bluuebunny/crossref_metadata_2025_split huggingface dataset:
ASTRO: Automated Spatial Whole-Transcriptome RNA-Expression Workflow
Authors: Zhang Dingyao , Chu Zhiyuan , Huo Yiran , Bai Zhiliang , Fan Rong , Lu Jun , Gerstein Mark 
Published: January 2025

AbstractMotivationDespite significant advances in spatial transcriptomics, the analysis of formalin-fixed paraffin-embedded (FFPE) tissues, which constitute most clinically available samples, remains challenging. Additionally, capturing both coding and noncoding RNAs in a spatial context poses significant challenges. We recently introduced Patho-DBiT, a technology designed to address these unmet needs. However, the marked differences between Patho-DBiT and existing spatial transcriptomics protocols necessitate specialized computational tools for comprehensive whole-transcriptome analysis in FFPE samples.ResultsHere, we present ASTRO, an automated pipeline developed to process spatial transcriptomics data. In addition to supporting standard datasets, ASTRO is optimized for whole-transcriptome analyses of FFPE samples, enabling the detection of various RNA species, including non-coding RNAs such as miRNAs. To compensate for the reduced RNA quality in FFPE tissues, ASTRO incorporates a specialized filtering step and optimizes spatial barcode calling, increasing the mapping rate. These optimizations allow ASTRO to spatially quantify coding and non-coding RNA species in the entire transcriptome and achieve robust performance in FFPE samples.AvailabilityCodes are available at GitHub (https://github.com/gersteinlab/ASTRO).
Evaluating Seqstant LiveGene Analysis in Real-Time Assessment of Metagenomic Next-Generation Sequencing (mNGS) Data from Respiratory Samples
Authors: Boutin Sébastien , Klein Sabrina , Untergasser Gerold , Loka Tobias P. , Jakob Suzan , Khatamzas Elham , Wrettos Georg , Knobloch Henri , Nurjadi Dennis 
Published: January 2025

AbstractBackgroundThe detection of pathogens causing infections by conventional diagnostic methods can be challenging and next-generation sequencing (NGS) technology offers a promising alternative method. In this study, we evaluated the performance of real-time metagenomic next-generation sequencing (rt-mNGS) for the detection of pathogens in respiratory samples.MethodWe used rt-mNGS, using the Seqstant LiveGene Analysis platform, on 335 respiratory samples in comparison to conventional culture results.ResultsWe observed an overall good concordance in 71.64% (240/335) of the methods. The rt-mNGS outperformed the gold standard culture in 16.12% (54/335) of the samples, while the culture was superior in detecting the clinically relevant pathogen in 12.24% (41/335) of the samples. The non-inferiority of rt-mNGS was statistically significant (δ = 10,α= 0.05, 1− β= 0.8). We also observed that the real-time analysis of NGS data is beneficial in obtaining reliable timely results as the initial report at cycle 46 exhibits a Positive Predictive Value (PPV) of 93.75% at the species-level with a sensitivity of 32.09%.ConclusionOverall, our study showed the non-inferiority of rt-mNGS compared to the standard-of-care microbiology for respiratory samples with statistical significance. Moreover, the rt-mNGS method exhibited superior sensitivity and superior overall performance. It also uniquely detected certain organisms that are typically hard to culture. However, rt-mNGS reported a higher number of false positives and faced limitations in detectingAspergillusspp. In conclusion, the study highlights the potential of rt-mNGS as a powerful tool in clinical diagnostics of respiratory infections and beyond.
Applied Machine Learning for human bacteria MALDI-TOF Mass Spectrometry: a systematic review
Authors: Schmidt Santiago Lucía , Guerrero-López Alejandro , Sevilla-Salcedo Carlos , Rodríguez Temporal David , Rodríguez-Sánchez Belén , Gómez-Verdejo Vanessa 
Published: January 2025

AbstractBacterial identification, antimicrobial resistance prediction, and strain typification are critical tasks in clinical microbiology, essential for guiding patient treatment and controlling the spread of infectious diseases. While machine learning (ML) and deep learning (DL) have shown immense promise in enhancing MALDI-TOF mass spectrometry applications for these tasks, a comprehensive review from a technical perspective remains lacking. To address this gap, we systematically reviewed 93 studies published between 2004 and 2024, focusing on key ML/DL aspects such as data size and balance, preprocessing pipelines, peak selection methods, algorithms, evaluation techniques, and the availability of open-source data and code. Our analysis highlights the predominant use of classical ML models like random forests and support vector machines, alongside emerging interest in DL approaches for handling complex, high-dimensional data. Despite significant progress, challenges such as inconsistent preprocessing workflows, reliance on blackbox models, limited external validation, and insufficient opensource resources persist, hindering transparency, reproducibility, and broader adoption. By addressing these critical gaps, this review provides actionable insights to bridge microbiological and technical perspectives, paving the way for more robust, scalable, and interpretable solutions in diagnostic microbiology.
Epigenetic priming promotes acquisition of tyrosine kinase inhibitor resistance and oncogene amplification in human lung cancer
Authors: Starble Rebecca M. , Sun Eric G. , Gbyli Rana , Radda Jonathan , Lu Jiuwei , Jensen Tyler B. , Sun Ning , Khudaverdyan Nelli , Hu Bomiao , Melnick Mary Ann , Zhao Shuai , Roper Nitin , Wang Gang Greg , Song Jikui , Politi Katerina , Wang Siyuan , Xiao Andrew Z. 
Published: January 2025

SummaryIn mammalian cells, gene copy number is tightly controlled to maintain gene expression and genome stability. However, a common molecular feature across cancer types is oncogene amplification, which promotes cancer progression by drastically increasing the copy number and expression of tumor-promoting genes. For example, in tyrosine kinase inhibitor (TKI)-resistant lung adenocarcinoma (LUAD), oncogene amplification occurs in over 40% of patients’ tumors. Despite the prevalence of oncogene amplification in TKI-resistant tumors, the mechanisms facilitating oncogene amplification are not fully understood. Here, we find that LUADs exhibit a unique chromatin signature demarcated by strong CTCF and cohesin deposition in drug-naïve tumors, which correlates with the boundaries of oncogene amplicons in TKI-resistant LUAD cells. We identified a global chromatin priming effect during the acquisition of TKI resistance, marked by a dynamic increase of H3K27Ac, cohesin loading, and inter-TAD interactions, which occurs before the onset of oncogene amplification. Furthermore, we have found that the METTL7A protein, which was previously reported to localize to the endoplasmic reticulum and inner nuclear membrane, has a novel chromatin regulatory function by binding to amplified loci and regulating cohesin recruitment and inter-TAD interactions.Surprisingly, we discovered that METTL7A remodels the chromatin landscape prior to large-scale copy number gains. Furthermore, while METTL7A depletion has little effect on the chromatin structure and proliferation of drug-naïve cells, METTL7A depletion prevents the formation and maintenance of TKI resistant-clones, highlighting the specific role of METTL7A as cells are becoming resistant. In summary, we discovered an unexpected mechanism required for the acquisition of TKI resistance regulated by a largely uncharacterized factor, METTL7A. This discovery sheds light into the maintenance of oncogene copy number and paves the way to the development of new therapeutics for preventing TKI resistance in LUAD.
Avoidance of pyroptosis accounts for the relatively high metastatic potential observed in early hybrid EMT states
Authors: Verma Aakanksha , Genna Alessandro , Vinik Yaron , Nataraj Nishanth Belugali , Abedrabbo Maha , Selvadurai Boobash Raj , Bhandari Tithi , Aharoni Noa , Ramesh Palaniappan , Boguslavski Boris , Drago Diana , Salame Tomer-Meir , Prior Amir , Levin Yishai , Weizman Eviatar , Zhu Rong , Caldas Carlos , Rueda Oscar M. , Lev Sima , Yarden Yosef 
Published: January 2025

SummaryEMT converts epithelial (E) phenotypes to invasive mesenchymal (M) states. However, analyses of circulating tumor cells (CTCs) indicated that biphenotypic (E+M) CTCs better correlate with metastasis. Similarly, investigations of murine tumors undergoing EMT concluded that early E+M states posses the highest metastatic potential. To explore this, we selected in animals with breast cancer CTCs having progressively increasing intravasation abilities. This revealed that downregulation of arrestin Arrdc4 associates with CTC aggressiveness. In xenografts, depleting Arrdc4 accelerated tumor progression, whereas overexpression hindered progression in immunocompetent, but not in immunocompromised mice. Mechanistically, high Arrdc44 suppresses glucose uptake and enhances gasdermin E, triggering pyroptosis a type of pro-inflammatory cell death. Consistently, Arrdc4’s lowest levels characterize the most metastatic biphenotypic states. In patients, both epigenetic and chromosomal aberrations downregulate ARRDC4 and predict poor prognosis. In summary, the uncovered mechanism portrays pyroptosis of biphenotypic EMT cells as a rheostat of CTCs, which may resolve the controversy on the role played by EMT in metastasis.
Genetic dissection of cyclic di-GMP signaling inPseudomonas aeruginosa viadiguanylate cyclase disruption
Authors: Martino Román A. , Volke Daniel C. , Tenaglia Albano H. , Tribelli Paula M. , Nikel Pablo I. , Smania Andrea M. 
Published: January 2025

AbstractThe second messengerbis-(3′→5′)-cyclic dimeric guanosine monophosphate (c-di-GMP) governs adaptive responses in the opportunistic pathogenPseudomonas aeruginosa, including biofilm formation and the transition from acute to chronic infections. Understanding the intricate c-di-GMP signaling network remains challenging due to the overlapping activities of numerous diguanylate cyclases (DGCs). In this study, we employed a CRISPR-based multiplex genome-editing tool to disrupt all 32 GGDEF domain-containing proteins (GCPs) implicated in c-di-GMP signaling inP.aeruginosaUCBPP-PA14. Phenotypic and physiological analyses revealed that the resulting mutant was unable to form biofilms and had attenuated virulence. Residual c-di-GMP levels were still detected despite the extensive GCP disruption, underscoring the robustness of this regulatory network. Taken together, these findings provide insights into the complex c-di-GMP metabolism and showcase the importance of functional overlapping in bacterial signaling. Moreover, our design overcomes the native redundancy in c-di-GMP synthesis, providing a framework to dissect individual DGC functions and paving the way for targeted strategies to address bacterial adaptation and pathogenesis.
The evolution of Hutchinsonian climatic niche hypervolumes in gymnosperms
Authors: Caron Fernanda S. , Burslem David F. R. P. , Morimoto Juliano 
Published: January 2025

ABSTRACTThe niche is a fundamental concept in ecology. One way to represent the niche is to use multidimensional geometry known as the Hutchinsonian niche hypervolume. However, hypervolume data are complex and the biological significance of niche hypervolume properties needs to be better understood. Here, we conducted for the first time a systematic and comprehensive test of the evolution of Hutchinsonian niche hypervolume properties (volume and holes) across 65 genera and 12 families of gymnosperms, which includes many species that are endangered or threatened. Using cutting-edge computational algorithms, we measured the evolution of geometric (i.e. volume) and topological (i.e. holes) properties of gymnosperm hypervolumes across a comprehensive calibrated phylogeny. Our comparative analysis revealed weak evidence of the non-independent evolution of niche hypervolume volume and no evidence of the non-independent evolution of hypervolume holes. We also found that genera and families with low hypervolume volume such as monotypic groups likeGingko, likely experienced shifts in hypervolume evolutionary rates. Our results show that geometric and topological properties of gymnosperm climatic niche hypervolumes evolve independently. This agrees with competitive exclusion hypothesis where extant groups are likely to be the ones which minimise niche overlap and competition.
GO Big or Go Home: A New Gene Ontology Subset that Improves Plant Gene Function Prediction
Authors: Fattel Leila , Lawrence-Dill Carolyn J. 
Published: January 2025

AbstractBackgroundThe availability of gene function prediction datasets helps researchers to consider possible functions for uncharacterized genes for hypothesis generation, candidate gene prioritization, and many other applications. Many such datasets are based on the Gene Ontology (GO) function graph. For plants this can be problematic because the most specific GO terms available are often derived from the biology of non-plant taxa (e.g., functions specific to nerve function would not seem likely to map to plant biological processes given that plants lack nerves). To balance the need for functional specificity while limiting to functions relevant to plant biology, researchers often limit to the GO Slim plant subset, but, by design, that subset consists of very general terms and limits real utility for e.g., specific hypothesis generation. Worse yet, sometimes researchers choose to simply throw out terms if they are not relevant to plant biology (rather than traversing the GO graph to select the most specific term in that hierarchy that is compatible with plant biology).ResultsWe created GO Big, a Gene Ontology subset type, to improve the biological relevance of gene function predictions for taxon-specific biology applications. GO Big plant subsets retain maximal functional specificity for hypothesis generation while limiting to terms applicable to the biology of plants. In brief, we used a curatorial approach to generate two GO Big subsets, a general subset derived from terms with experimentally validated functions across Viridiplantae species, and a species-specific subset for maize (Zea maysssp.mays).ConclusionAnnotating genes with assignments that better reflect the biology of a taxon can pave the way for more biologically accurate and testable hypotheses for genes of interest. The subsets produced here can help plant biologists limit genome-wide gene function prediction sets to functions possible for plant genes, and the process to generate GO Big subsets is described in detail to enable others to create GO Big subsets for additional taxon sets, including ones for protists, fungi, and other phylogenetic categories.
Particular Amino Acid on Lateral Interface Maintains FtsZ Function Under Acid Stress inStreptococcus mutans
Authors: Chen Yuxing , Li Yongliang , Niu Jiahao , Yang Liuchang , Chi Yaqi , Cai Xue , Xin Fengjiao , Zhang Jie , Fang Xianyang , Mondal Manas , Gao Yiqin , Wang Xiaoyan 
Published: January 2025

AbstractFtsZ is the core protein for cell division in bacteria that can polymerize into Z-rings and drive cytokinesis. Understanding how bacteria maintain the correct function of FtsZ under various environmental stresses is crucial for novel antibacterial drug discovery. Our previous study revealed that the FtsZ inS. mutanshas higher self-assembly and GTPase activity under acidic stress, which may be responsible for the cariogenesis ofS. mutans. However, the mechanism is still unknown. Here, we further reported the crystal structure ofS. mutansFtsZ, revealing a unique lateral interface. Through protein polymerization and GTPase ability assay, we experimentally demonstrated that mutation of Arg68 on this lateral interface significantly reduced the functional activity of FtsZ in an acidic environment. The phenotype assay and rat caries model further showed that mutation of Arg68 effectively inhibited the acid resistance ofS. mutansand the occurrence and progress of dental caries in vivo. By employing a molecular dynamics simulation analysis, we conclude that mutation of Arg68 disrupts the conformation change necessary for SmFtsZ polymerization under acidic conditions. Our study proposes a novel mechanism to maintain FtsZ function in bacteria and could be a potential target for antimicrobial drugs to inhibit the growth ofS. mutansin an acidic environment.Significance StatementFtsZ is the core protein that drives cytokinesis. Maintaining the self-assembly and GTPase activity of FtsZ plays a critical role in cell growth under environmental stress. Currently, research on FtsZ function maintenance under stress mainly focuses on model organisms, with less on other pathogenic bacteria. This study reveals a novel structural mechanism for the acidic tolerance of FtsZ inS. mutanswhich survives in strongly acidic surroundings. Meanwhile, Arg68 on the lateral interface of SmFtsZ may be a potential therapeutic target to regulate microecology and combatS. mutans-associated dental caries.
Lepidoptera Diversity, Richness, and Distribution in Semi-Urban Farmland and other Habitats around Lumbini, Rupandehi
Authors: Baral Celeus , Baral Hem Sagar , Inskipp Carol , Maharjan Rajana 
Published: January 2025

AbstractThis study comprehensively examined Lepidoptera diversity in the semi-urban agricultural landscapes of Lumbini, Nepal, documenting 30 moth species from six families and 39 butterfly species from five families over 14 days. Field methods included moth traps with 50 Watts LED lights inside a box with egg cartons for moth trapping and butterfly transect surveys across various habitats—grasslands, shrublands, and agricultural areas for recording butterfly species. The Erebidae family dominated moth populations, while Nymphalidae led butterfly diversity, showing resilience in disturbed habitats influenced by environmental factors such as weather patterns, lunar phases, and habitat characteristics. Statistical analyses using Simpson’s Diversity Index, Shannon-Wiener Diversity Index, Pielou’s Evenness Index, and Margalef’s Richness Index revealed that shrubland and agricultural habitats supported the highest species richness and evenness, while grasslands hosted fewer species. The study highlighted the importance of agricultural and shrubland ecosystems for biodiversity, emphasizing ongoing monitoring to understand how Lepidoptera populations respond to environmental changes, offering essential insights for future conservation efforts.
Complete genome sequence assembly elucidates evolution and regulation of 5S rDNA loci in the greater duckweedSpirodela polyrhiza
Authors: Stepanenko Anton , Schubert Veit , Chen Guimin , Kishchenko Olena , Michael Todd P. , Lam Eric , Hrmova Maria , Schubert Ingo , Borisjuk Nikolai 
Published: January 2025

AbstractWe resolved the molecular architecture of the 5S rDNA loci in an aquatic monocotSpirodela polyrhiza. Measurements of fluorescencein situhybridization signals revealed two loci with 5S rDNA clusters. A combination of the extra-long DNA reads and conventional sequencing of 5S rDNA repeats allowed the assembling of complete loci sequences located on ChrSp6 and ChrSp13. The homologous chromosomes of the ChrSp6 locus contain clusters of 40 and >60 copies of 5S rDNA repeat units with intergenic spacer (IGS) of 400 bp. The ChrSp13 locus is represented by 5S rDNA clusters of rRNA genes spaced by IGSs of 1,056 or 1,069 bp arranged in two sub-clusters, suggesting a different rate of repeat homogenization between loci. The G/C-rich 5S rDNA arrays in both loci are embedded in A/T-enriched chromosome regions with possible regulatory functions. The TATA-like boxes of the 5S rDNA repeat on ChrSp6 and ChrSp13 exhibit different affinities for the TATA-binding protein in 3D modeling of protein/DNA interactions, suggesting a locus-specific regulation of rRNA transcription. Our findings shed light on the molecular architecture of the 5S rDNA loci, which could foster an innovative era for the principles of evolution and regulation of rRNA genes in plants.
Single-Cell Genomics Elucidates Molecular Variations and Regulatory Mechanisms in Circulating Immune Cells
Authors: Yin Jianhua , Zheng Yuhui , Huang Zhuoli , Zhou Wenwen , Yuan Yue , Cai Pengfei , Bai Yong , Yang Shichen , Gao Yue , Duan Shanshan , Wang Yang , Zhang Wenxi , Zhang Xinyu , Wei Yilin , Xu Zekai , Huang Yaling , Liu Ying , Wang Weikai , Yang Tao , Lv Jingzhi , Zhang Zhongjin , Chen Xiaoya , Zhang Xiru , Li Fupeng , Zhang Yan , Zeng Guodan , Wang Xue , Ma Wen , Hou Guixue , Hao Shijie , Liu Chang , Lai Yiwei , Wang Bo , Li Yuxiang , Zhang Wenwei , Gao Peng , Xie Jun , Esteban Miguel A. , Gu Ying , Ji Jiansong , Qi Ting , Liu Boxiang , Wang Jian , Yang Jian , Xu Xun , Liu Longqi , Jin Xin , Liu Chuanyu 
Published: January 2025

AbstractThe human peripheral blood displays diverse molecular characteristics across populations, understanding the drivers and underlying mechanisms of which remains challenging. Here, we introduce the Chinese Immune Multi-Omics Atlas (CIMA), elucidating sex-, age-, and genetic-related molecular variations by analyzing multi-omics data from 428 adults with over 10 million immune cells. CIMA generated an enhancer-driven gene regulatory network, identifying 237 high-quality regulons and revealing cell type-specific regulatory mechanisms. Additionally, 11,521 leadcis-expression quantitative trait loci (eQTLs) and 46,339 chromatin accessibility QTLs (caQTLs) were identified at cell type level. CIMA also uncovered pleiotropic associations among immune-related disease risk loci, eQTLs, and caQTLs in a cell type-specific manner. Lastly, a novel cell language model, CIMA-CLM, was developed to predict chromatin accessibility and noncoding variant effects using chromatin sequences and gene expressions. This work represents a population-scale multi-omics resource of human immune cells, providing a valuable reference for future investigation of immune-related diseases.
Reproducible Boolean model analyses and simulations with the CoLoMoTo software suite: a tutorial
Authors: Noël Vincent , Naldi Aurélien , Calzone Laurence , Paulevé Loic , Thieffry Denis 
Published: January 2025

AbstractThis tutorial provides stepwise instructions to install the 20 tools integrated in the CoLoMoTo software suite, to develop reproducible dynamical analyses of logical models of complex biological molecular networks.The tutorial specifically focuses on the analysis of a previously published model of the regulatory network controlling mammalian cell proliferation. It includes chunks of python code to reproduce several of the results and figures published in the original article and further extend these results with the help of a selection of tools included in the CoLoMoTo suite.The notebook covers the visualisation of the network with the tool GINsim, an attractor analysis with bioLQM, the computation of synchronous attractors with BNS, the extraction of modules from the full model, MaBoSS simulations of the wild-type model, as well as of selected mutants, and finally the delineation of compressed probabilistic state transition graphs.The integration of all these analyses in an executable Jupyter notebook greatly eases their reproducibility, as well as the inclusion of further extensions. This notebook can further be used as a template and enriched with other ColoMoTo tools to enable comprehensive dynamical analyses of biological network models.