bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple interactions mediate the localization of BLTP2 at ER-PM contacts to control plasma membrane dynamics
Authors: Dai Anbang , Xu Peng , Amos Chase , Fujise Kenshiro , Wu Yumei , Yang Han , Eisen Julia N. , Guillén-Samander Andrés , De Camilli Pietro 
Published: February 2025

SummaryBLTP2/KIAA0100, a bridge-like lipid transfer protein, was reported to localize at contacts of the endoplasmic reticulum (ER) with either the plasma membrane (PM) or recycling tubular endosomes depending on the cell type. Our findings suggest that mediating bulk lipid transport between the ER and the PM is a key function of this protein as BLTP2 tethers the ER to tubular endosomes only after they become continuous with the PM and that it also tethers the ER to macropinosomes in the process of fusing with the PM. We further identify interactions underlying binding of BLTP2 to the PM, including phosphoinositides, the adaptor proteins FAM102A and FAM102B, and also N-BAR domain proteins at membrane-connected tubules. The absence of BLTP2 results in the accumulation of intracellular vacuoles, many of which are connected to the plasma membrane, pointing to a role of the lipid transport function of BLTP2 in the control of PM dynamics.
ChemEmbed: A deep learning framework for metabolite identification using enhanced MS/MS data and multidimensional molecular embeddings
Authors: Faizan-Khan Muhammad , Giné Roger , Badia Josep M. , Pérez-Ribera Maribel , Junza Alexandra , Vinaixa Maria , Sales-Pardo Marta , Guimerà Roger , Yanes Oscar 
Published: February 2025

AbstractMachine learning tools have become essential for annotating the vast number of unidentified MS/MS spectra in metabolomics, addressing the limitations of current reference spectral libraries. However, these tools often struggle with the high dimensionality and sparsity of MS/MS spectra and metabolite structures. ChemEmbed introduces a novel approach by combining multidimensional and continuous vector representations of chemical structures with enhanced MS/MS spectra. This enhancement is achieved by merging spectra from multiple collision energies and incorporating calculated neutral losses from 38,472 distinct compounds, providing richer input for a convolutional neural network (CNN). ChemEmbed achieves top-ranked candidate annotations in over 42% of cases and identifies the correct compound within the top five in more than 76% of cases in a test dataset. Against external benchmarks such as CASMI 2016 and 2022, ChemEmbed outperforms SIRIUS, the current state-of-the-art in computational metabolomics. In a validation experiment with the Annotated Recurrent Unidentified Spectra (ARUS) dataset— including over 25,000 spectra from human plasma and 68,000 from urine— ChemEmbed successfully identified 24 previously unannotated compounds. By aligning with the advanced capabilities of modern mass spectrometry instrumentation, ChemEmbed balances accuracy, computational efficiency, and scalability, making it a powerful solution for high-throughput metabolomics applications.
Early cell cycle genes in cortical organoid progenitors predict interindividual variability in infant brain growth trajectories
Authors: Glass Madison R. , Matoba Nana , Beltran Alvaro A. , Patel Niyanta K. , Farah Tala M. , Eswar Karthik , Bhargava Shivam , Huang Karen , Curtin Ian , Ahmed Sara , Srivastava Mary , Drake Emma , Davis Liam T. , Yeturi Meghana , Sun Kexin , Love Michael I. , Simon Jeremy M. , St. John Tanya , Marrus Natasha , Pandey Juhi , Estes Annette , Dager Stephen , Schultz Robert T. , Botteron Kelly , Evans Alan , Kim Sun Hyung , Styner Martin , McKinstry Robert C. , Collins D. Louis , Volk Heather , Benke Kelly , Zwaigenbaum Lonnie , Hazlett Heather , Beltran Adriana S. , Girault Jessica B. , Shen Mark D. , Piven Joseph , Stein Jason L. ,   the Infant Brain Imaging Study Network
Published: February 2025

SummaryHuman induced pluripotent stem cell (iPSC) derived cortical organoids (hCOs) model neurogenesis on an individual’s genetic background. The degree to which hCO phenotypes recapitulate the brain growth of the participants from which they were derived is not well established. We generated up to 3 iPSC clones from each of 18 participants in the Infant Brain Imaging Study, who have undergone longitudinal brain imaging during infancy. We identified consistent hCO morphology and cortical cell types across clones from the same participant. hCO cross-sectional area and production of cortical hem cells were associated within vivocortical growth rates. Cell cycle associated genes expression in early progenitors at the crux of fate decision trajectories were correlated with cortical growth rate from 6-12 months of age, and were enriched in microcephaly and neurodevelopmental disorder genes. Our data suggest the hCOs capture inter-individual variation in cortical cell types influencing infant cortical surface area expansion.
Novel Protein Structure Validation using PDBMine and Data Analytics Approaches
Authors: Pandala Niharika , Brown Katherine G. , Valafar Homayoun 
Published: February 2025

AbstractProtein structure prediction is essential for understanding biological functions and advancing drug development. Although experimental techniques like NMR, X-ray crystallography, and cryo-EM provide valuable insights, they are expensive and time-consuming, prompting reliance on computational approaches. AlphaFold2 revolutionized protein model predictions accuracy in 2020. However, limitations remain in the prediction of novel proteins, complex conformations, and mutations. To address these challenges, we leverage PDBMine software and machine learning for advanced data analytics. This approach detects and corrects structural inaccuracies, calculates fitness scores, and enhances model reliability, accelerating drug discovery and therapeutic breakthroughs by bridging gaps in current protein prediction capabilities.
Cumulative effects of high temperature and low dissolved oxygen alter the acute thermal tolerance and cellular stress response in lake trout
Authors: Weinrauch Alyssa M , Lazaro-Côté Analisa , Durhack Travis C , Enders Eva C , Jeffries Ken M 
Published: February 2025

AbstractLake trout (Salvelinus namaycush) is an important food fish in Northern communities, inhabiting cool, well-oxygenated water. Yet, climate change is reducing available habitat with extended summer stratification of lakes creating an upper thermal barrier (∼15 °C) and lower dissolved oxygen (DO) boundary (4-7 mg L-1). Together, these environmental factors can influence tolerance thresholds and climate change may lead to abiotic factors exceeding these physiological thresholds in lake trout habitats. Thresholds can shift with environmental acclimation in lake trout populations, but the functional basis of this shift has yet to be examined. The abundance of mRNA transcripts offers insight into underlying cellular responses to environmental stressors that can provide an early warning of fitness consequences. Here, we used a stress-response transcriptional profiling chip to investigate a suite of genes involved in thermal and general stress in lake trout acclimated to a range of temperatures (6-18 °C) and DO (normoxia: > 8.5 mg L-1or hypoxia: 5.5-6.5 mg L-1), as well as following an acute thermal stress (i.e., CTmax). Transcriptional profiles were assessed in the gill, liver, and and epidermal mucus. Generally, fish acclimated to the greatest combined stressor (18 °C and hypoxia) had the largest transcriptional response, suggestive of a transition from a routine stress response to an extreme survival response. A noted temperature dependence occurred in liver tissue, which was not evident in gill or mucus tissues. Further, transcriptional responses in the gill and mucus were highly correlated (r= 0.74-0.87), highlighting the potential use of these tissues for non-lethal sampling methods to enhance management and conservation strategies for lake trout across their distribution.
Archaeal lineages related to eukaryotes encode functional diterpenoid cyclases
Authors: McShea Hanon , De Anda Valerie , Brocks Jochen J. , Welander Paula V. , Baker Brett J. 
Published: February 2025

SummaryThe first eukaryotic cell originated through the union of an archaeon (Asgardarchaeota) and a bacterium (Alphaproteobacteria)1–4. Little is known about the molecular basis of eukaryogenesis, but it is likely that lipids played a key role in this process. Modern eukaryotic membranes contain polycyclic triterpenoids (mainly sterols) that are essential for a variety of cellular functions, but these lipids have not been identified in archaea. The lipid composition of Asgardarchaeota including the newly described class Hodarchaeales, which share a common ancestor with eukaryotes, is unknown. Here, we investigated the potential for Asgards to produce cyclic terpenoids. Phylogenomics coupled with structural prediction revealed that Asgards lack the capacity to make sterols, yet organisms from the clades Hodarchaeales and Kariarcheales encode for divergent homologs of sterol cyclases, predicted to produce diterpenoids. We tested the functionality of these enzymesin vitro, showing that they cyclize geranylgeranyl pyrophosphate to form bicyclic halimadienyl pyrophosphate. Halimadienyl lipids have previously been shown to mediate intracellular persistence ofMycobacterium tuberculosisin host endosomes5–7, and may function similarly Asgardarchaeota. This is the first evidence of experimentally validated diterpenoid cyclases in archaea, providing new insights into the biochemistry of these microbes pivotal in the evolution of complex cellular life.
Size switchable DNA origami structure enabled by dynamic crossovers
Authors: Li Xueqiao , Gao Rui , Wang Xiaoxue , Wu Wenna , Liu Huajie , Zhang Tao 
Published: February 2025

AbstractDNA nanostructures are formed by many DNA double helices connected via crossovers. If multiple DNA double helices are connected by crossovers at different base positions (different rotational angles), these DNA double helices are stacked together to obtain desired two- or three-dimensional DNA structures. Here we inserted i-motif or hairpin motifs in crossover regions of one layer DNA origami structure and employed dynamic DNA element to implement size-switchablity between expansion and contraction. By changing pH or adding complementary strands to regulate interspacings between DNA double helixes, multiple crossover replacements realize the dynamic size changes between 68 nm and 150 nm as characterized by atomic force microscopy. We further demonstrated dynamic sizes changes enabled or inhibited FRET (fluorescence resonance energy transfer) signals between Cy3 and Cy5 and the controlled distances between protein molecules. The results reveal the feasibility of fabricating size-switchable DNA origami nanostructures via crossover redesign, demonstrating their potential in nano-engineering, proximity enabled chemical reacitons, as well as for biomedical applications.
Suppressed macrophage response to quorum-sensing-activeStreptococcus pyogenesoccurs at the level of the nucleus
Authors: Feldstein Sam F. , Rahbari Kate M. , Leonardo Trevor R. , Alvernaz Suzanne A. , Federle Michael J. 
Published: February 2025

AbstractStreptococcus pyogenes, or Group A Streptococus (GAS), a significant human pathogen, employs quorum sensing (QS) systems to coordinate its behavior and genetic regulation in order to enhance survival. Our previous research established that one such QS system, the Rgg2/3 system, can suppress macrophage NFκB activity and production of pro-inflammatory cytokines. Yet, the scope of suppression and the mechanism by which it occurs remains unknown. In this study, we used transcriptomic and phosphoproteomic approaches to address these unanswered questions. We found QS-ON GAS broadly suppressed most inflammatory transcriptional pathways including those of NFκB, type I and type II interferon responses, and intracellular stress responses. Yet, we found no alternative transcriptional programs were activated after QS-ON GAS infection. Additionally, phosphoproteomics showed no disruption in typical inflammatory pathways such as those related to NFκB and MAPK activation, which was confirmed by western blotting and translocation assays. Instead, the proteomic data highlighted a potential role for epigenetic mechanisms of inflammatory regulation. To determine if epigenetic regulation was involved in QS-mediated immunomodulation, DNA methylation was measured and studies were performed inhibiting various histone and chromatin modifiers. These studies also showed no dijerence between QS-ON compared with QS-OFF infected macrophages. These findings expand our understanding of QS-mediated suppression and of GAS virulence strategies that appear to employ unusual methods of restricting inflammation. Uncovering this mechanism will ojer invaluable insight into GAS, itself, as well as understudied immunological pathways.ImportanceStreptococcus pyogenesis a ubiquitous pathogen that causes over 600 million infections every year and 500 thousand to 1 million fatalities. While in developed countries it is generally known to cause mild conditions such as pharyngitis, it can also manifest as severe infections such as necrotizing fasciitis, septic arthritis, and lead to post-infectious sequelae including rheumatic heart disease and glomerulonephritis. Elucidating new mechanisms of virulence in this organism, including how it evades and suppresses immune responses can be critical in understanding its pathogenicity, epidemiology, and identification of novel treatment avenues in this era of multi-drug-resistant bacteria. In this study, we characterize the broad spectrum by which GAS modulates the host innate immune response and begin to uncover host pathways that bacteria can use or inhibit for its survival.
DISRUPTION OF TRANSTHALAMIC CIRCUITRY FROM PRIMARY VISUAL CORTEX IMPAIRS VISUAL DISCRIMINATION IN MICE
Authors: McKinnon C. , Mo C. , Sherman S. M. 
Published: February 2025

ABSTRACTLayer 5 (L5) of the cortex provides strong driving input to higher-order thalamic nuclei, such as the pulvinar in the visual system, forming the basis of cortico-thalamo-cortical (transthalamic) circuits. These circuits provide a communication route between cortical areas in parallel to direct corticocortical connections, but their specific role in perception and behavior remains unclear. Using targeted optogenetic inhibition in mice performing a visual discrimination task, we selectively suppressed the corticothalamic input from L5 cells in primary visual cortex (V1) at their terminals in pulvinar. This suppresses transthalamic circuits from V1; furthermore, any effect on direct corticocortical projections and local V1 circuitry would thus result from transthalamic inputs (e.g., V1 to pulvinar back to V1 (Miller-Hansen and Sherman, 2022). Such suppression of transthalamic processing during visual stimulus presentation of drifting gratings significantly impaired discrimination performance across different orientations. The impact on behavior was specific to the portion of visual space that retinotopically coincided with the V1 L5 corticothalamic inhibition. These results highlight the importance of incorporating L5-initiated transthalamic circuits into cortical processing frameworks, particularly those addressing how the hierarchical propagation of sensory signals supports perceptual decision-making.SIGNIFICANCE STATEMENTAppreciation of pathways for transthalamic communication between cortical areas, organized in parallel with direct connections, has transformed our thinking about cortical functioning writ large. Studies of transthalamic pathways initially concentrated on their anatomy and physiology, but there has been a shift towards understanding their importance to cognitive behavior. Here, we have used an optogenetic approach in mice to selectively inhibit the transthalamic pathway from primary visual cortex to other cortical areas and back to itself. We find that such inhibition degrades the animals’ ability to discriminate, showing for the first time that specific inhibition of visual transthalamic circuitry reduces visual discrimination. This causal data adds to the growing evidence for the importance of transthalamic signaling in perceptual processing.
Circulating extracellular vesicles from HIV-1 gp120-treated mice act as endogenous algogens, mediating and maintaining HIV-associated chronic pain
Authors: Yuan Subo , Liew Jia Yi , Bei Jiani , Pal Ajay , Qiu Yuan , Shang Junkui , Araya Katherine , Tat Vivian , Hao Haiping , Gamez Isaac , Haines Connor , Chang Qing , Saito Tais B. , Khanipov Kamil , Gong Bin 
Published: February 2025

AbstractHIV-associated chronic pain (HIV-PAIN) remains prevalent in the post combined antiretroviral therapy era, affecting 30-60% of HIV patients worldwide. The underlying mechanism responsible for the development and maintenance of chronic pain remains unclear. gp120 is a causal factor of the HIV-PAIN and functions as an exogenous algogen. The pain experienced by human HIV-PAIN has been modeled in mice (referred to as mHIV-PAIN) using intrathecal (i.t.) injections of gp120. gp120 is a relatively short-term, static, exogenous algogen that is exhaustiblein vivo. In authentic infection, HIV virions serve as the primary source of exogenous gp120, which initiates the early phase of clinical HIV-PAIN. Interestingly, while the source of replenishing gp120 decreases after antiretroviral therapy by suppressing viremia, the prevalence of chronic HIV-PAIN remains stable. To induce chronic pain in mice, gp120 needs to be repeatedly applied by the i.t. route. This raises a key question: Is an endogenous inexhaustible algogen responsible for maintaining the chronicity of HIV-PAIN?In the present study, we isolated circulating small extracellular vesicles (sEV) from mice using our mHIV-PAIN model that is i.t. injected with gp120. We refer to such sEV as gp120-sEV herein. We observed that gp120 is absent in gp120-sEV. Following transfusion of gp120-sEV intrathecally, naïve recipient mice exhibit an extensive pain phenotype, including cold pain tested with we newly invented dry ice vapor cold test. RNA-sequence analysis suggests that gp120-sEVs induced expression of genes related to nociception and neuroinflammation pathways. These findings provide direct evidence that circulating sEV function as endogenous long-term “dynamic” algogens that enhance initial pain and extend the chronification of HIV-PAIN in mice, suggesting that chronic HIV-PAIN requires an exogenous algogen (gp120) paired with endogenous algogen (gp120-sEV), and that these components work synchronically to initiate and extend pain chronification. This double algogen concept provides a new insight into the pathogenesis of HIV-PAIN chronification. Our new mechanistic understanding will also assist in identifying new therapeutics to alleviate HIV-PAIN by targeting pathological gp120-sEV.
SynSeg: Generating Synthetic Datasets for Accurate Subcellular Segmentation with U-net
Authors: Guo Zhengyang , Xu Kaiming , Wang Zi , Ke Jingyi , Huang Jingwen , Ye Yuqi , Ou Guangshuo 
Published: February 2025

AbstractAccurate segmentation of subcellular components is crucial for understanding cellular processes, but traditional methods struggle with noise and complex structures. Convolutional neural networks improve accuracy but require large, time-consuming, and biased manually annotated datasets. Here, we developed SynSeg, a pipeline that generates synthetic training data to train a U-net model for subcellular structure segmentation, eliminating the need for manual annotation. SynSeg leverages synthetic datasets with variations in intensity, morphology, and signal distribution to deliver context-aware segmentations, even in challenging imaging conditions. We demonstrate SynSeg’s superior performance in segmenting vesicles and cytoskeletal filaments from culture cells and liveC. elegans, outperforming traditional methods such as Otsu’s thresholding, ILEE, and FilamentSensor 2.0. Additionally, SynSeg effectively quantified disease-associated microtubule morphology in live cells, uncovering structural defects caused by mutant Tau proteins linked to neurodegenerative diseases. These results highlight the potential of synthetic data-driven approaches to advance biological segmentation and enhance microscopy techniques.Significance StatementThis study introduces a novel approach for accurately segmenting cellular structures, such as microtubules and vesicles, using synthetic datasets and advanced deep learning techniques. By leveraging a U-Net model trained on thousands of artificially generated images, our method eliminates the need for labor-intensive experimental data and simplifies the data creation process. Importantly, it incorporates noise and variability into the training datasets to make the model more robust and biologically relevant.Our findings demonstrate that the model can successfully identify cellular components, paving the way for its application in real-world microscopy images. This innovation has the potential to accelerate discoveries in cell biology by providing an efficient, scalable tool for analyzing complex cellular structures, even in challenging imaging conditions.
Machine learning of molecular dynamics simulations provides insights into modulation of viral capsid assembly
Authors: Pavlova Anna , Fan Zixing , Lynch Diane L. , Gumbart James C. 
Published: February 2025

AbstractAn effective approach in the development of novel antivirals is to target the assembly of viral capsids using capsid assembly modulators (CAMs). CAMs targeting hepatitis B virus (HBV) have two major modes of function: they can either accelerate nucleocapsid assembly, retaining its structure, or misdirect it into non-capsid-like particles. Previous molecular dynamics (MD) simulations of early capsid-assembly intermediates showed differences in protein conformations for apo and bound states. Here, we have developed and tested several classification machine learning (ML) models to better distinguish between apo-tetramer intermediates and those bound to accelerating or misdirecting CAMs. Models based on tertiary structural properties of the Cp149 tetramers and their inter-dimer orientation, as well as models based on direct and inverse contact distances between protein residues, were tested. All models distinguished the apo states and the two CAM-bound states with high accuracy. Furthermore, tertiary structure models and residue-distance models highlighted different tetramer regions as important for classification. Both models can be used to better understand structural transitions that govern the assembly of nucleocapsids and to assist the development of more potent CAMs. Finally, we demonstrate the utility of classification ML methods in comparing MD trajectories and describe our ML approaches, which can be extended to other systems of interest.TOC Graphic
Structome-TM: Complementing dataset assembly for structural phylogenetics by addressing size-based biases
Authors: Malik Ashar J. , Ascher David B. 
Published: February 2025

AbstractThe increasing availability of protein structures presents new opportunities for detecting homologous proteins. While global alignment methods are widely used and generally effective, they often struggle to identify related structures obscured by differences in protein size and domain architecture. To address this limitation, we introduce Structome-TM, a web server for protein structure comparison and phylogenetic analysis using TM-score as a metric. By emphasizing local structural alignments, Structome-TM improves the detection of homologous proteins that global methods might overlook. With a user-friendly interface and efficient pairwise comparisons, Structome-TM expands the structural neighbourhood landscape and facilitates phylogenetic reconstruction.Availability and implementationThe Structome-TM web server is available athttps://biosig.lab.uq.edu.au/structometm/