bluuebunny/crossref_metadata_2025 huggingface dataset:
Parapipe: a Pipeline for Handling Parasite NGS Datasets and its Application to Cryptosporidium
Authors: Morris Arthur V. , Robinson Guy , Chalmers Rachel , Caccio Simone , Connor Tom
Published: January 2025

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Cryptosporidium, a protozoan parasite of significant public health concern, is responsible for severe diarrheal diseases, particularly in immunocompromised individuals and young children in resource-limited settings. Analysis of whole genome next generation sequencing (NGS) data is a critical next step in improving our understanding ofCryptosporidiumepidemiology, transmission dynamics, and genetic diversity. However, effective analysis of NGS data in a public health context necessitates the development of robust, validated bioinformatics tools. Here, we present Parapipe, a modular ISO accreditable bioinformatics pipeline designed for high-throughput processing and analysis ofCryptosporidiumNGS datasets. Built using Nextflow DSL2 and containerized with Singularity, Parapipe is portable, scalable, and capable of end-to-end analyses, including quality control, variant calling, multiplicity of infection (MOI) investigations and phylogenomic clustering analysis.

Using both simulated and real-world datasets, we demonstrate Parapipe’s ability to resolve genetic heterogeneity, identify mixed infections, and generate high-resolution phylogenomic insights. Here, we use it to carry out a comparison between whole genome single nucleotide polymorphism (wgSNP) typing and the conventionally used gp60 molecular typing scheme. Compared to existing pipelines, Parapipe uniquely integrates MOI analysis, enabling the differentiation of mixed infections and supporting epidemiological investigations. Parapipe’s design facilitates integration with geographic, demographic, epidemiological and environmental data, enhancing its utility for tracking transmission pathways and outbreak sources.

Parapipe represents a significant advance in utilising genomics for public health surveillance ofCryptosporidium, offering a streamlined and reproducible framework for analysis with potential application to other pathogenic protozoa. By automating complex workflows and enabling detailed genomic characterization, Parapipe provides a valuable tool for public health agencies and researchers, supporting efforts to mitigate the global burden of cryptosporidiosis.
High-throughput assessment of exercise-induced adaptations and muscle function in health and ageing
Authors: Malita Alina , Texada Michael J. , Kubrak Olga , Lassen Mette , Skakkebaek Anne H. , Bradic Ivan , Larsen Martin R. , Ahrentløv Nadja , Rewitz Kim
Published: January 2025

Exercise improves metabolic health, enhances insulin sensitivity, and preserves muscle function, making it a core intervention to combat age-related decline and metabolic disorders. However, large-scale genetic and pharmacological screens to uncover exercise-induced adaptations remain challenging in mammalian models due to their complexity and cost. Here, we present the ClimbMaster, a fully automated, computer-controlled platform for assessing exercise-induced adaptations and physical performance in the fruit flyDrosophila. The system uses repeated climbing exercises to simulate endurance training, enabling precise measurements of climbing speed and endurance across different conditions and life stages. Using the ClimbMaster, we demonstrate that exercise improves endurance, promotes fat loss, and enhances insulin-mediated glucose uptake and modulates insulin sensitivity in muscle, highlighting key conserved features of exercise physiology between flies and mammals. We also show that rapamycin, a TOR inhibitor, mitigates age-related performance decline. This platform enables high-throughput screens to investigate genetic and environmental factors influencing muscle health, aging, and insulin resistance, providing a scalable and versatile tool for the identification of novel therapeutic targets to improve healthspan and physical performance.
Unveiling the Conformational Dynamics of the Histone Tails Using Markov State Modeling
Authors: Patel Rutika , Loverde Sharon M.
Published: January 2025

Biomolecules predominantly exert their function through altering conformational dynamics. The nucleosome core particle (NCP) is the fundamental unit of chromatin. DNA with ∼146 base pairs wrap around the histone octamer to form a nucleosome. The histone octamer is comprised of two copies of each histone protein (H3, H4, H2A, and H2B) with a globular core and disordered N-terminal tails. Epigenetic modifications of the histone N-terminal tails play a critical role in the regulation of chromatin structure and biological processes such as transcription and DNA repair. Here, we report all-atomistic molecular dynamics (MD) simulations of the nucleosome at microsecond timescales to construct Markov state models (MSMs) to elucidate distinct conformations of the histone tails. We employ the time-lagged independent component analysis (tICA) to capture their essential slow dynamics, with k-means clustering used to discretize the conformational space. MSMs unveil distinct states and transition probabilities to characterize the dynamics and kinetics of the tails. Next, we focus on the H2B tail, one of the least studied tails. We show that acetylation increases secondary structure formation, with an increase in transition rates. These findings will aid in understanding the functional implications of tail conformations in nucleosome stability and gene regulation.

Significance Statement

The nucleosome is the fundamental repeat unit of chromatin, composed of a histone octamer and DNA. Each histone has a globular core and N-terminal tail regions. N-terminal tails are major sites for post-translational modifications, chromatin structure, and gene regulation. Using all-atom molecular dynamics simulations of the nucleosome to examine the dynamics of histone tails and analyze the effects of one of the histone modifications, such as acetylation on histone tails. We explore tail dynamics and kinetics using Markov State Models (MSMs) to gain insight into histone tail structural changes. Acetylation of the H2B tail shows an increased dynamics of the tail based on transition rates. Our study characterizes transition rates of all histone tails that can influence nucleosome plasticity and gene regulation.
The epigenetic factorZrf1regulates intestinal stem cell proliferation during midgut regeneration
Authors: Shun Li Joshua Shing , Liu Ying , Kim Ah-Ram , Qadiri Mujeeb , Xu Jun , Xia Baolong , Binari Richard , Asara John M. , Hu Yanhui , Perrimon Norbert
Published: January 2025

Stem cells are essential for tissue maintenance and regeneration, balancing self-renewal and differentiation to support homeostasis and repair. Through an RNAi screen in theDrosophilamidgut, we identified the epigenetic factor Zrf1 as a critical regulator of intestinal stem cell (ISC) proliferation. Functional analyses reveal that Zrf1 integrates inputs from multiple signaling pathways and interacts with components of the RNA-induced silencing complex (RISC). Zrf1 mutants exhibit elevated expression of transposable elements (TEs) and chromatin disruption, highlighting a broader role in genome stability. Single-nuclei RNA sequencing (snRNA-seq) further demonstrated the influence of Zrf1 on chromatin organization and TE repression, particularly within stem cell progenitors. Our findings suggest that Zrf1 is potentially a key chromatin regulator necessary for maintaining stem cell proliferation and genome integrity, enhancing our understanding of the molecular controls underlying stem cell function and chromatin dynamics.
Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes
Authors: Kellom Matthew , Berg Maureen , Chen I-Min A. , Chu Ken , Clum Alicia , Huntemann Marcel , Ivanova Natalia N. , Kyrpides Nikos C. , Mukherjee Supratim , Reddy T. B. K. , Roux Simon , Seshadri Rekha , Szabo Gitta , Varghese Neha J. , Woyke Tanja , Eloe-Fadrosh Emiley A.
Published: January 2025

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool - a tetranucleotide-informed metagenome stability diagram - that is publicly available in the Integrated Microbial Genomes and Microbiomes (IMG/M) platform for metagenome-ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments, and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change.

Importance

Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.
A Single-Cell Atlas of the Upper Respiratory Epithelium Reveals Heterogeneity in Cell Types and Patterning Strategies
Authors: Foote Alexander G. , Sun Xin
Published: January 2025

The upper respiratory tract, organized along the pharyngolaryngeal-to-tracheobronchial axis, is essential for homeostatic functions such as breathing and vocalization. The upper respiratory epithelium is frequently exposed to pollutants and pathogens, making this an area of first-line defense against respiratory injury and infection. The respiratory epithelium is composed of a rich array of specialized cell types, each with unique capabilities in immune defense and injury repair. However, the precise transcriptomic signature and spatial distribution of these cell populations, as well as potential cell subpopulations, have not been well defined. Here, using single cell RNAseq combined with spatial validation, we present a comprehensive atlas of the mouse upper respiratory epithelium. We systematically analyzed our rich RNAseq dataset of the upper respiratory epithelium to reveal 17 cell types, which we further organized into three spatially distinct compartments: theTmprss11a+ pharyngolaryngeal, theNkx2-1+ tracheobronchial, and theDmbt1+ submucosal gland epithelium. We profiled/analyzed the pharyngolaryngeal epithelium, composed of stratified squamous epithelium, and identified distinct regional signatures, including a Keratin gene expression code. In profiling the tracheobronchial epithelium, which is composed of a pseudostratified epithelium-with the exception of the hillock structure-we identified that regional luminal cells, such as club cells and basal cells, show varying gradients of marker expression along the proximal-distal and/or dorsal-ventral axis. Lastly, our analysis of the submucosal gland epithelium, composed of an array of cell types, such as the unique myoepithelial cells, revealed the colorful diversity of between and within cell populations. Our single-cell atlas with spatial validation highlights the distinct transcriptional programs of the upper respiratory epithelium and serves as a valuable resource for future investigations to address how cells behave in homeostasis and pathogenesis.

Highlights

- Defined three spatially distinct epithelial compartments,Tmprss11a+ pharyngolaryngeal,Nkx2-1+ tracheobronchial, andDmbt1+ submucosal gland, comprising 17 total cell types

- Profiled Keratin gene expression code along proximal-distal and basal-luminal axes and highlighted “stress-induced” Keratins KRT6A and KRT17 at homeostasis

- Demarcated expression gradients ofScgb1a1+ andScgb3a2+club cells along the proximal-distal axes

- Specified submucosal gland cell heterogeneity includingNkx3-1+mucin-producing cells, with ACTA2+ basal myoepithelial cells exhibiting gene profile for neuroimmune mediated signaling
Decoding Mechanisms of PTEN Missense Mutations in Cancer and Autism Spectrum Disorder using Interpretable Machine Learning Approaches
Authors: Yang Miao , Wang Jingran , Zhou Ziyun , Li Wentian , Verkhivker Gennady , Xiao Fei , Hu Guang
Published: January 2025

Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homolog (PTEN) serves as a paradigmatic model for mapping its mutational landscape and identifying genotypic predictors of distinct phenotypic outcomes, including cancer and autism spectrum disorder (ASD). Despite extensive research into the genotype-phenotype correlations of PTEN mutations, the mechanisms underlying the dual association of specific PTEN mutations with both cancer and ASD (PTEN-cancer/ASD mutations) remain elusive. This study introduces an integrative approach that combines machine learning (ML) with structural dynamics to elucidate the molecular effects of PTEN-cancer/ASD mutations. Analysis of biophysical and network biology-based signatures reveals a complex energetic and functional landscape. Subsequently, an ML model and corresponding integrated score were developed to classify and predict PTEN-cancer/ASD mutations, underscoring the significance of protein dynamics in predicting cellular phenotypes. Further molecular dynamics simulations demonstrated that PTEN-cancer/ASD mutations induce dynamic alterations characterized by open conformational changes restricted to the P loop and coupled with inter-domain allosteric regulation. This research aims to enhance the genotypic and phenotypic understanding of PTEN-cancer/ASD mutations through an interpretable ML model integrated with structural dynamics analysis. By identifying shared mechanisms between cancer and ASD, the findings pave the way for the development of novel therapeutic strategies.
Multiparametric optimization of human primary B-cell cultures using Design of Experiments
Authors: Rovsing Anne Bruun , Green Kenneth , Jensen Lisbeth , Nielsen Ian Helstrup , Mikkelsen Jacob Giehm , Degn Søren E.
Published: January 2025

B cells are essential in the immune system, driving antibody production, cytokine secretion, and antigen presentation. Studies in mouse models have illuminated key mechanisms underlying B-cell activation, differentiation, class-switch recombination, and somatic hypermutation. However, the extent to which these findings translate to human biology remains unclear. To address this, we developed a human primary B-cell culture system using feeder cells engineered to express CD40L, supplemented with the cytokines BAFF, IL-4, and IL-21. Using a Design of Experiments (DOE) approach, we optimized critical parameters and dissected the individual contributions of each specific factor. Our results reveal that BAFF plays a negligible role, and IL-21 has more subtle effects, whereas CD40L and IL-4 are critical determinants of cell viability, proliferation and IgE class-switching. Furthermore, we find that engineered feeder cells can serve equally well as a source of cytokines, but providing these in purified form increases the flexibility of the system. This platform enables detailed investigation of human B-cell biology, offering insights into intrinsic and extrinsic regulators of antibody responses and providing a foundation forin vitroproduction of human primary antibodies.
Proximal relationships of moonlighting Proteins inEscherichia coli: a mathematical genomic perspective
Authors: Nawn Debaleena , Hassan Sk. Sarif , Sil Moumita , Ghosh Ankita , Goswami Arunava , Uversky Vladimir N.
Published: January 2025

Moonlighting proteins inEscherichia coli(E.coli) perform multiple independent functions without altering their primary amino acid sequence, challenging the “one gene-one enzyme” hypothesis. Bacterial proteins serve various functions, including host cell adhesion, extracellular matrix interaction, and immune modulation, while also supporting essential physiological processes within the bacteria. Identifying these proteins in pathogens and tracking their genetic changes is crucial for understanding bacterial survival and virulence. A quantitative understanding of these proteins is pivotal as it enables the identification of specific patterns and relationships between amino acid composition, protein stability, and functional versatility. This study quantitatively analyzes fiftyE. colimoonlighting proteins, focusing on their structural and functional features. Key findings include variability in amino acid composition, with alanine predominating, and a preference for non-polar residues, which may enhance protein stability. Quantitative features analyses identified seven distinct proximal sets, reflecting the proteins’ spatial arrangements of amino acids, structural diversity, and functional roles in processes such as metabolism, stress response, and gene regulation. These results deepen our understanding of the multifunctionality ofE. colimoonlighting proteins, indicating their adaptability and implications for bacterial survival and pathogenicity.
A field-focused systems approach reveals mRNA covalent modifications linked to sorghum growth and development under drought stress
Authors: Yu Li’ang , Melandri Giovanni , Nelson Dittrich Anna C. , Calleja Sebastian , Palos Kyle , Srinivasan Aparna , Brewer Emily K. , Henderson Riley , Garcia Ciara Denise , Zhang Xiaodan , Rozzi Bruno , Eveland Andrea , Schroeder Susan J. , Stern David , Skirycz Aleksandra , Lyons Eric , Arnold A. Elizabeth , Gregory Brian D. , Nelson Andrew D. L. , Pauli Duke
Published: January 2025

Covalent RNA modifications (RCMs) are post-transcriptional changes to the chemical composition of RNA. RCMs influence mRNA stability, regulate transcription and translation efficiency, and play critical roles in the growth and development of eukaryotes. However, their role in plants remains poorly understood, particularly as they relate to performance in the field under stress conditions. In this study, we grew a panel of six diverse sorghum (S. bicolor) accessions in the field during the summer in central Arizona and examined their physiological and molecular responses to drought and heat stress over time. We then explored the molecular features that contributed to plant performance under stress. To do so, we combined genomic, transcriptomic, epitranscriptomic, physiological, and metabolomic data in a systems-level approach. Co-expression network analyses uncovered two modules of interest, one controlled primarily by a single stress-responsive transcription factor, SbCDF3, and the other by an RCM, dihydrouridine. While the CDF3 module largely contained a set of stress response and photosynthesis-associated genes that were positively correlated with plant performance, the dihydrouridine-associated module was largely comprised of photosynthesis and metabolism genes, including SbPPDK1, which is integral to C4 photosynthesis in the grasses. In addition, the transcript encoding the enzyme responsible for this RCM, dihydrouridine synthase (SbDUS2), was also present in this module, and its abundance was positively correlated with photosynthetic traits andSbPPDK1abundance. Given that this highly conserved RCM has never been characterized in plants, we examined loss of function mutants for the DUS2 enzyme in Arabidopsis, demonstrating decreases in plant growth and performance under heat stress in this background. Our work highlights both a key transcription factor, CDF3, for breeding in thePoaceae. In addition, for the xfirst time in plants, we reveal a role for the RCM dihydrouridine in modifying conserved, core metabolic and photosynthesis-associated transcripts in plants.
STExplorer: Navigating the Micro-Geography of Spatial Omics Data
Authors: Zormpas Eleftherios , Vlachogiannis Nikolaos I. , Resteu Anastasia , Unsworth Adrienne , Tual-Chalot Simon , Dorgau Birthe , Queen Rachel , Lako Majlinda , Tiniakos Dina , Comber Alexis , Anstee Quentin M. , Giakountis Antonis , Cockell Simon J.
Published: January 2025

Spatial transcriptomics (ST) has the potential to provide unprecedented insights into gene expression across tissue architecture, but existing analytical methods often overlook the full complexity of the spatial dimension. We present STExplorer, an R package that adapts well-established computational geography (CG) methods to explore the micro-geography of spatial omics data. By incorporating techniques like Geographically Weighted Principal Component Analysis (GWPCA), Fuzzy Geographically Weighted Clustering (FGWC), Geographically Weighted Regression (GWR), and analyses of observation Spatial Autocorrelation (SA), STExplorer enables the uncovering of spatially resolved patterns that capture the spatial heterogeneity of biological data. STExplorer provides a complete suite of functions for spatial analyses and visualisations, supporting deeper biological understanding and inference. Built on the Bioconductor ecosystem, the package integrates with SpatialFeatureExperiment objects, ensuring compatibility with existing pipelines. It includes preprocessing capabilities such as data import, quality control, gene count normalisation, and variable gene selection, alongside tools for downstream analysis and detailed visualisations that quantify and map spatial heterogeneity and relationships. We demonstrate the utility of STExplorer through applications to spatial transcriptomics datasets, revealing that spatially varying gene expression and relationships are often masked by standard analyses. By bridging bioinformatics and CG, STExplorer provides a novel and informed approach to spatial transcriptomics analysis, with robust tools to address spatial heterogeneity and its associated underlying biology, thereby advancing our understanding of complex tissue biology without reinventing the wheel.
Towards a comprehensive anatomical matrix for crown birds: phylogenetic insights from the pectoral girdle and forelimb skeleton
Authors: Chen Albert , Steell Elizabeth M. , Benson Roger B. J. , Field Daniel J.
Published: January 2025

Phylogenetic analyses of phenotypic characters in crown-group birds often recover results that are strongly incongruous with the findings of recent phylogenomic analyses. Furthermore, existing morphological datasets for crown birds are frequently limited by restricted taxon or character sampling, inconsistent character construction, incorrect scoring, or a combination of several of these factors. As part of an effort to address these limitations, in this study we focus on identifying phylogenetically informative characters of the avian pectoral girdle and forelimb skeleton, elements of which are commonly preserved as avian fossils. We assembled and vetted a dataset of 204 characters, which were then scored for a phylogenetically diverse range of 75 extant avian taxa and incorporated into phylogenetic analyses. Analyses run without topological constraints exhibited notable conflicts with the results of recent phylogenomic studies, possibly due to functional convergence and rapid cladogenesis in the early evolutionary history of crown birds. Qualitative anatomical comparisons and quantitative metrics of homoplasy further highlighted the fact that similar morphologies in pectoral girdle and forelimb elements have evolved repeatedly in distantly related groups of birds, representing a major confounding factor in avian morphological phylogenetics. However, the implementation of molecular scaffolds allowed identification of diagnostic character combinations for numerous avian clades previously only recognized through molecular data, such as Phaethontimorphae, Aequornithes, and Telluraves. Although large morphological datasets may not guarantee increased congruence with molecular phylogenetic studies, they can nonetheless be valuable tools for identifying anatomical synapomorphies of key clades, placing fossils into phylogenetic context, and studying macroevolutionary patterns within major groups of organisms.
Tying the Knot: In Silico Design of Foldable Lasso Peptides
Authors: Nguyen John D. M. , da Hora Gabriel C. A. , Mifflin Marcus C. , Roberts Andrew G. , Swanson Jessica M. J.
Published: January 2025

Lasso peptides are a unique class of natural products with distinctively threaded structures, conferring exceptional stability against thermal and proteolytic degradation. Despite their promising biotechnological and pharmaceutical applications, reported attempts to prepare them by chemical synthesis result in forming the nonthreaded branched-cyclic isomer, rather than the desired lassoed structure. This is likely due to the entropic challenge of folding a short, threaded motif prior to chemically mediated cyclization. Accordingly, this study aims to better understand and enhance the relative stability of pre-lasso conformations—the essential precursor to lasso peptide formation—through sequence optimization, chemical modification, and disulfide incorporation. Using Rosetta fixed backbone design, optimal sequences for several class II lasso peptides are identified. Enhanced sampling with well-tempered metadynamics confirmed that designed sequences derived from the lasso structures of rubrivinodin and microcin J25 exhibit a notable improvement in pre-lasso stability relative to the competing nonthreaded conformations. Chemical modifications to the isopeptide bond-forming residues of microcin J25 further increase the probability of pre-lasso formation, highlighting the beneficial role of non-canonical amino acid residues. Counterintuitively, the introduction of a disulfide cross-link decreased pre-lasso stability. Although cross-linking inherently constrains the peptide structure, decreasing the entropic dominance of unfolded phase space, it hinders the requisite wrapping of the N-terminal end around the tail to adopt the pre-lasso conformation. However, combining chemical modifications with the disulfide cross-link results in further pre-lasso stabilization, indicating that the ring modifications counteract the constraints and provide a cooperative benefit with cross-linking. These findings lay the groundwork for further design efforts to enable synthetic access to the lasso peptide scaffold.

SIGNIFICANCE

Lasso peptides are a unique class of ribosomally synthesized and post-translationally modified natural products with diverse biological activities and potential for therapeutic applications. Although direct synthesis would facilitate therapeutic design, it has not yet been possible to fold these short sequences to their threaded architecture without the help of biosynthetic enzyme stabilization. Our work explores strategies to enhance the stability of the pre-lasso structure, the essential precursor tode novolasso peptide formation. We find that sequence design, incorporating non-canonical amino acid residues, and design-guided cross-linking can augment stability to increase the likelihood of lasso motif accessibility. This work presents several strategies for the continued design of foldable lasso peptides.
A logratio approach to the analysis of autosomal genotype frequencies across multiple samples
Authors: Graffelman Jan
Published: January 2025

John Aitchison has shown that the logratio principal component analysis of multiple samples of a biallelic polymorphism can evidentiate the Hardy-Weinberg law. This article extends Aitchison’s work to multiallelic polymorphisms showing how the Hardy-Weinberg law manifests itself in a logratio based statistical analysis of larger genotypic compositions. Some fundamental relationships between allelic and genotypic compositions are derived, and the close relationships between the logratio principal component analysis of allelic and genotypic compositions and the corresponding compositional biplots are established. We perform simulations and practical genetic data analysis to explore the implications of Hardy-Weinberg equilibrium for the logratio principal component analysis of genotypic compositions. A general multiallelic compositional measure for disequilibrium is presented, and shown to relate to the classical inbreeding coefficient. The proposed compositional analysis is illustrated with biallelic glyoxalase genotypes and multiallelic forensic STRs from the 1,000 Genomes project.
Mouse Single-Cell Long-Read Splicing Atlas by Ouro-Seq
Authors: An Hyunsu , Choi Sin Young , Yi Jawoon , Lim Chaemin , Shin So-I , Oh Sera , Lee Rosalind H. , Park Jihwan
Published: January 2025

Alternative splicing creates cellular and phenotypic diversity; thus, characterizing splicing patterns across diverse cell types is essential for a comprehensive understanding of these cell types. However, existing full-length single-cell RNA-sequencing methods suffer from multiple technical limitations, such as the pervasive presence of reverse transcription artifacts across genes. Here, we introduce Ouro-Seq, a novel single-cell long-read sequencing framework with a versatile artifact removal mechanism for characterizing full-length mRNA species expressed by individual cells. We also developed a computational pipeline that identifies genuine full-length cDNAs and normalizes full-length mRNA size distributions for integration. Using Ouro-Seq, we constructed the Mouse Single-Cell Long-Read Splicing Atlas by collecting full-length transcriptomes of 103,304 nuclei or cells from 12 major organs and tissues of adult mice. Our atlas comprehensively characterizes alternative splicing, alternative promoter usage, and alternative polyadenylation events across cell types, revealing previously unappreciated functional heterogeneity among individual cells. Different cell types exhibit largely distinct expression patterns of various isoforms, corresponding to their specific morphologies and biological functions. Our splicing atlas and generalized long-read frameworks will empower researchers to fully interpret biological variation across full-length transcriptomes of single cells.
Immune cell mitochondrial phenotypes are largely preserved in mitochondrial diseases and do not reflect disease severity
Authors: Liu Cynthia C. , Kurade Mangesh , Monzel Anna S. , Kelly Catherine , Juster Robert-Paul , Trumpff Caroline , Hirano Michio , Picard Martin
Published: January 2025

Objective

To profile immune cell mitochondrial phenotypes in mitochondrial diseases (MitoD) and evaluate how those phenotypes relate to disease manifestations or biomarkers.

Methods

We profiled mitochondrial content and oxidative phosphorylation (OxPhos) enzymatic activities in isolated monocytes, lymphocytes, neutrophils, platelets, and mixed peripheral blood mononuclear cells (PBMCs) from 37 individuals with MitoD (m.3243A>G, n=23; single, large-scale mitochondrial DNA (mtDNA) deletions, n=14) and 68 healthy women and men from the Mitochondrial Stress, Brain Imaging, and Epigenetics (MiSBIE) study.

Results

We first confirm and quantify robust cell type differences in mitochondrial content, activities of OxPhos complexes I, II, and IV, and the mitochondrial respiratory capacity (MRC) index. In relation to MitoD, neither mitochondrial content nor OxPhos capacity were consistently affected, other than a mild monocyte-specific reduction in complex I (partially mtDNA encoded) relative to complex II (entirely nDNA encoded), consistent with the mtDNA defects examined. Relative to the large differences in cell type-specific mitochondrial phenotypes, differences in MitoD relative to controls were generally small (<25%) across mitochondrial measures. The MitoD biomarkers GDF15 and FGF21, as well as clinical disease severity measures, were most strongly related to mitochondrial abnormalities in platelets, and most weakly related to mitochondrial OxPhos capacity in lymphocytes, which are known to eliminate mtDNA defects. Finally, comparing PBMCs collected in the morning/fasted state to the afternoon/fed state following a stressful experience, we report significant time-dependent changes in mitochondrial biology over the time scale of hours.

Conclusions

Overall, these results demonstrate that the dynamic and cell-type specific mitochondrial phenotypes are preserved in mitochondrial diseases and are generally unrelated to the severity of MitoD symptoms.
Impacts of species introductions on the trait diversity of interacting avian frugivores and fleshy-fruited plants depend on native trait diversity
Authors: Nowak Larissa , Fricke Evan C. , Traveset Anna , Donoso Isabel
Published: January 2025

Introductions of non-native species to native ecological communities by humans are major drivers of global biodiversity change. At the same time, biotic interactions, such as those between avian frugivores and fleshy-fruited plants, build the backbone of ecosystems. Hence, studying how species introductions influence interacting species of both trophic levels is essential to understand possible functional consequences of global change.

Here, we take a trait-based approach, focusing on species traits that influence their biotic interactions and related ecosystem functioning, and explore how species introductions affect the diversity of such functional traits within and across assemblages of interacting fleshy-fruited plants and frugivorous birds at several locations across the globe.

Specifically, we calculate differences in trait diversity and mean trait values, and compare beta trait diversity with and without introduced species, for 25 frugivorous bird and 62 fleshy-fruited plant assemblages.

Introduced species tended to increase bird and plant trait diversity in assemblages with low native trait diversity but decreased it in assemblages with higher native trait diversity. In bird assemblages, species introductions shifted mean values towards larger birds with wider bills and more pointed wings. In plant assemblages, mean trait values showed variable changes: fruit length increased and plant height decreased.

Comparisons between assemblages revealed that introduced species reduced the beta trait diversity of both frugivorous birds and fleshy-fruited plants, suggesting biotic homogenisation in terms of their functional traits.

Changes in trait diversity underscore that species introductions can have functional consequences for biotic interactions and related ecosystem functions, potentially affecting the availability of interaction partners with matching traits and the provisioning of seed dispersal.
A universal spectrum annotator for complex peptidoforms in mass spectrometry-based proteomics
Authors: Schulte Douwe , Leuvenink Rien , Jager Shelley , Heck Albert J. R. , Snijder Joost
Published: January 2025

Accurate and comprehensive peptide spectrum annotation is a crucial step to interpret mass spectrometry-based proteomics data. While peak assignment in peptide fragmentation spectra is central to a broad range of proteomics applications, current tools tend to be specialized to a specific task. Here we present a more comprehensive tool, the Annotator, which unifies spectrum annotation for bottom-up, middle-down, top-down, cross-linked, and glycopeptide fragmentation mass spectra, from all fragmentation methods, including all ion types: a/b/c, x/y/z, d/v/w, and immonium ions. The Annotator integrates all known post-translational modifications from common databases and additionally allows for the definition of custom modifications and diagnostic fragment ions. The underlying library used for the theoretical fragmentation and matching is based on the unified peptidoform notation ProForma 2.0 and made available as a Rust library (rustyms) with Python bindings. This enables spectrum annotation of diverse and complex peptidoforms across the broad range of mass spectrometry-based proteomics applications.
Decoding cellular transcriptional regulatory networks governing wheat inflorescence development
Authors: Liu Xuemei , Lin Xuelei , Kang Jingmin , Long Katie A. , Yue Jingjing , Chen Chuan , Wang Dongzhi , Lister Ashleigh , Macaulay Iain C. , Liu Xin , Uauy Cristobal , Xiao Jun
Published: January 2025

Wheat inflorescence architecture, particularly spikelet and floret development, is critical for grain yield. To decode the cellular transcriptional regulatory network (cTRN) underlying wheat inflorescence development, we integrated multiple single-cell omics technologies to construct a spatiotemporal atlas of transcriptional and chromatin accessibility dynamics. This comprehensive analysis identified 20 cell types, 7,211 cell type-specific genes and 152,333 cell type-specific accessible chromatin regions (csACRs) in the wheat inflorescence. Trajectory analysis identified two sub-clusters of proliferating cells as the origins of spikelet and floret formation, deviating from the traditional developmental model. Key transcription factors and hormone-related genes in the cTRN, along with the csACRs, providing new targets for modulating wheat inflorescence architecture. Our findings provide a high-resolution resource for crop inflorescence research and establish a paradigm for applying spatiotemporal single-cell omics analysis to plant biology.
Evaluation of nutritional factors, cytokines, liver parameters and survival of patients with liver cirrhosis and hepatocellular carcinoma: a cross-sectional study
Authors: Faria Iara Carvalho , Monici Leonardo Trevisan , Pavan Célia Regina , Almeida Jazon Romilson de Souza , Faria Sérgio Henrique Dias Marques , Sevá-Pereira Tiago
Published: January 2025

Hepatocellular carcinoma (HCC) is the leading cause of mortality among cirrhotic patients, often linked to advanced liver disease. This cross-sectional study evaluated the nutritional factors, cytokine profiles, liver function parameters, and survival of patients with liver cirrhosis (LC) and HCC. Forty-seven patients were grouped as LC (n=21) or LC with HCC (n=26). Nutritional status was assessed through anthropometry, bioelectrical impedance analysis, and dietary recall, while cytokine levels (IL-6, IL-10, TNF-α) and biochemical markers (AST, ALT, albumin, prealbumin) were analyzed. Survival data were evaluated using Kaplan-Meier curves and Cox regression. HCC patients exhibited higher IL-6 levels, correlating with advanced disease stages (p=0.035). IL-10 levels were elevated in early-stage HCC (BCLC A) compared to BCLC B (p=0.006). AST and ALT levels were significantly higher in HCC patients, reflecting greater hepatocyte damage. Survival analysis revealed a median of 756 days, with shorter survival in HCC patients (p=0.0172). Nutritional parameters did not significantly correlate with survival outcomes, though most patients were eutrophic or overweight. This study highlights the roles of IL-6 and IL-10 as potential biomarkers in HCC progression and provides critical insights into the biochemical and nutritional profiles associated with LC and HCC. These findings may inform future therapeutic interventions.
Towards whole-genome inference of polygenic scores with fast and memory-efficient algorithms
Authors: Zabad Shadi , Haryan Chirayu Anant , Gravel Simon , Misra Sanchit , Li Yue
Published: January 2025

With improved Whole Genome Sequencing (WGS) and variant imputation techniques, modern Genome-wide Association Studies (GWASs) have enriched our understanding of the landscape of genetic associations for thousands of disease phenotypes. However, translating the marginal associations for millions of genetic variants to integrated polygenic risk scores (PRS) that capture their joint effects on the phenotype remains a major challenge. Due to technical and statistical constraints, commonly-used PRS methods in this setting either perform heuristic Pruning-and-Thresholding or overlook most genetic association signals by restricting inference to small variant sets, such as HapMap3. Here, we present a set of algorithmic improvements and compact data structures that enable scaling summary statistics-based PRS inference to tens of millions of variants while avoiding numerical instabilities common in such high-dimensional settings. These enhancements consist of highly compressed Linkage-Disequilibrium (LD) matrix format, which integrates with streamlined and parallel coordinate ascent updating schemes. When incorporated into our existing PRS method (VIPRS), the new algorithms yield over 50 fold reductions in storage requirements and lead to orders of magnitude improvements in runtime and memory efficiency. The updated VIPRS software can now perform Variational Bayesian regression over 1.1 million HapMap3 variants in under a minute. Using this new scalable implementation, we applied VIPRS to 75 of the most heritable, continuous phenotypes in the UK Biobank, leveraging marginal associations for up to 18 million bi-allelic variants. Performing inference over this rich association data requires less than 20 minutes of wallclock time and 15GB of memory per phenotype. It also delivers consistent gains in cross-population transferability, with an average improvement of 10-15% in incremental R-squared.
Diagnostic Accuracy of a Smartphone-Enabled Urinary Albumin-to-Creatinine Ratio Test for Detecting Chronic Kidney Disease Among At-Risk Populations
Authors: Jeddah Danielle , Bevins Nicholas B , Ronen Matan , Tangri Navdeep
Published: January 2025

Objective

To evaluate the diagnostic accuracy of the FDA-cleared Minuteful Kidney Test (MKT), a home-based semi-quantitative urine albumin-to-creatinine ratio (uACR) test, compared to the Beckman Coulter AU 480 analyzer, a standard laboratory quantitative method, for detecting albuminuria in individuals with or at risk for chronic kidney disease (CKD).

Methods

Urine samples were obtained from individuals with risk factors for kidney damage. Each sample was analyzed for uACR using both the MKT and the laboratory standard method. Albuminuria was classified according to KDIGO guidelines: A1 (uACR ≤30 mg/g, “Normal to mildly increased”), A2 (uACR 30-300 mg/g, “Moderately increased”), and A3 (uACR ≥300 mg/g, “Severely increased”). Sensitivity, specificity, PPV, and NPV of MKT were calculated against the laboratory standard.

Results

Out of 615 collected urine samples, 555 met inclusion criteria. Albuminuria (uACR ≥30 mg/g) was detected in 24.9% of samples using the laboratory method (95% CI, 21.3–28.5%). The MKT demonstrated a sensitivity of 96.4%, specificity of 84.2%, NPV of 98.6%, and PPV of 66.8%. The test accurately categorized 85.6% of samples into the KDIGO albuminuria categories A1, A2, and A3, accurately identifying 100% of laboratory-confirmed A3 samples as abnormal.

Conclusions

The Minuteful Kidney Test shows high sensitivity, exceeding the guideline-required threshold (>85%, P<0.001), and robust specificity for detecting albuminuria in high-risk populations. This device offers potential to improve CKD screening and management and facilitate early intervention in primary care and community settings, where accurate rule-out capabilities are essential.
Evidence Suggesting Prolonged Neuroinflammation in a Subset of Children after Moderate/Severe TBI: A UCLA RAPBI Study
Authors: McCabe Courtney , Dennis Emily L , Lindsey Hannah M , Babikian Talin , Bickart Kevin , Giza Christopher C , Asarnow Robert F
Published: January 2025

Traumatic brain injury (TBI) presents a public health concern as a leading cause of death and disability in children. Pediatric populations are particularly vulnerable to adverse outcomes following TBI due to periods of rapid growth, synaptic pruning, and myelination. Pediatric patients with moderate-severe TBI (msTBI) and healthy controls were evaluated from the post-acute (2-5 months) to chronic phase (13-19 months) of recovery using diffusion magnetic resonance imaging (dMRI) and interhemispheric transfer time (IHTT), which is an event-related potential measure the speed of information transfer across the corpus callosum. We previously identified two subgroups of patients based on IHTT, with one group showing a significantly slower IHTT (TBI-slow), poorer cognitive performance, and progressive structural damage. In contrast, the other group (TBI-normal) did not differ from controls on IHTT or cognitive performance and showed relative structural recovery over time. Here, we examined group differences in restricted diffusion imaging (RDI), which is a dMRI metric sensitive to inflammation. Comparing TBI-slow, TBI-normal, and controls on RDI cross-sectionally, dMRI connectometry analysis revealed higher RDI across the white matter in the TBI-slow group compared to both the control and TBI-normal groups.

Longitudinal analyses indicated that while both TBI groups exhibited a decrease in RDI over time, suggesting resolution of neuroinflammation and recovery, the decreases in the TBI-slow group were smaller. The differences in RDI between TBI-slow and TBI-normal suggest that inflammation may play a key role in the prolonged recovery, including brain structure, cognitive performance, and symptom reports, of pediatric patients with msTBI.
Clinical and bacterial determinants of unfavorable tuberculosis treatment outcomes: an observational study in Georgia
Authors: Goig Galo A. , Loiseau Chloé , Maghradze Nino , Mchedlishvili Kakha , Avaliani Teona , Tsutsunava Ana , Brites Daniela , Kalkan Sevda , Borrell Sonia , Aspindzelashvili Rusudan , Avaliani Zaza , Kipiani Maia , Tukvadze Nestani , Jugheli Levan , Gagneux Sebastien
Published: January 2025

Tuberculosis (TB) remains a major public health concern. Improving TB control programmes and treatment success rates requires a deeper understanding of the factors that determine disease presentation and patient treatment outcomes. While the demographic and clinical factors influencing treatment outcomes are well documented, the role of bacterial genetics remains limited. In this study, we analyzed theMycobacterium tuberculosiscomplex (MTBC) genomes and the associated clinical data from 4,536 TB patients in the country of Georgia covering a period of 13 years. Multivariable modelling confirmed the role of known demographic and clinical factors such as sex, age, body mass index (BMI) and comorbidities in determining treatment outcomes, as well as the efficacy of novel TB treatments containing bedaquiline. In addition, we found that some bacterial variables, including the MTBC lineage, the specific mutations conferring resistance to rifampicin and fluoroquinolones, as well as a high bacterial burden were associated with unfavorable outcomes. GWAS analyses revealed no genetic mutations in the bacteria other than known drug resistance-conferring mutations to be associated with treatment outcomes. However, we found that mutations in the bacterial genesufDwere linked to cavitary disease. Additionally, we observed that mutations insufD,mutations conferring resistance to rifampicin and fitness compensatory mutations were associated with the bacterial burden within patients. We conclude that both patient and bacterial factors determine disease presentation and clinical outcomes in TB.