bluuebunny/crossref_metadata_2025 huggingface dataset:
Homologous recombination deficiency in ovarian high-grade serous carcinoma by self-reported race
Authors: Lawson-Michod Katherine A. , Johnson Courtney E. , Barnard Mollie E. , Davidson Natalie , Collin Lindsay J. , Nix David A. , Huff Chad , Berchuck Andy , Salas Lucas A. , Greene Casey , Marks Jeffrey R. , Peres Lauren C. , Doherty Jennifer A. , Schildkraut Joellen M.
Published: January 2025

Background

Approximately half of ovarian high-grade serous carcinomas (HGSC) have homologous recombination deficiency (HRD). However, HRD is not well-characterized in Black individuals.

Objective

To characterize HGSC HRD by self-reported race and evaluate whether differences in HRD are associated with ovarian cancer mortality.

Study population

Cohort study using data collected from two population-based case-control studies of ovarian cancer. Cases were selected based on self-reported race (178 Black, 123 White) and pathologically-confirmed HGSC.

Exposures

HRD features identified using matched tumor-normal whole-exome DNA sequencing and categorized as germline or somatic variants in homologous recombination pathway genes, or the SBS3 HRD-associated signature.

Outcomes

Median difference and 95% confidence intervals (CI) for age at diagnosis and tumor mutation burden, and age and stage-adjusted hazard ratios (HR) and 95%CIs for survival, comparing individuals with an HRD feature to those without, separately by self-reported race.

Results

More of the germline and somatic variants detected among Black individuals compared with White individuals were unannotated or variants of uncertain significance (VUS; germline 65% versus 45%; somatic 62% versus 50%, respectively). While the prevalences of many HRD features were similar between Black individuals and White individuals, Black individuals had a higher prevalence of the HRD signature identified using de novo mutational signature analysis (40% versus 29%) and germlineBRCA2variants (8% versus 2%) compared with White individuals. We observed that among Black individuals,BRCA2variants were associated with better survival (somatic HR=0.23, 95%CI 0.07–0.76; germline HR=0.48, 95%CI 0.22–1.03), while germlineBRCA1variants were associated with worse survival (HR=2.11, 95%CI 1.14–3.88). When we restricted to VUS and unannotated variants, we observed similar associations with survival forBRCA2 among Black individuals (somatic HR=0.18, 95%CI 0.04-0.75; germline HR=0.40, 95%CI 0.15–1.09).

Conclusions and Relevance

HRD testing informs precision-based medicine approaches that improve outcomes, but a higher proportion of VUS among Black individuals may complicate referral for such care. Our findings emphasize the importance of recruiting diverse individuals in genomics research and better characterizing VUS.
Impact of Serum Sample Storage on the Stability of TRAIL, IP-10, and CRP: Implications for Biomarker Research Employing Biobanks
Authors: Kalfon Roy , Raz Ayelet , Halabi Salim , Navon Roy , Gottlieb Tanya M. , Eden Eran , Hainrichson Mary
Published: January 2025

1.

Serum biobanks are a valuable resource for proteomic screening, clinical validation and tool comparison studies. Protein integrity can be impacted by sample handling from blood draw until serum separation, by serum processing and freezing, and by storage time in the freezer. Since proteins are destabilized with different dynamics, it is critical to consider each biomarker’s behavior under the conditions relevant to a given biobank, before employing the biobank to study a biomarker panel. MeMed BV®is a next generation host-based diagnostic test for discriminating between bacterial and viral infection that computationally integrates the circulating levels of three biomarkers: TNF-related apoptosis-inducing ligand (TRAIL), interferon γ-induced protein 10 (IP-10), and C-reactive protein (CRP). Here we report the impact of serum sample storage at −80°C on the stability of these three biomarkers. Notably, TRAIL levels decrease by approximately 30% after five years of storage at −80°C, while IP-10 levels decrease by only 17% and CRP levels do not decrease significantly. We conclude that long-term freezer storage differentially compromises the integrity of MeMed BV’s constituent biomarkers.
Restoring Cholesterol Efflux in Vascular Smooth Muscle Cells Transitioning into Foam Cells Through Liver X Receptor Activation
Authors: Borràs Carla , Rotllan Noemí , Griñán Raquel , Santos David , Mourín Marta , Soto Begoña , Camacho Mercedes , Tondo Mireia , Canyelles Marina , Blanco-Vaca Francisco , Escolà-Gil Joan Carles
Published: January 2025

Objective

Macrophage foam cells derived from vascular smooth muscle cells (VSMCs) account for 30–70% of foam cells in atherosclerotic lesions. Liver X receptor (LXR) agonists promote high-density lipoprotein (HDL)-mediated cholesterol efflux from macrophages. This study aimed to investigate the effects of LXR activation on the reverse cholesterol transport (RCT) rate from VSMCs to fecesin vivo.

Approach and Results

Cholesterol efflux induced by serum and HDL was evaluated in human and mouse VSMCs treated with the LXR agonist T090137 before and after methyl-β-cyclodextrin (MBD)-cholesterol loading. Additional experiments included treatment with an acyl-coenzyme A: cholesterol acyltransferase (ACAT) inhibitor. Cholesterol-radiolabeled VSMCs were injected into the peritoneal cavity of mice, and RCT was assessed by measuring radiolabeled cholesterol in serum, liver, and feces over 48 hours. Serum and HDL induced cholesterol efflux at similar levels in both human and mouse VSMCs. Cholesterol efflux was significantly reduced following MBD-cholesterol loading; however, treatment with the LXR agonist significantly enhanced efflux. Radiolabeled foam-like VSMCs injected into mice exhibited impaired cholesterol transfer to serum, HDL, and feces compared to non-lipid-laden VSMCs. Pre-treatment with the LXR agonist increased radiolabeled cholesterol levels in serum and HDL and doubled its fecal excretion. Additionally, LXR activation restored RCT from MBD-cholesterol-loaded VSMCs to feces, reaching levels comparable to those of non-lipid-laden cells. Treatment with an ACAT inhibitor fully restored RCT rates in foam-like VSMCs, and the combination of the ACAT inhibitor and the LXR agonist further enhanced RCT.

Conclusions

HDL-mediated cholesterol efflux is significantly impaired in VSMCs during their transition into foam cells. Pharmacological activation of LXR enhances RCT from VSMCs to fecesin vivoand restores the impaired RCT from transitioning VSMCs. The combination of LXR agonists and ACAT inhibitors holds promise as a synergistic therapeutic approach to restoring cholesterol homeostasis in lipid-laden VSMCs, offering potential strategies to mitigate atherosclerosis.

Highlights

LXR activation enhances cholesterol efflux in VSMCsin vitro, even after their transition into foam cells.

VSMCs transitioning into foam cells exhibit reduced cholesterol transfer to HDL and feces in mice.

LXR agonist treatment enhances reverse cholesterol transport (RCT) from VSMCs to fecesin vivo.

Selective ACAT inhibition restores RCT in foam-like VSMCs, with further enhancement observed upon LXR activation.
Addressing SARS-CoV-2 Evolution: Neutralization of Emerging Variants of Concern by the AVX/COVID-12 ‘Patria’ Vaccine Based on HexaPro-S Ancestral Wuhan Spike or Its Updated BA.2.75.2 Version
Authors: Carballo-Uicab Gregorio , Mellado-Sánchez Gabriela , González-González Edith , Salinas-Trujano Juana , Mendoza-Salazar Ivette , López-Olvera Karina , Gómez-Castellano Keyla M. , Salazar Ma. Isabel , Torres-Flores Jesús M. , Chagoya-Cortés Héctor Elías , Paz-De la Rosa Georgina , Mena Ignacio , Rojas-Martínez Oscar , Lara Puente Jesús Horacio , Peralta-Sánchez Gustavo Javier , Sarfati-Mizrahi David , Torres-Flores Alejandro , Sun Weina , Krammer Florian , García-Sastre Adolfo , Palese Peter , López-Macías Constantino , Lozano-Dubernard Bernardo , Pérez-Tapia Sonia M. , Almagro Juan C.
Published: January 2025

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a global health challenge, causing severe morbidity and mortality, particularly in vulnerable groups such as the elderly, immunocompromised individuals, and those with comorbidities. In low- and middle-income countries (LMICs), vaccine access is hindered by high costs and inequitable distribution. To tackle these issues, Mexico developed the AVX/COVID-12 (V-Wu) vaccine, a recombinant Newcastle disease virus (NDV)-based platform expressing a stabilized ancestral Wuhan spike protein (HexaPro-S). Locally manufactured after rigorous testing and regulatory approval, V-Wu aims to enhance self-sufficiency and equity in immunization. This study evaluates an updated vaccine version, AVX/COVID-12 (V-BA), designed to combat Omicron subvariants by expressing the HexaPro-S protein of BA.2.75.2. Both vaccines were administered intramuscularly in K18-hACE2 transgenic and BALB/c mouse models using a prime-boost regimen. Immunogenicity was analyzed by measuring antibodies against Omicron S proteins BA.2.75.2 and XBB.1.5, as well as neutralizing antibodies against Wuhan, BA.1, XBB.1.16, and JN.1 variants. Both vaccines were safe, eliciting robust antibody responses against Omicron S proteins and neutralizing antibodies against multiple emerging SARS-CoV-2 variants of concern (VOCs). V-BA demonstrated superior protection against current Omicron variants, while V-Wu offered broader coverage, including the ancestral Wuhan strain and emerging variants like JN.1. These findings underscore the adaptability of NDV-based platforms in addressing the evolving SARS-CoV-2 landscape and reaffirm the ongoing utility of the ancestral Patria vaccine. Together, they demonstrate the potential of these platforms to drive the development of next-generation vaccines tailored to emerging viral threats, contributing to global health equity.
Identification of a novel papillary renal cell carcinoma molecular subtype characterized by HIF-pathway over-activation
Authors: de Nicolás-Hernández Javier , Arenas Alicia , Valdivia Carlos , Santos María , Lanillos Javier , Bechmann Nicole , Peitzsch Mirko , Gil-Vilariño Eduardo , Monteagudo María , Mellid Sara , Montero-Conde Cristina , Cascón Alberto , Leandro-García Luis Javier , de Velasco Guillermo , Durán Ignacio , Puente Javier , García-Donas Jesús , Caleiras Eduardo , Robledo Mercedes , Rodríguez-Antona Cristina
Published: January 2025

Purpose

Papillary renal cell carcinoma (pRCC), the second most common subtype of renal cancer, exhibits heterogeneity in molecular features and response to targeted therapies, including antiangiogenic drugs. Discovering molecular biomarkers able to stratify pRCC patients into clinically relevant subgroups and understanding the underlying mechanisms are urgently needed to advance precision medicine. Here, we molecularly dissect a large pRCC series through the expression of the targets of hypoxia inducible factors (HIF), master regulators of angiogenesis, metabolic reprogramming and immune microenvironment.

Experimental Design

We merged and analyzed multi-omic and clinical data of 346 patients derived from two pRCC series (TCGA-KIRP and a Spanish metastatic series). Altered pathways and differences in tumor microenvironment were identified through tumor transcriptomic analyses. Tumor metabolome analysis was performed in selected cases.

Results

Molecular revision of driver mutations classified 302 patients as pRCC, while uncovering misclassified cases. Analysis of HIF targets gene expression identified a subset of pRCC tumors with increased HIF activity (31%; “HIF-active”). These tumors were characterized by high hypoxia scores, increased angiogenesis, low expression of Krebs cycle genes and mitochondrial activity, high immune infiltration and increased epithelial-mesenchymal transition (P<0.0001; each feature) and they were associated with increased metastasis risk and worse overall survival (P<0.005). Metabolome analyses revealed that HIF-active tumors accumulated L-2-hydroxyglutarate (L-2-HG), an oncometabolite that leads to pseudohypoxia by inhibiting HIF prolyl hydroxylases and preventing HIFα degradation. L-2-HG-accumulation agreed with diminishedL2HGDHexpression, associated with losing one copy of the gene and low expression ofPPARGC1A, which regulates its transcription.

Conclusions

HIF-pathway overactivation defines a pseudohypoxic pRCC molecular subgroup characterized by high angiogenesis, immune infiltration and aggressive features. These findings advance our understanding of pRCC diversity, revealing potential clues for the variable response of patients to targeted therapies and paving the way to more personalized pRCC treatments.
CellPhenoX: An eXplainable Cell-specific machine learning method to predict clinical Phenotypes using single-cell multi-omics
Authors: Young Jade , Inamo Jun , Caterer Zachary , Krishna Revanth , Zhang Fan
Published: January 2025

Single-cell technologies have enhanced our knowledge of molecular and cellular heterogeneity underlying disease. As the scale of single-cell datasets expands, linking cell-level phenotypic alterations with clinical outcomes becomes increasingly challenging. To address this, we introduce CellPhenoX, an eXplainable machine learning method to identify cell-specific phenotypes that influence clinical outcomes. CellPhenoX integrates classification models, explainable AI techniques, and a statistical framework to generate interpretable, cell-specific scores that uncover cell populations associated with relevant clinical phenotypes and interaction effects. We demonstrated the performance of CellPhenoX across diverse single-cell designs, including simulations, binary disease-control comparisons, and multi-class studies. Notably, CellPhenoX identified an activated monocyte phenotype in COVID-19, with expansion correlated with disease severity after adjusting for covariates and interactive effects. It also uncovered an inflammation-associated gradient in fibroblasts from ulcerative colitis. We anticipate that CellPhenoX holds the potential to detect clinically relevant phenotypic changes in single-cell data with multiple sources of variation, paving the way for translating single-cell findings into clinical impact.
Affinity-guided labeling reveals P2X7 nanoscale membrane redistribution during microglial activation
Authors: Arnould Benoit , Martz Adeline , Belzanne Pauline , Peralta Francisco Andrés , Cevoli Federico , Hovhannisyan Volodya , Goumon Yannick , Hosy Eric , Specht Alexandre , Grutter Thomas
Published: January 2025

ATP-gated purinergic P2X7 receptors are crucial ion channels involved in inflammation. They sense abnormal ATP release during stress or injury and are considered promising clinical targets for therapeutic intervention. However, despite their predominant expression in immune cells such as microglia, there is limited information on P2X7 membrane expression and regulation during inflammation at the single-molecule level, necessitating new labeling approaches to visualize P2X7 in native cells. Here, we presentX7-uP, an unbiased, affinity-guided P2X7 chemical labeling reagent that selectively biotinylates endogenous P2X7 in BV2 cells, a murine microglia model, allowing subsequent labeling with streptavidin-Alexa 647 tailored for super-resolution imaging. We uncovered a nanoscale microglial P2X7 redistribution mechanism where evenly spaced individual receptors in quiescent cells undergo upregulation and clustering in response to the pro-inflammatory agent lipopolysaccharide and ATP, leading to synergistic interleukin-1β release. Our method thus offers a new approach to revealing endogenous P2X7 expression at the single-molecule level.
Mutations adjacent to the nucleotide-binding cleft ofArabidopsis thalianaACTIN7 confer resistance to the actin-disrupting compound latrunculin B
Authors: Sparks J. Alan , Sun Liang , Chin Sabrina , Ramanjulu Nolan , Wen Jiangqi , Gilroy Simon , Blancaflor Elison B. , Khan Bibi Rafeiza
Published: January 2025

A forward genetic screen identified a dominant-negativeArabidopsis thalianamutant resistant to growth inhibition caused by the actin-disrupting compound latrunculin B (LatB). Map-based cloning combined with whole-genome sequencing revealed that the mutant referred to here aslbr1forLatB resistant1had a point mutation in theAT5G09810gene, which encodes the vegetative actin (ACT) isoform ACT7. The cytosine to thymine mutation in the second exon ofACT7oflbr1led to substitution of proline to serine at position 34 (P34S) adjacent to the nucleotide-binding cleft of the ACT7 protein. Confirmation thatACT7is the causal gene for thelbr1phenotype was achieved through transgenic complementation withACT7 wild type(ACT7WT) andACT7 P34S(ACT7P34S) constructs.ACT7P34also rescued the seedling developmental defects and conferred partial resistance to LatB in the recessiveact7-5mutant. Furthermore, expressing a P34S mutation in ACT2 (ACT2P34S), another vegetative ACT isoform, conferred partial LatB resistance to wild type. Finally, site-directed mutagenesis of ACT7 amino acid residues forming putative hydrogen bonds with LatB, based on yeast and mammalian actin docking and structural analyses, reveals domains adjacent to the actin nucleotide-binding cleft crucial for LatB’s effects on the plant actin cytoskeleton.

Highlight

Characterization of the dominant-negativelbr1mutant uncovers amino acid residues in the actin protein crucial for latrunculin’s mechanism of action in plants.
The dynamics of SNARE complex assembly and disassembly in response to Ca2+current activation in live chromaffin cells
Authors: Fang Qinghua , Zhao Ying , An Dong , Lindau Manfred
Published: January 2025

A SNAP25 based FRET construct named SCORE (SNARE COmplex REporter) has revealed a transient FRET increase that specifically occurred at fusion sites preceding fusion events by tens of milliseconds and presumably reflects vesicle priming. The FRET increase lasts for a few seconds until it is reversed. In those experiments, the FRET increase was found to be localized to areas <0.5 µm2at sites of transmitter release as detected amperometrically using electrochemical detector arrays. Due to the localization to such small areas, it was unknown if the reversal of the FRET increase is due to local dispersion of high-FRET SCORE copies leaving the site after fusion and exchange with surrounding low-FRET copies, or if it reflects disassembly of the high-FRET complexes. To resolve this question, we performed whole-cell patch clamp pulse stimulation experiments, imaging the entire footprint of the cells in Total Internal Reflection Fluorescence (TIRF) excitation mode such that diffusional exchange between high-FRET and low-FRET copies does not produce a net FRET change. We show here that pulse stimulation of calcium currents results in FRET ratio transients with a time course very similar that related to fusion events. By comparing the kinetics of the FRET ratio decay with analytical and numerical diffusion simulation results, we show that the experimentally observed kinetics cannot be explained by diffusional exchange and conclude that the SCORE FRET ratio transients reflect incorporation of SCORE in SNARE complexes followed by SNARE complex disassembly. Experiments using Synaptobrevin 2/Cellubrevin double knock-out mouse embryonal chromaffin cells showed no pulse induced FRET change, indicating that the vSNARE is required for the incorporation of SCORE (or SNAP25 in wild type cells) in the SNARE complex during priming.

Statement of Significance

In chromaffin cells, SNAP25-based FRET constructs (SCORE) revealed transient FRET increases within <0.5 µm2areas, preceding individual fusion events that reversed within seconds. It remained unknown whether this reversal stems from high-FRET complex disassembly or diffusion-mediated exchange with low-FRET complexes. Here, we performed whole-cell patch-clamp pulse stimulation with TIRF microscopy, imaging large ∼30 µm2areas of the cell footprint. Calcium currents induced FRET transients with the same decay time constant of ∼1.5 s, significantly shorter than the time scale of diffusion. The SCORE FRET ratio thus reports in real time the dynamics of SNRE complex assembly and disassembly in live cells. Using Synaptobrevin 2/Cellubrevin double knock-out mouse chromaffin cells we show that vSNAREs are required for SNAP25 incorporation into SNARE complexes during priming.
Refining the cis-regulatory grammar learned by sequence-to-activity models by increasing model resolution
Authors: Chandra Nuria Alina , Hu Yan , Buenrostro Jason D. , Mostafavi Sara , Sasse Alexander
Published: January 2025

Chromatin accessibility can be measured genome-wide with ATAC-seq, enabling the discovery of regulatory regions that control gene expression and determine cell type. Deep genomic sequence-to-function (S2F) models link underlying genomic sequences to the measured chromatin state and identify motifs that regulate chromatin accessibility. Previously, we developed AI-TAC, a S2F model that predicts chromatin accessibility across 81 immune cell types and identifies sequence patterns that control their differential ATAC-seq signals. While AI-TAC provided valuable insights into the regulatory patterns that govern immune cell differentiation, later research established that ATAC-seq profiles (the distribution of Tn5 cuts) contain additional information about the exact location and strength of TF binding. To make use of this additional information, we developed bpAI-TAC, a multi-task neural network which models ATAC-seq at base-pair resolution across 90 immune cell types. We show that adding ATAC-profile information consistently improves predictions of differential chromatin accessibility. We also demonstrate that simultaneous learning of related cell types through multi-task modeling leads to better predictions than single task models. We then present a systematic framework for comparing how differences in model performance can be attributed to differences in what the model has learned. To understand what additional information bpAI-TAC gleans from ATAC-profiles, we use sequence attributions and identify motifs that have different effect sizes when trained on profiles. We conclude that modeling ATAC-seq at base-pair resolution enables the model to learn a more sensitive representation of the regulatory syntax that drives differences between immunocytes, and therefore will improve predictions of variant effects.
Star Power: Early life stages of an endangered sea star are robust to current and near-future warming
Authors: Hodin Jason , Anteau Fleur P. , Ashcraft Brook F. , Brito Michael , Curliss Fiona , Kalytiak-Davis Augustin R. , Peng James S. , Schwab Chloe J , Valdez Vannessa V. , Weertman Willem
Published: January 2025

The sunflower star,Pycnopodia helianthoides, was a top benthic predator throughout its former range from Alaska to northern Mexico, until its populations were devastated starting in 2013 by a disease known as seastar wasting. The subsequent absence of sunflower stars from northern California waters was coincident with a dramatic ecological phase shift from healthy bull kelp forests (Nereocystis luetkeana) to barrens formed by purple sea urchins (Strongylocentrotus purpuratus), a prey of sunflower stars. Modeling suggests that restoration and resilience of kelp forests can be enhanced by the return of sunflower stars. Towards this end we run a conservation breeding program for sunflower stars in the Salish Sea of Washington, where sunflower stars have persisted in much reduced numbers. We here report on a variety of investigations into the temperature tolerance of sunflower stars, focusing on their poorly studied early life stages from their planktonic embryos and larvae, through metamorphosis and settlement as they transition to the benthos, and then for eight months of juvenile growth. Our results indicate that the optimum temperature for early life stage sunflower stars is more than 4°C higher than ambient temperatures in the Salish Sea, and that the juveniles demonstrate enhanced performance to a simulated marine heat wave. These results suggest that Salish Sea-derived sunflower stars would be robust to current and even near-future predicted temperatures in the south of their former range.
Building Foundation Models to Characterize Cellular Interactions via Geometric Self-Supervised Learning on Spatial Genomics
Authors: You Yuning , Wang Zitong Jerry , Fleisher Kevin , Liu Rex , Thomson Matt
Published: January 2025

Cellular interactions form the fundamental/core circuits that drive development, physiology, and disease within tissues. Advances in spatial genomics (SG) and artificial intelligence (AI) offer unprecedented opportunities to computationally analyze and predict the behavior of cell intricate networks, and to identify interactions that drive disease states. However, challenges arise in bothmethodologyandscalability:(i)how to computationally characterize complicated cellular interactions of multi-scale nature where chemical genes/circuits in individual cells process information and drive interactions among large numbers of diverse cell types, and(ii)how to scale up the pipeline to accommodate the increasing volumes of SG data that map transcriptome-scale gene expression and spatial proximity across millions of cells. In this paper, we introduce theCellular Interaction Foundation Model(CI-FM), an AI foundation model functioning to analyze and simulate cellular interactions within living tissues. In the CI-FM pipeline, we explicitly capture and embed cellular interactions within microenvironments by leveraging the powerful and scalable geometric graph neural network model, and optimize the characterization of cellular interactions with a novel self-supervised learning objective – we train it to infer gene expressions of cells based upon their interacting microenvironment. As a result, we construct CI-FM with 100 million parameters by consuming SG data of 23 million cells. Our benchmarking experiments show CI-FM effectively infers gene expressions conditional on the microenvironmental contexts: we achieve a high correlation and a low mismatch error (MSE of 1.1% relative to the square median expression), with 79.4% of cells on average being annotated as the similar cell type based on their predicted and actual expressions. We demonstrate the downstream utility of CI-FM by: (i) applying CI-FM to embed tumor samples to capture cellular interactions within tumor microenvironments (ROC-AUC score of 0.76 on classifying sample conditions via linear probing on embeddings), and identifying shared signatures across samples; and (ii) using CI-FM to simulate changes in microenvironmental composition in response to T cell infiltration, which highlights how CI-FM can be leveraged to model cellular responses to tissue perturbations – an essential step toward constructing “AI virtual tissues”. Our model is open source and publicly accessible athttps://huggingface.co/ynyou/CIFM.
URAdime – a tool for analyzing primer sequences in sequencing data to identify dimers and super-amplicons
Authors: Limberis Jason D , Metcalfe John Z
Published: January 2025

Targeted sequencing of multiplex PCR amplicons is commonplace in research laboratories and clinical diagnostics. There are numerous tools for the a priori optimization of primers and reactions, but no tools to detect specific problematic primers post hoc. We developed URAdime, a tool for analyzing primer sequences in sequencing data to identify dimers and super-amplicons. We show that it successfully detects these unwanted amplicons and accurately attributes their generation to specific primers.
Axonal pathology differentially affects human Purkinje cell subtypes in the essential tremor cerebellum
Authors: Widner James , Faust Phyllis L. , Louis Elan D. , Fujita Hirofumi
Published: January 2025

The cerebellar cortex is organized into discrete regions populated by molecularly distinct Purkinje cells (PCs), the sole cortical output neurons. While studies in animal models have shown that PC subtypes differ in their vulnerability to disease, our understanding of human PC subtype and vulnerability remains limited. Here, we demonstrate that human cerebellar regions specialized for motor vs cognitive functions (lobule HV vs Crus I) contain distinct PC populations characterized by specific molecular and anatomical features, which show selective vulnerability in essential tremor (ET), a cerebellar degenerative disorder. Using a known PC subtype marker, neurofilament heavy chain (NEFH), we found that motor lobule HV contains PCs with high NEFH expression, while cognitive lobule Crus I contains PCs with low NEFH expression in post-mortem samples from healthy controls. In the same cerebella, PC axons in lobule HV were 2.2-fold thicker than those in Crus I. Across lobules, axon caliber positively correlated with NEFH expression. In ET cerebella, we identified motor lobule-specific PC axon pathology with a 1.5-fold reduction in caliber and increased axon variability in lobule HV, while Crus I axons were unaffected. Tremor severity and duration in ET correlated with axon diameter variability selectively in lobule HV PCs. Given that axonal caliber is a major determinant of neural signaling capacity, our results (1) suggest that disrupted cerebellar corticonuclear signaling is occurring in ET, (2) provide evidence of region-specific PC subtypes in the human cerebellum and offer insight into how selective PC vulnerability may contribute to the pathophysiology of cerebellar degeneration.

Significance Statement

The cerebellar cortex has a uniform laminar architecture but contains heterogeneous cell types. Purkinje cells (PCs), the sole output cells of the cerebellar cortex, include subtypes whose lobular distribution is thought to underlie functional segmentation and patterned degeneration of the cerebellum in animal models. However, human PC subtypes and their disease vulnerability remain unknown. Here, we establish the existence of human PC subtypes that appear conserved across mammalian species using both marker expression and axonal thickness. Consistent with its phenotype, we demonstrate differential PC vulnerability to degeneration in essential tremor cerebella, where motor function- mediating PC subtypes display significant axonal thinning, while axons of cognitive function-mediating PC subtypes are spared. These findings advance Purkinje cell type- oriented research in cerebellar disorders.
A niche-dependent redox rheostat regulates epithelial stem cell fate in the distal colon
Authors: Chen Xi , Raghunathan Krishnan , Bao Bin , Ngwa Elsy , Kwong Andrew , Wu Zhongyang , Babcock Stephen , Baek Clara , Ye George , Muppirala Anoohya , Peng Qianni , Rutlin Michael , Bhaumik Mantu , Yang Daping , Kotlarz Daniel , Jadhav Unmesh , Rao Meenakshi , Weerapana Eranthie , Zhou Xu , Ordovas-Montanes Jose , Snapper Scott B. , Thiagarajah Jay R.
Published: January 2025

The intestinal epithelium is a rapidly regenerating tissue dependent on resident stem cell self-renewal and differentiation. The reactive oxygen species (ROS) generating enzyme NADPH oxidase 1 (NOX1) is spatially restricted to the crypt base epithelium in the distal colon. Using NOX1-deletion, along with cell-specific redox reporter mice, lineage tracing, single-cell transcriptomics, cysteine proteomics, and cell metabolic studies, we investigated the role of redox balance in colonic stem cell function. We show that distal colonic stem cells uniquely require NOX1-generated ROS to maintain a relatively oxidized state that promotes stem cell self-renewal. Mechanistically, this occurs through a cellular circuit that connects hypoxia inducible factor 1 (HIF1α)-dependent signaling to ROS regulation of isocitrate dehydrogenase 1 (IDH1), to maintain efficient cell cycle entry and cell fate determination in the relatively hypoxic distal colonic niche environment. Our studies therefore provide a basis for understanding regeneration dynamics and disease propensity in the distal large intestine.

GRAPHICAL ABSTRACT

HIGHLIGHTS

The balance of cycling intestinal stem cells (ISCs) versus committed epithelial cells in the uniquely hypoxic niche of the distal colon is regulated by NADPH oxidase 1 (NOX1) dependent H2O2both at homeostasis and during regeneration.

Physiological increases in cellular H2O2favors maintenance of glycolysis in ISCs for self-renewal through regulation of isocitrate dehydrogenase 1 activity.

Maintenance of the increased cellular oxidative state stabilizes HIF1α through a re-enforcing metabolic circuit.

A shift from a relatively oxidative to a reductive cell environment in distal colonic ISCs leads to decreased progression through the cell cycle and altered cell fate determination.
Spillover is the dominant non-photochemical quenching mechanism in angiosperms
Authors: Nanda Sanchali , Cainzos Maximiliano , Shutova Tatyana , Fataftah Nazeer , Fleig Verena , Lihavainen-Bag Jenna , Bag Pushan , Holzwarth Alfred R. , Jansson Stefan
Published: January 2025

Non-photochemical quenching (NPQ) is an important photoprotective process in plants, but all molecular details of the process(es) involved are yet not understood. We have used advanced spectroscopic techniques (including simultaneous time- and spectrally-resolved room-temperature chlorophyll fluorescence analysis and spectro-kinetic deconvolution) to analyse the processes inArabidopsis, hybrid aspen and Scots pine plants. We used four well-characterizedArabidopsislines (npq1, npq2, npq4and L17) affected in NPQ, together with hybrid aspen lines with corresponding modifications that we generated. The data are described best by a model for NPQ induction with up to five fluorescence components representing distinct biochemical entities. A dominant fluorescing species at the end of NPQ induction was identified as functionally detached and quenched LHCII but most importantly we believe that one represents a “PSII-PSI (Photosystem II-Photosystem I) complex” where direct energy transfer between PSII and PSI (spillover) take place. This provides strong quenching in all three plant species. We suggest a new integrated model for NPQ in higher plants where spillover is a major element and suggest roles for PsbS and zeaxanthin. Moreover, we discuss the link between NPQ and thylakoid rearrangements as thylakoid destacking facilitates direct contact between PSII and PSI; a prerequisite for spillover.
GRNFomer: Accurate Gene Regulatory Network Inference Using Graph Transformer
Authors: Hegde Akshata , Cheng Jianlin
Published: January 2025

Motivation

Gene Regulatory Networks (GRNs) are crucial for understanding cellular processes, but accurately inferring them from gene expression data remains challenging due to the complex, nonlinear interactions between genes and the high dimensionality of the data. We introduce GRNFormer, an advanced graph transformer model designed to accurately infer regulatory relationships between transcription factors and target genes from single-cell RNA-seq transcriptomics data, while supporting generalization across species and cell types.

Results

GRNFormer surpasses existing methods in both accuracy and scalability, achieving an AUROC of 90% and an AUPRC of 86% on test datasets. Our case study on human embryonic stem cells highlights its ability to identify biologically meaningful regulatory interactions and pathways. The freely accessible GRNFormer tool streamlines GRN inference, presenting significant potential to drive advancements in omics data analysis and systems biology.

Availability

https://github.com/BioinfoMachineLearning/GRNformer.git
Target the Heart: a new axis of Alzheimer’s disease prevention
Authors: Heller Lawrence I. , Lowe Allison S. , Del Rosario Hernández Thaís , Gore Sayali V. , Chatterjee Mallika , Creton Robbert
Published: January 2025

Cyclosporine A and other calcineurin inhibitors have been identified as prospective treatments for preventing Alzheimer’s disease. Utilizing a neural network model, Z-LaP Tracker, we previously found that calcineurin inhibitors elicit a unique behavioral profile in zebrafish larvae characterized by increased activity, acoustic hyperexcitability, and reduced visually guided behaviors. Screening a large library of FDA-approved drugs using Z-LaP Tracker revealed a cluster of 65 drugs demonstrating a cyclosporine A-like behavioral profile. 14 of these drugs were heart medications, including angiotensin receptor blockers, beta-blockers, alpha-adrenergic receptor antagonists, and a statin. This suggests some heart medications may be effective in preventing or ameliorating Alzheimer’s disease pathology. Other studies have shown that many of these 14 drugs directly or indirectly inhibit the calcineurin-NFAT pathway, alike cyclosporine A. Dual administration of the heart medications with cyclosporine A in Z-LaP Tracker revealed synergistic effects: lower doses of each heart medication could be delivered in conjunction with a lower dose of cyclosporine A to evoke a similar or larger behavioral effect than higher doses of each drug independently. This indicates that co-administering a low dose of cyclosporine A with select cardiac drugs could be a potentially effective treatment strategy for Alzheimer’s diseaseandcardiovascular dysfunction, while mitigating side effects associated with higher doses of cyclosporine A. Given that heart disease precedes Alzheimer’s disease in many patients, physicians may be able to create a treatment regimen that simultaneously addresses both conditions. Our results suggest that cyclosporine A combined withsimvastatin, irbesartan, cilostazol, doxazosin,ornebivololare the most promising candidates for future exploration.
Allocentric Flocking
Authors: Salahshour Mohammad , Couzin Iain D.
Published: January 2025

Understanding how group-level dynamics arise from individual interactions re- mains a core challenge in collective behavior research. Traditional models assume that animals follow simple behavioral rules, like explicitly aligning with neighbors, yet experimental support for such interactions is often lacking. Here we consider a model grounded in the neurobiological principles underlying animals’ navigational circuits, particularly the fact that animals encode their headings, and also bearings to objects (e.g., other individuals) in their environment, via a world-centered—allocentric—neural coding. We compare this to an egocentric representation, where bearings are encoded with respect to the arbitrary heading of the animal. An allocentric framework, as op- posed to an egocentric one, is shown to enable effective tracking of dynamically moving targets. Moreover, we demonstrate that when individuals themselves act as sensory inputs to each other, that sophisticated, coherent collective motion can emerge di- rectly from navigational circuits (and thus, may readily evolve in nature), without requiring explicit alignment, or additional rules of interaction.
Warming, but not acidification, increases metabolism and reduces growth of redfish (Sebastes fasciatus) in the Gulf of St. Lawrence
Authors: Guitard Joëlle J. , Chabot Denis , Senay Caroline , Robert Dominique , Deslauriers David
Published: January 2025

Understanding the effects of global change, including temperature, pH, and oxygen availability, on commercially important species is crucial for anticipating consequences for these resources and their ecosystems. In the Gulf of St. Lawrence (GSL), redfish (Sebastes spp.) have been under moratorium from 1995 to 2024, with a massive recruitment observed in 2011–2013. However, little is known about their metabolic and thermal physiology, making predictions of their response to changing GSL conditions challenging. To address this, we quantified the effects of four acclimatation temperatures (2.5, 5.0, 7.5, and 10.0 ℃) and two pH levels (7.35 and 7.75) on standard and maximum metabolic rates (SMR and MMR), aerobic scope (AS), hypoxia tolerance (O2crit), food consumption, and growth in redfish. SMR, MMR, and AS increased with temperature, but growth decreased at the highest temperature, likely due to increased metabolic demand, with food consumption similar across 5.0 to 10.0 °C treatments. O2crit was lower for fish acclimated to 2.5 and 5.0 ℃, making redfish less hypoxia-tolerant at higher temperatures. Except from SMR, no significant effect of pH was observed. These results suggest that future changes in the GSL will challenge redfish, with potential long-term effects on their growth due to increased energy requirements.
MIReVTD, a Minimum Information Standard for Reporting Vector Trait Data
Authors: Ryan Sadie J. , Huxley Paul J. , Lippi Catherine A. , Pawar Samraat , Cator Lauren , Rund Samuel S.C. , Johnson Leah R.
Published: January 2025

Vector-borne diseases pose a persistent and increasing challenge to human, animal, and agricultural systems globally. Mathematical modeling frameworks incorporating vector trait responses are powerful tools to assess risk and predict vector-borne disease impacts. Developing these frameworks and the reliability of their predictions hinge on the availability of experimentally derived vector trait data for model parameterization and inference of the biological mechanisms underpinning transmission. Trait experiments have generated data for many known and potential vector species, but the terminology used across studies is inconsistent, and accompanying publications may share data with insufficient detail for reuse or synthesis. The lack of data standardization can lead to information loss and prohibits analytical comprehensiveness. Here, we present MIReVTD, a Minimum Information standard for Reporting Vector Trait Data. Our reporting checklist balances completeness and labor- intensiveness with the goal of making these important experimental data easier to find and reuse, without onerous effort for scientists generating the data. To illustrate the standard, we provide an example reproducing results from anAedes aegyptimosquito study.
deepNGS Navigator: Exploring antibody NGS datasets using deep contrastive learning
Authors: MohammadiPeyhani Homa , Lee Edith , Bonneau Richard , Gligorijevic Vladimir , Lee Jae Hyeon
Published: January 2025

High-throughput sequencing uncovers how B-cells adapt and evolve in response to antigens by generating B-cell receptor (BCR) sequences at an unprecedented scale. As BCR datasets grow to be millions of sequences, using efficient computational methods becomes crucial for analyzing and understanding complex patterns within the data. One important aspect of antibody sequence analysis is detecting clonal families or clusters of related sequences, whether they come from immunization, synthetic libraries or even ML-generated datasets. Such analysis helps us to understand how sequences are evolutionarily connected, and how they might have been selected or evolved. Here we introduce deepNGS Navigator, a computational tool that leverages language models and contrastive learning to transform large datasets of antibody sequences into 2D representations. The resulting 2D maps offer an intuitive visualization of overall diversity of input datasets, which can be clustered based on the sequence distances and their densities across the map. Beyond grouping related sequences, the 2D maps can also point to evolutionary trajectories and capture mutational patterns among closely related sequences. By analyzing properties like charge, hydrophobicity, number of sequence neighbors, and read counts, the maps highlight which clusters are most promising for further investigation while also detecting anomalies or noisy sequences with higher risk. We demonstrate deepNGS Navigator’s utilities on various datasets, including: 1) a synthetic library from a yeast display targeting HER2, 2) a machine learning-generated dataset with a hierarchical tree structure, 3) NGS sequences from a llama immunized against COVID RBD, 4) human naive and memory B-cell sequences, and 5) an insilico dataset simulating B-cell clonal lineages.
Molecular basis of arthropod appendage diversity
Authors: Bruce Heather S. , Patel Nipam H.
Published: January 2025

Arthropods have an incredible diversity of limbs that are modified for walking, chewing, cleaning, mating, grasping, sensing, and more. Understanding the relationships and evolutionary histories of different limbs is a central task, but their sheer diversity makes this a daunting if not impossible task using morphology alone. Here, the in situ expression patterns and CRISPR-Cas9 phenotypes for the five best-studied leg-patterning genes –Distal-less,Sp6-9,dachshund,extradenticle, andhomothorax– are described for all limbs of the crustaceanParhyale.

Crustaceans are well-suited for this task because their limbs are more diverse than those of other arthropods, and each individual possesses a wide range of limb types that are relevant to many other arthropods, living and extinct. These results will a) provide a template for understanding the genetic basis of limb construction in arthropods more generally based on the strong phenotypes that can be obtained with CRISPR-Cas9, and b) contribute to our understanding of the evolution and affinities of highly modified legs like mouthparts and genitalia using molecular methods to complement previous morphological and embryological approaches.
Updated Guidance for Communicating PFAS Identification Confidence with Ion Mobility Spectrometry
Authors: Boatman Anna K. , Chappel Jessie R. , Kirkwood-Donelson Kaylie I. , Fleming Jonathon F. , Reif David M. , Schymanski Emma L. , Rager Julia E. , Baker Erin S.
Published: January 2025

Over the last decade, global contamination from per- and polyfluoroalkyl substances (PFAS) has become apparent due to their detection in countless matrices worldwide, from consumer products to human blood to drinking water. As researchers implement non-targeted analyses (NTA) to more fully understand the PFAS present in the environment and human bodies, clear guidance is needed for consistent and objective reporting of the identified molecules. While confidence levels for small molecules analyzed and identified with high-resolution mass spectrometry (HRMS) have existed since 2014, unification and automation of these levels is needed due to inconsistencies in reporting and continuing innovations in analytical methods. Here, we (i) investigate current practices for confidence level reporting of PFAS identified with liquid chromatography (LC), gas chromatography (GC), and/or ion mobility spectrometry (IMS) coupled with high resolution mass spectrometry (HRMS) and (ii) propose a simple, unified confidence level guidance that incorporates both PFAS-specific attributes and IMS collision cross section (CCS) values.

Synopsis

Unified and simplified requirements guide confidence level assignment in non-targeted PFAS identification efforts with ion mobility spectrometry.
Phylo-HS: A phylogenetic hierarchical softmax for taxonomic classification
Authors: Menegaux Romain
Published: January 2025

Taxonomic binning –assigning taxonomic labels to DNA sequencing reads – is a core component of metagenomics data analysis. While machine learning approaches offer competitive speed and accuracy, their scalability is hindered by the growing number of referenced genomes and species. A major bottleneck lies in the final softmax layer of neural network models, which computes probabilities and gradients for all outcome classes. To address this, we proposePhylo-HS, a hierarchical softmax method that leverages the taxonomic tree to group classes into meaningful clusters. Phylo-HS achieves an order of magnitude speed improvement on a dataset with 5,000 classes and improves classification accuracy compared to frequency-based hierarchical softmax methods. By integrating phylogenetic structure into the model, Phylo-HS effectively balances scalability and accuracy for large-scale metagenomic analysis.