrotic tissue was given a 2x weight (12.4 and 12.6, respectively). The creation of this standard area diagram enables breeding programs to make consistent, accurate disease ratings regardless of personnel’s’ previous experience with Fusarium yellows. Additionally, more iterations of pixel quantification equations may overcome accuracy issues for rating Fusarium yellows.
WITHDRAWN: The Effects of Anthropogenic Electromagnetic Fields on the Behavior of Geomagnetically Displaced Skates
Authors: Newton Kyle C. , Donato Natalie H , Henkel Sarah , Chapple Taylor K
Published: April 2024

Withdrawal Statement

The authors have withdrawn this manuscript because while we stand behind this important work, we are addressing significant peer-review recommendations to provide a more robust product and will provide an updated version soon. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Interpolation of Microbiome Composition in Longitudinal Datasets
Authors: Peleg Omri , Borenstein Elhanan
Published: April 2024

The human gut microbiome significantly impacts health, prompting a rise in longitudinal studies that capture microbiome samples at multiple time points. Such studies allow researchers to characterize microbiome changes over time, but importantly, also present major analytical challenges due to incomplete or irregular sampling. To address this challenge, longitudinal microbiome studies often employ various interpolation methods, aiming to infer missing microbiome data. However, to date, a comprehensive assessment of such microbiome interpolation techniques, as well as best practice guidelines for interpolating microbiome data, are still lacking.

This work aims to fill this gap, rigorously implementing and systematically evaluating a large array of interpolation methods, spanning several different categories, for longitudinal microbiome interpolation. To assess each method and its ability to accurately infer microbiome composition at missing time points, we used three longitudinal microbiome datasets that follow individuals over a long period of time, and a leave-one-out approach.

Overall, our analysis demonstrated that the K-nearest neighbors algorithm consistently outperforms other methods in interpolation accuracy, yet, accuracy varied widely across datasets, individuals, and time. Factors such as microbiome stability, sample size, and the time gap between interpolated and adjacent samples significantly influenced accuracy, allowing us to develop a model for predicting the expected interpolation accuracy at a missing time point.

Our findings, combined, suggest that accurate interpolation in longitudinal microbiome data is feasible, especially in dense cohorts. Furthermore, using our predictive model, future studies can interpolate data only in time points where the expected interpolation accuracy is high.
Pre-clinical proof-of-concept of anti-fibrotic activity of caveolin-1 scaffolding domain peptide LTI-03 inex vivoprecision cut lung slices from patients with Idiopathic Pulmonary Fibrosis
Authors: MacKenzie BreAnne , Mahavadi Poornima , Jannini-Sa Yago Amigo Pinho , Creyns Brecht , Coelho Ana Lucia , Espindola Milena , Ruppert Clemens , Hötzenecker Konrad , Hogaboam Cory , Guenther Andreas
Published: April 2024

Rationale:While rodent lung fibrosis models are routinely used to evaluate novel antifibrotics, these models have largely failed to predict clinical efficacy of novel drug candidates for Idiopathic Pulmonary Fibrosis (IPF). Moreover, single target therapeutic strategies for IPF have failed and current multi-target standard of care drugs are not curative. Caveolin-1 (CAV-1) is an integral membrane protein, which, via its caveolin scaffolding domain (CSD), interacts with caveolin binding domains (CBD). CAV-1 regulates homeostasis, and its expression is decreased in IPF lungs. LTI-03 is a seven amino acid peptide derived from the CSD and formulated for dry powder inhalation; it was well tolerated in normal volunteers (NCT04233814) and a safety trial is underway in IPF patients (NCT05954988).Objectives:Anti-fibrotic efficacy of LTI-03 and other CSD peptides has been observed in IPF lung monocultures, and rodent pulmonary, dermal, and heart fibrosis models. This study aimed to characterize progressive fibrotic activity in IPF PCLS explants and to evaluate the antifibrotic effects of LTI-03 and nintedanib in this model.Methods:First, CBD regions were identified in IPF signaling proteins usingin silicoanalysis. Then, IPF PCLS (n=8) were characterized by COL1A1 immunostaining, multiplex immunoassays, and bulk RNA sequencing following treatment every 12hrs with LTI-03 at 0.5, 3.0, or 10 μM; nintedanib at 0.1 μM or 1 μM; or control peptide (CP) at 10 μM.Measurements and Main Results:CBDs were present in proteins implicated in IPF, including VEGFR, FGFR and PDGFR. Increased expression of profibrotic mediators indicated active fibrotic activity in IPF PCLS over five days. LTI-03 dose dependently decreased COL1A1 staining, and like nintedanib, decreased profibrotic proteins and transcripts. Unlike nintedanib, LTI-03 did not induce cellular necrosis signals.Conclusion:IPF PCLS explants demonstrate molecular activity indicative of fibrosis during 5 days in culture and LTI-03 broadly attenuated pro-fibrotic proteins and pathways, further supporting the potential therapeutic effectiveness of LTI-03 for IPF.
Light-induced Extracellular Vesicle Adsorption
Authors: Hisey Colin L. , Rima Xilal Y. , Doon-Ralls Jacob , Nagaraj Chiranth K. , Mayone Sophia , Nguyen Kim T. , Wiggins Sydney , Dorayappan Kalpana D.P. , Selvendiran Karuppaiyah , Wood David , Hu Chunyu , Patel Divya , Palmer Andre , Hansford Derek , Reategui Eduardo
Published: April 2024

The role of extracellular vesicles (EVs) in human health and disease has garnered considerable attention over the past two decades. However, while several types of EVs are known to interact dynamically with the extracellular matrix and there is great potential value in producing high-fidelity EV micropatterns, there are currently no label-free, high-resolution, and tunable platform technologies with this capability. We introduce Light-induced Extracellular Vesicle Adsorption (LEVA) as a powerful solution to rapidly advance the study of matrix- and surface-bound EVs and other particles. The versatility of LEVA is demonstrated using commercial GFP-EV standards, EVs from glioblastoma bioreactors, and E. coli outer membrane vesicles (OMVs), with the resulting patterns used for single EV characterization, single cell migration on migrasome-mimetic trails, and OMV-mediated neutrophil swarming. LEVA will enable rapid advancements in the study of matrix- and surface-bound EVs and other particles, and should encourage researchers from many disciplines to create novel diagnostic, biomimetic, immunoengineering, and therapeutic screening assays.
mastR: Marker Automated Screening Tool for multi-omics data
Authors: Chen Jinjin , Mohamed Ahmed , Bhuva Dharmesh D. , Davis Melissa J. , Tan Chin Wee
Published: April 2024

Motivation

Biomarker discovery and utilization is important and offers insight into potential underlying mechanisms of disease. Existing marker identification methods primarily focus on single cell RNA sequencing (scRNA-seq) data, with no specific automated methods designed to learn from the bulk RNA-seq data. Furthermore, when adapting scRNA-seq methods to bulk RNA-seq, the background expressions of non-targeted cell types are not accounted for. Here we bridge this gap with an automated marker identification method that works for bulk RNA sequencing data.

Results

We developedmastR, a novel computational tool for accurate marker identification from omics data. It leverages robust pipelines fromedgeRandlimmaR/Bioconductor packages, performing pairwise comparisons between groups, and aggregating the results through rank-product-based permutation test. A signal-to-noise ratio approach is implemented to minimize background signals. We assess the performance of amastR-derived NK cell signature against curated published signatures and find our derived signature performs as well if not better than published signatures. We also demonstrate the utility ofmastRon simulated scRNA sequencing data and provide examples ofmastRoutperformingSeuratin marker selection.

Availability and implementation

All statistical analyses were carried out using R (version 4.3.0 or higher) and Bioconductor (version 3.17 and higher).MastRis available as an R/Bioconductor package with a comprehensive vignette for ease of use (https://bioconductor.org/packages/release/bioc/html/mastR.html) and a guide hosted on GitHub:https://davislaboratory.github.io/mastR/.
Linkage: an interactive shiny app and R package for linking of DNA regulatory peaks to genes
Authors: Liu Zenghui , Chen Shaodong , Li Tianting , Zhang Chao , Luo Yuyan , Zheng Junxi , Lu Zixiao , Yang Jin , Xu Siwen
Published: April 2024

Existing studies have demonstrated that the integration analysis of transcriptomic and epigenomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, such investigations on large-scale sequencing data remain challenging for researchers or clinicians with limited bioinformatics knowledge. To facilitate the interpretation of gene regulatory landscape, we developed an R Shiny application and R package [Linking ofatac-seq togeneexpression data (Linkage)] for exploring and visualizing potential cis-regulatory elements (CREs) of genes based on ATAC-seq and RNA-seq data. Linkage offers six modules to systematically identify, annotate, and interpret potential gene regulatory elements from the whole genome step by step. Linkage can provide interactive visualization for the correlation between chromatin accessibility and gene expression. More than that, Linkage identifies transcription factors (TFs) that potentially drive the chromatin changes through identifying TF binding motifs within the CREs and constructing trans-regulatory networks of the target gene set. This powerful tool enables researchers to conduct extensive multiomics integration analysis and generate visually appealing visualizations that effectively highlight the relationship between genes and corresponding regulatory elements. With Linkage, users can obtain publishable results and gain deeper insights into the gene regulatory landscape.

Availability and implementation

‘Linkage’ is freely available as a Shiny web application (https://xulabgdpu.org.cn/linkage) and an R package (https://github.com/XuLab-GDPU/Linkage). The documentation is available at (https://aicplane.github.io/Linkage-tutorial/).
Pervasive but lagged responses in the composition of small mammal communities to a century of climate change
Authors: Abercrombie Ethan , Myers Jonathan A. , Smith Adam B.
Published: April 2024

Climate change has widespread effects on the distribution, abundance, and behavior of species around the world, leading to the reshuffling of ecological communities. However, it remains unclear whether individual species’ range shifts scale up to result in communities whose rate of change lag, lead, or track the rate of climate change. We capitalized on a century-old data set originally collected by Joseph Grinnell and his students, plus modern resurveys, to measure long-term compositional responses of small mammal communities to climate change in historical and modern eras across three regions in the Sierra Nevada of California (Lassen, Yosemite, and Sequoia and Kings Canyon National Parks). Across this period, mean annual temperature in each region increased and mean annual precipitation decreased. We tested whether small mammal communities have shifted their composition in favor of species more adapted to hot and dry conditions, processes known as thermophilization and mesophilization respectively. We found positive thermophilization rates (communities composed of more warm-adapted species) in all three regions and negative mesophilization rates (communities composed of dry-adapted species) in one of the three regions. Importantly, thermophilization and mesophilization rates lagged behind corresponding rates of climate change on average by 0.90-1.2 °C and 26.5-111.0 mm, but the magnitude of lags was unrelated to region, amount of climate change, or their interaction. Previous work demonstrated high intraspecific variability in range shifts across the three regions in our study. Our results suggest that the net effects of climate change will be directional at the scale of the ecological community, despite variability in individual species responses to environmental change and the varied mechanisms that govern them. Communities, like many individual species, may already be out of equilibrium with ambient climate.
A Personalized Metabolic Modelling Approach through Integrated Analysis of RNA-Seq-Based Genomic Variants and Gene Expression Levels in Alzheimer’s Disease
Authors: Uzuner Dilara , İlgün Atılay , Bozkurt Fatma Betül , Çakır Tunahan
Published: April 2024

Motivation

Alzheimer’s disease (AD) is known to cause alterations in brain metabolism. Furthermore, genomic variants in enzyme-coding genes may exacerbate AD-linked metabolic changes. Generating condition-specific metabolic models by mapping gene expression data to genome-scale metabolic models is a routine approach to elucidate disease mechanisms from a metabolic perspective. RNAseq data provides both gene expression and genomic variation information. Integrating variants that perturb enzyme functionality from the same RNAseq data may enhance model accuracy, offering insights into genome-wide AD metabolic pathology.

Results

Our study pioneers the extraction of both transcriptomic and genomic data from the same RNA-seq data to reconstruct personalized metabolic models. We mapped genes with significantly higher load of pathogenic variants in AD onto a human genome-scale metabolic network together with the gene expression data. Comparative analysis of the resulting personalized patient metabolic models with the control models showed enhanced accuracy in detecting AD-associated metabolic pathways compared to the case where only expression data was mapped on the metabolic network. Besides, several otherwise would-be missed pathways were annotated in AD by considering the effect of genomic variants.

Implementation

The scripts are available at

https://github.com/SysBioGTU/GenomicVariantsMetabolicModels.

Contact

tcakir@gtu.edu.tr
Antibiotic-inducedMalasseziaspp. expansion in infants promotes early-life immune dysregulation and airway inflammation in mice
Authors: Bernardes Erik van Tilburg , Gutierrez Mackenzie W. , Nguyen William N. T. , Mercer Emily M. , Ramay Hena R. , Glatthardt Thaís , Thomson Carolyn A. , Halim Tisha , Gopalakrishnan Nithya , Kalbfleish Kristen , Patel Kamala D. , McCoy Kathy D. , Freedman Stephen B. , Arrieta Marie-Claire
Published: April 2024

Antibiotics have deleterious consequences for the gut microbiome and can increase the risk of childhood asthma. While the effects of antibiotics on the bacterial microbiome and asthma risk are well characterized, their impact on the fungal microbiome (mycobiome) remains vastly unexplored. We investigated the effect of antibiotic use on the gut mycobiome in an observational, prospective clinical study of young infants. Antibiotic treatment resulted in increased fungal abundance and expansion of the yeastMalasseziaspp. Based on these findings, germ-free mouse pups were colonized with a defined consortium of mouse-derived bacteria (Oligo-MM12) with or withoutMalassezia restricta. Colonization with this yeast increased myeloid and lymphoid intestinal immune responses deemed critical in atopy development, and elevated airway inflammation in house-dust mite (HDM)-challenged mice. Further evaluation in eosinophil-deficient mice revealed that the observed immune response is partially dependent on this cell type. This translational work demonstrates that fungal overgrowth and expansion ofMalasseziaspp. are previously overlooked collateral effects of infant antibiotic use, which may offer a potential strategy to prevent or mitigate pediatric asthma and related conditions.

One Sentence Summary:Antibiotic-inducedMalasseziaspp. expansion in infants promotes early-life immune dysregulation and airway inflammation in gnotobiotic mice.
Interferon-sensitized hematopoietic progenitors dynamically alter organismal immunity
Authors: Guillamot Maria , Subudhi Ipsita , Paraskevopoulou Varvara , Prystupa Aleksandr , Sidhu Ikjot , Yeaton Anna , Laskou Maria , Hannemann Carmen , Donahoe Casey , Wiseman Destini , Aifantis Iannis , Naik Shruti , Weinstock Ada
Published: April 2024

Inflammation has enduring impacts on organismal immunity. However, the precise mechanisms by which tissue-restricted inflammation conditions systemic responses are poorly understood. Here, we leveraged a highly compartmentalized model of skin inflammation and identified a surprising type I interferon (IFN)- mediated activation of hematopoietic stem/progenitor cells (HSPCs) that results in profound changes to systemic host responses. Post-inflamed mice were protected from atherosclerosis and had worse outcomes following influenza virus infection. This IFN-mediated HSPC modulation was dependent on IFNAR signaling and could be recapitulated with the administration of recombinant IFNα. Importantly, the transfer of post-inflamed HSPCs was sufficient to transmit the immune suppression phenotype. IFN modulation of HSPCs was rooted both in long-term changes in chromatin accessibility and the emergence of an IFN- responsive functional state from multiple progenitor populations. Collectively, our data reveal the profound and enduring effect of transient inflammation and more specifically type I IFN signaling and set the stage for a more nuanced understanding of HSPC functional modulation by peripheral immune signals.
Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG data from older Cantonese speakers
Authors: Momenian Mohammad , Ma Zhengwu , Wu Shuyi , Wang Chengcheng , Brennan Jonathan , Hale John , Meyer Lars , Li Jixing
Published: April 2024

Currently, the field of neurobiology of language is based on data from only a few Indo-European languages. The majority of this data comes from younger adults neglecting other age groups. Here we present a multimodal database which consists of task-based and resting state fMRI, structural MRI, and EEG data while participants over 65 years old listened to sections of the story The Little Prince in Cantonese. We also provide data on participants’ language history, lifetime experiences, linguistic and cognitive skills. Audio and text annotations, including time- aligned speech segmentation and prosodic information, as well as word-by-word predictors such as frequency and part-of-speech tagging derived from natural language processing (NLP) tools are included in this database. Both MRI and EEG data diagnostics revealed that the data has good quality. This multimodal database could advance our understanding of spatiotemporal dynamics of language comprehension in the older population and help us study the effects of healthy aging on the relationship between brain and behaviour.
Pronounced expression of extracellular matrix proteoglycans regulated by Wnt pathway underlies the parallel evolution of lip hypertrophy in East African cichlids
Authors: Machii Nagatoshi , Hatashima Ryo , Niwa Tatsuya , Taguchi Hideki , Kimirei Ismael A. , Mrosso Hillary D. J. , Aibara Mitsuto , Nagasawa Tatsuki , Nikaido Masato
Published: April 2024

Cichlid fishes inhabiting the East African Great Lakes, Victoria, Malawi, and Tanganyika, are textbook examples of parallel evolution, as they have acquired similar traits independently in each of the three lakes during the process of adaptive radiation. In particular, “hypertrophied lip” has been highlighted as a prominent example of parallel evolution. However, the underlying molecular mechanisms remain poorly understood. In this study, we conducted an integrated comparative analysis between the hypertrophied and normal lips of cichlids across three lakes based on histology, proteomics, and transcriptomics. Histological and proteomic analyses revealed that the hypertrophied lips were characterized by enlargement of the proteoglycan-rich layer, in which versican and periostin proteins were abundant. Transcriptome analysis revealed that the expression of extracellular matrix-related genes, including collagens, glycoproteins and proteoglycans, was higher in hypertrophied lips, regardless of their phylogenetic relationships. In addition, the genes in Wnt signaling pathway, which is involved in promoting proteoglycan expression, was highly expressed in both the juvenile and adult stages of hypertrophied lips. Our comprehensive analyses showed that hypertrophied lips of the three different phylogenetic origins can be explained by similar proteomic and transcriptomic profiles, which may provide important clues into the molecular mechanisms underlying phenotypic parallelisms in East African cichlids.
Sex-peptide targets distinct higher order processing neurons in the brain to induce the female post-mating response
Authors: Nallasivan Mohanakarthik P. , Singh Deepanshu N.D. , Saleh Mohammed Syahir R. S. , Soller Matthias
Published: April 2024

Sex-peptide (SP) transferred during mating induces female post-mating responses including refractoriness to re-mate and increased oviposition inDrosophila. Yet, where SP target neurons reside, remained uncertain. Here we show that expression of membrane-tethered SP (mSP) in the head or trunk either reduces receptivity or increases oviposition, respectively. Using fragments from large regulatory regions ofSex Peptide Receptor,fruitlessanddoublesexgenes together with intersectional expression of mSP, we identified distinct interneurons in the brain and abdominal ganglion controlling receptivity and oviposition. These interneurons can induce post-mating responses through SP received by mating. Trans-synaptic mapping of neuronal connections reveals input from sensory processing neurons and two post-synaptic trajectories as output. Hence, SP target neurons operate as key integrators of sensory information for decision of behavioural outputs. Multi-modularity of SP targets further allows females to adjust SP-mediated male manipulation to physiological state and environmental conditions for maximizing reproductive success.
Impacts of global warming on fertility of male fishes: evidence from meta-analysis of temperature effects on spermatozoa motility
Authors: Cheng Yu , Wang Jinhai , Alavi Sayyed Mohammad Hadi , Zhang Songpei , Linhartová Zuzana , Roy Deepali Rahi , Shazada Nururshopa Eskander , Dzyuba Borys , Linhart Otomar
Published: April 2024

Studies have demonstrated adverse effects of global warming on aquatic ecosystems from the abiotic to the biotic level. In the present work, a meta-analysis study was conducted to elucidate the effects of global warming on spermatozoa functions, which are key determinants of male fertility. We recruited 245 data records from a pool of empirical studies, which includes 20 studies spanning 20 cold- and warm-water fish species, to identify the effects of increased water temperature (IWT) on determinants of sperm fertility in fishes. Data were systematically re-processed and re-analyzed to determine the overall effects of IWT on sperm kinetics such as motility (MOT), duration of motility (DSM), curvilinear velocity (VCL), rectilinear velocity (VSL) and average path velocity (VAP), as well as on enzymatic activities for energy supply (EAES) and antioxidant enzyme activity (ANEA). The standardized mean difference was calculated for each study, with positive values indicating higher performance under IWT. Results showed that (a) the overall effect size for MOT was more negative in cold-water fishes (-1.22) than in warm-water fishes (-0.98). (b) Each 1 °C increase in the activation medium reduced MOT by 1.30% (cold-water fishes) and 3.47% (warm-water fishes). (c) The IWT negatively affected DSM, decreasing it by 10 s (cold-water species) and 5.64 s (warm-water species) per degree of IWT. (d) Spermatozoa velocity (VCL and VSL) was increased by IWT in warm-water species. In conclusion, this study shows that IWT negatively affects sperm motility kinetics, suggesting an impact of global warming on fish reproduction.
Coastal oceanographic connectivity estimates at the global scale
Authors: Assis Jorge , Legrand Terence , Fragkopoulou Eliza , Serrão Ester A. , Araújo Miguel
Published: April 2024

Motivation

Oceanographic connectivity driven by ocean currents is critical in determining the distribution of marine biodiversity. It mediates the genetic and individual exchange between populations, from structuring dispersal barriers that promote long-term isolation to enabling long-distance dispersal that underpins species expansion and resilience against climate change. Despite its significance, comprehensive estimates of oceanographic connectivity on a global scale remain unavailable, while traditional approaches, often simplistic, fail to capture the complexity of oceanographic factors contributing to population connectivity. This gap hinders a deeper understating of species’ dispersal ecology, survival, and evolution, ultimately precluding the development of effective conservation strategies aimed at preserving marine biodiversity. To address this challenge, we present a comprehensive dataset of connectivity estimates along the world’s coastlines, known for their rich marine biodiversity. These estimates are derived from a biophysical modelling framework that combines high-resolution ocean current data with graph theory to predict multi-generational stepping-stone connectivity. Alongside, we provide coastalNet, an R package designed to streamline access, analysis, and visualization of connectivity estimates. This tool enhances the utility and application of the data, adhering to the FAIR principles of Findability, Accessibility, Interoperability, and Reusability. The dataset and package set a new benchmark for research in oceanographic connectivity, allowing a better exploration of the complex dynamics of coastal marine ecosystems.

Main types of variables contained

Pairwise connectivity estimates (probability and time) between coastal sites.

Spatial location and grain

Global, equal-area hexagons with 8.45 km edge length.

Time period and grain

Daily, from 2000 to 2020.

Major taxa and level of measurement

Coastal marine biodiversity.

Software format

A package of functions developed for R software.
Ecological divergence of sibling allopolyploid marsh orchids is associated with species specific plasticity and distinct fungal communities
Authors: Emelianova Katie , Hawranek Anna-Sophie , Eriksson Mimmi C. , Wolfe Thomas M. , Paun Ovidiu
Published: April 2024

Phenotypic plasticity, the dynamic adjustment of traits to environmental variations, is crucial for enabling species to exploit broader niches and withstand suboptimal conditions. This adaptability is particularly relevant for newly formed allopolyploids, which possess redundant gene copies and must become established in diverse environments distinct from their parents and other relatives. By evaluating gene expression and root mycobiome among two ecologically divergent sibling allopolyploid marsh orchids (Dactylorhiza majalisandD. traunsteineri) in reciprocal transplants at localities where both species are native, we aimed to understand the drivers of species persistence in the face of interspecific gene flow. Despite consistent abiotic differences characterising the alternative environments at each locality, the majority of gene expression differences between the allopolyploids appears to be plastic. Ecologically relevant processes, such as photosynthesis and transmembrane transport, include some genes that are differentially expressed between the two orchids regardless of the environment, while others change their activity plastically in one species or the other. This suggests that although plasticity helps define the specific ecological range of each sibling allopolyploid, it also mediates gene flow between them, thereby preventing differentiation. Extending our investigations to the root mycobiome, we uncover more diverse fungal communities for either species when grown in the environment with nutrient-poor soils, indicating that both abiotic and biotic factors drive the distribution of sibling marsh orchids. Altogether, our results indicate that plasticity can simultaneously promote diversification and homogenization of lineages, influencing the establishment and persistence of recurrently formed allopolyploid species.

Significance statement

This study highlights the role of phenotypic plasticity in the persistence and distribution of sibling allopolyploid marsh orchids (Dactylorhiza majaliss.l.). By examining gene expression and the diversity of root mycobiome across reciprocal transplantations in native environments, we uncover high plasticity that facilitates adaptation and gene flow, thereby promoting both diversification and homogenization. These findings underscore the importance of plasticity in the establishment and long-term survival of allopolyploid species across the landscape.
Inferring species interactions from co-occurrence networks with environmental DNA metabarcoding data in a coastal marine food-web
Authors: Boyse Elizabeth , Robinson Kevin P. , Carr Ian M. , Beger Maria , Goodman Simon J.
Published: April 2024

Improved understanding of biotic interactions is necessary to accurately predict the vulnerability of ecosystems to climate change. Recently, co-occurrence networks built from environmental DNA (eDNA) metabarcoding data have been advocated as a means to explore interspecific interactions in ecological communities exposed to different human and environmental pressures. Co-occurrence networks have been widely used to characterise microbial communities, but it is unclear if they are effective for characterising eukaryotic ecosystems, or whether biotic interactions drive inferred co-occurrences. Here, we assess spatiotemporal variability in the structure and complexity of a North Sea coastal ecosystem inferred from co-occurrence networks and food webs using 60 eDNA samples covering vertebrates and other eukaryotes. We compare topological characteristics and identify potential keystone species,i.e., highly connected species, across spatial and temporal subsets, to evaluate variance in community composition and structure. We find consistent trends in topological characteristics across co-occurrence networks and food webs, despite trophic interactions forming a minority of significant co-occurrences. Known keystone species in food webs were not highly connected in co-occurrence networks. The lack of significant trophic interactions detected in co-occurrence networks may result from ecological complexities such as generalist predators having flexible interactions or behavioural partitioning, as well as methodological limitations such as the inability to distinguish age class with eDNA, or co-occurrences being driven by other interaction types or shared environmental requirements. Deriving biotic interactions with co-occurrence networks constructed from eDNA requires further validation in well-understood ecosystems, and improved reporting of methodological limitations, such as species detection uncertainties, which could influence inferred ecosystem complexity.
EpiCHAOS: a metric to quantify epigenomic heterogeneity in single-cell data
Authors: Kelly Katherine , Scherer Michael , Braun Martina Maria , Lutsik Pavlo , Plass Christoph
Published: April 2024

Epigenetic heterogeneity is a fundamental property of biological systems, and is recognized as a potential driver of tumor plasticity and therapy resistance. Single-cell epigenomics technologies have been widely employed to study epigenetic variation between – but not within – cellular clusters. We introduce epiCHAOS: a quantitative metric of cell-to-cell heterogeneity, applicable to any single-cell epigenomics data type. After validation in synthetic datasets, we applied epiCHAOS to investigate global and region-specific patterns of epigenetic heterogeneity across diverse biological systems. EpiCHAOS provides an excellent approximation of stemness and plasticity in development and malignancy, making it a valuable addition to single-cell cancer epigenomics analyses.
Biodetection of an odor signature in white-tailed deer associated with infection by chronic wasting disease prions
Authors: Golden Glen J. , Ramirez Elizabeth A. , Stevens Hayley N. , Bourbois Jennifer , Grove Daniel , Bowen Richard A. , DeLiberto Thomas J. , Kimball Bruce A.
Published: April 2024

Chronic wasting disease (CWD) has become a major concern among those involved in managing wild and captive cervid populations. CWD is a fatal, highly transmissible spongiform encephalopathy caused by an abnormally folded protein, called a prion. Prions are present in a number of tissues, including feces and urine in CWD infected animals, suggesting multiple modes of transmission, including animal-to-animal, environmental, and by fomite. CWD management is complicated by the lack of practical, non-invasive, live-animal screening tests. We previously demonstrated that ferrets were able to detect and discriminate fecal samples from ducks infected or not infected with avian influenza virus based on odor. That work clearly predicted that animal biodetectors can be trained to identify populations and/or individuals infected with CWD via detection of fecal odors. Such a tool may also prove useful in identifying potentially infected live animals, carcasses, urine, feces, and contaminated environments. Toward this goal, dogs were trained to detect and discriminate CWD infected individuals from non-infected deer in a laboratory setting. Dogs were tested with novel panels of fecal samples demonstrating the dogs’ ability to generalize a learned odor profile to novel odor samples based on infection status. Additionally, dogs were transitioned from alerting to fecal samples to an odor profile that consisted of CWD infection status with a different odor background using different sections of gastrointestinal tracts. These results indicated that canine biodetectors can discriminate the specific odors emitted from the feces of non-infected versus CWD infected white-tailed deer as well as generalizing the learned response to other tissues collected from infected individuals. These findings suggest that the health status of wild and farmed cervids can be evaluated non-invasively for CWD infection via monitoring of volatile metabolites thereby providing an effective tool for rapid CWD surveillance.
Finding Fluorescence: Utilizing community science to document novel biofluorescence occurrences and encourage community engagement in science
Authors: Burke Hannah , Serrano Lauren , Lemmon Emily , Whitcher Courtney
Published: April 2024

Fluorescence, a form of photoluminescence, is the emission of light at a longer wavelength by a substance when exposed to shorter-wavelength energy. Biofluorescence, which can be observed in living organisms, involves the absorption of light at one wavelength and re-emission at a longer wavelength due to fluorophores in specialized cells or structures. While initially studied in marine organisms, attention has shifted to exploring biofluorescence in terrestrial organisms, revealing roles in reproduction, camouflage, communication, and prey attraction across phyla. Community science databases engage the public in data collection, fostering scientific discovery and strengthening the science-society connection. Such databases have become valuable tools and have aided scientists in understanding the natural history of many different traits in organisms. This paper introducesFinding Fluorescence, the first biofluorescence-based community science website established in 2020 to gather public observations of biofluorescent organisms. The study presents at least 15 novel biofluorescence accounts spanning five phyla, 15 families, and 15 species. The observations collected fromFinding Fluorescencecontribute to our understanding of fluorescence in organisms and provide insight into possible ecological functions. We emphasize the importance of community engagement in scientific exploration and encourage future studies to incorporate such aspects into their research.
Treg fitness as a biomarker for disease activity in Juvenile Idiopathic Arthritis
Authors: Attrill Meryl H. , Shinko Diana , Viveiros Telma Martins , Milighetti Martina , de Gruijter Nina M. , Jebson Bethany , Kartawinata Melissa , Rosser Elizabeth C. , Wedderburn Lucy R. ,   CHARMS study,   JIAP study, Pesenacker Anne M.
Published: April 2024

Juvenile Idiopathic Arthritis (JIA) is an autoimmune condition characterised by persistent flares of joint inflammation. However, no reliable biomarker exists to predict the erratic disease course. Normally, regulatory T cells (Tregs) maintain immune tolerance, with altered Tregs associated with autoimmunity. Treg signatures have shown promise in monitoring other autoimmune conditions, therefore a Treg gene and/or protein signature could offer novel biomarker potential for predicting disease activity in JIA.

Machine learning on our nanoString Treg gene signature on peripheral blood (PB) Tregs generated a model to distinguish active JIA (active joint count, AJC≥1) Tregs from healthy controls (HC, AUC=0.9875). Biomarker scores from this model successfully differentiated inactive (AJC=0) from active JIA PB Tregs. Moreover, scores correlated with clinical activity scores (cJADAS), and discriminated subclinical disease (AJC=0, cJADAS≥0.5) from remission (AUC=0.8980, Sens=0.8571, Spec= 0.8571).

To investigate altered Treg fitness in JIA by protein expression, we utilised spectral flow cytometry and unbiased analysis. Three Treg clusters were increased in active JIA PB, including CD226highCD25loweffector-like Tregs and CD39-TNFR2-Helioshigh, while a 4-1BBlowTIGITlowID2intermediateTreg cluster predominated in inactive JIA PB (AJC=0). The ratio of these Treg clusters correlated to cJADAS, and higher ratios could predict inactive individuals that flared by 6-month follow-up.

Thus, we demonstrate altered Treg signatures and subsets as an important factor, and useful biomarker, for disease progression versus remission in JIA, revealing genes and proteins important in Treg fitness. Ultimately, PB Treg fitness measures could serve as routine biomarkers to guide disease and treatment management to sustain remission in JIA.
The nuclear sulfenome ofArabidopsis: spotlight on histone acetyltransferase GCN5 regulation through functional thiols
Authors: Smet Barbara De , Yang Xi , Plskova Zuzana , Castell Carmen , Fernandez-Fernandez Alvaro , Dard Avilien , Mhamdi Amna , Vertommen Didier , Chan Kai Xun , Pyr dit Ruys Sébastien , Messens Joris , Kerchev Pavel I. , Breusegem Frank Van
Published: April 2024

Partial reduction of oxygen during energy generating metabolic processes in aerobic life forms results in the production of reactive oxygen species (ROS). In plants, ROS production is heightened during periods of both abiotic and biotic stress, which imposes a significant overload on the antioxidant systems. Hydrogen peroxide (H2O2) holds a central position in cellular redox homeostasis and signalling, playing an important role by oxidising crucial cysteines to sulfenic acid (-SOH), considered as a biologically relevant post-translational modification (PTM). Until now, the role of the nucleus in the cellular redox homeostasis has been relatively underexplored. The regulation of histone-modifying enzymes by oxidative PTMs on redox-active cysteines or tyrosine residues is particularly intriguing as it allows the integration of redox signalling mechanisms with chromatin control of transcriptional activity. One of the most extensively studied histone acetyltransferases is the conserved GENERAL CONTROL NONDEPRESSIBLE 5 (GCN5) complex. This study investigated the nuclear sulfenome inArabidopsis thalianaby expressing a nuclear variant of the Yeast Activation Protein-1 (YAP) probe, identifying 225 potential redox-active nuclear proteins subject to sulfenylation. Mass spectrometry analysis further confirmed the sulfenylation of GCN5 at specific cysteine residues, with their functional significance and impact on the protein-protein interaction network assessed through cysteine-to-serine mutagenesis.

Highlight

Protein cysteine thiols are post-translationally modified under oxidative stress. Through thein vivocapturing of nuclear proteins undergoing sulfenylation inArabidopsis, we highlight the functionality of particular cysteines in the histone acetyltransferase GCN5.
StomaVision: stomatal trait analysis through deep learning
Authors: Wu Ting-Li , Chen Po-Yu , Du Xiaofei , Wu Heiru , Ou Jheng-Yang , Zheng Po-Xing , Wu Yu-Lin , Wang Ruei-Shiuan , Hsu Te-Chang , Lin Chen-Yu , Lin Wei-Yang , Chang Ping-Lin , Ho Chin-Min Kimmy , Lin Yao-Cheng
Published: April 2024

StomaVision is an automated tool designed for high-throughput detection and measurement of stomatal traits, such as stomatal number, pore size, and closure rate. It provides insights into plant responses to environmental cues, streamlining the analysis of micrographs from field-grown plants across various species, including monocots and dicots. Enhanced by a novel collection method that utilizes video recording, StomaVision increases the number of captured images for robust statistical analysis. Accessible via an intuitive web interface at  and available for local use in a containerized environment at , this tool ensures long-term usability by minimizing the impact of software updates and maintaining functionality with minimal setup requirements. The application of StomaVision has provided significant physiological insights, such as variations in stomatal density, opening rates, and total pore area under heat stress. These traits correlate with critical physiological processes, including gas exchange, carbon assimilation, and water use efficiency, demonstrating the tool’s utility in advancing our understanding of plant physiology. The ability of StomaVision to identify differences in responses to varying durations of heat treatment highlights its value in plant science research.

Plain language summary

StomaVision is a tool that automatically counts and measures tiny openings on plant leaves, helping us learn how plants deal with their surroundings. It is easy to use and works well with various plant species. This tool helps scientists see how plants change under stress, making plant research easier and more accurate.
A multidisciplinary on-farm survey of maize-bean intercropping highlights key considerations for reviving traditional agricultural systems.
Authors: Vazeux-Blumental Noa , Mathieu Laura , Trabac Theo , Palaffre Carine , Lagardere Bernard , Carraretto Maryse , Bauland Cyril , Le Guilloux Martine , Paysant-Le Roux Christine , Caius Jose , Marmagne Anne , Enjalbert Jerome , Flutre Timothee , Le Cadre Edith , Parnaudeau Virginie , Muller Daniel , Moenne-Loccoz Yvan , Manicacci Domenica , Tenaillon Maud I
Published: April 2024

Cereal-legume intercropping is a promising strategy for sustainable agroecosystems. The traditional intercropping of maize and bean is experiencing a revival in some modern agricultural settings, such as in southwestern France, where maize hybrids are intercropped with the commercialized Tarbais bean. We conducted on-farm surveys to address the following questions: How do intercropping and sole cropping impact yield, nutrient uptake and rhizosphere bacterial assemblages? Do positive or negative interactions between maize and bean dominate in intercropping at the phenotypic level? What is the effect of intercropping at the transcriptomic level? We recorded technical itineraries, conducted yield and nutrient measurements, and characterized soil bacterial assemblages via metabarcoding to compare sole cropped maize and beans with intercropped plants. We also set up a controlled field assay to quantify differentially expressed (DE) genes between cropping systems. We observed an increase in bacterial diversity in intercropping and a significant impact of the cropping system on agronomic traits, with frequent farm-by-cropping system interactions. Competition dominated maize-bean intercropping, with 56 out of 90 significant negative correlations between maize and bean traits. The bean displayed lower yield in intercropping but greater seed size, weight, nitrogen and carbon percentages. From the controlled field assay, we found that competition primarily affected the beans and their transcriptome, with nearly 30% of DE genes detected while none were found in maize. Overall, our findings suggest that synergies between the two crops are likely hindered, underscoring the importance of carefully considering partner varieties and technical itineraries in the revival of traditional agricultural systems.
Bayesian parameter inference for epithelial mechanics
Authors: Yan Xin , Ogita Goshi , Ishihara Shuji , Sugimura Kaoru
Published: April 2024

Cell-based mechanical models, such as the Cell Vertex Model (CVM), have proven useful for studying the mechanical control of epithelial tissue dynamics. We recently developed a statistical method called image-based parameter inference for formulating CVM model functions and estimating their parameters from image data of epithelial tissues. In this study, we employed Bayesian statistics to improve the utility and flexibility of image-based parameter inference. Tests on synthetic data confirmed that both our non-hierarchical and hierarchical Bayesian models provide accurate estimates of model parameters. By applying this method toDrosophilawings, we demonstrated that the reliability of parameter estimation is closely linked to the mechanical anisotropies present in the tissue. Moreover, we revealed that the cortical elasticity term is dispensable for explaining force-shape correlationsin vivo. We anticipate that the flexibility of the Bayesian statistical framework will facilitate the integration of various types of information, thereby contributing to the quantitative dissection of the mechanical control of tissue dynamics.