bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural Language Processing-like Deep Learning Aided in Identification and Validation of Thiosulfinate Tolerance Clusters in Diverse Bacteria
Authors: Myers Brendon K. , Lamichhane Anuj , Kvitko Brian H. , Dutta Bhabesh 
Published: September 2024

AbstractAllicin tolerance (alt) clusters in phytopathogenic bacteria, which provide resistance to thiosulfinates like allicin, are challenging to find using conventional approaches due to their varied architecture and the paradox of being vertically maintained within genera despite likely being horizontally transferred. This results in significant sequential diversity that further complicates their identification. Natural language processing (NLP) - like techniques, such as those used in DeepBGC, offers a promising solution by treating gene clusters like a language, allowing for identifying and collecting gene clusters based on patterns and relationships within the sequences. We curated and validatedalt-like clusters inPantoea ananatis97-1R (PA),Burkholderia gladiolipv.gladioliFDAARGOS 389 (BG), andPseudomonas syringaepv. tomato DC3000 –(PTO). Leveraging sequences from the RefSeq bacterial database, we conducted comparative analyses of gene synteny, gene/protein sequences, protein structures, and predicted protein interactions. This approach enabled the discovery of several novelalt-like clusters previously undetectable by other methods, which were further validated experimentally. Our work highlights the effectiveness of NLP-like techniques for identifying underrepresented gene clusters and expands our understanding of the diversity and utility ofalt-like clusters in diverse bacterial genera. This work demonstrates the potential of these techniques to simplify the identification process and enhance the applicability of biological data in real-world scenarios.Significance StatementThiosulfinates, like allicin, are potent antifeedants and antimicrobials produced byAlliumspecies and pose a challenge for phytopathogenic bacteria. Phytopathogenic bacteria have been shown to utilize an allicin tolerance (alt) gene cluster to circumvent this host response, leading to economically significant yield losses. Due to the complexity of mining these clusters, we applied techniques akin to natural language processing to analyze Pfam domains and gene proximity. This approach led to the identification of novelalt-like gene clusters, showcasing the potential of artificial intelligence to reveal elusive and underrepresented genetic clusters and enhance our understanding of their diversity and role across various bacterial genera.
Predicting the effect of non-coding mutations on single-cell DNA methylation using deep learning
Authors: Liu Zhe , Gu An , Bao Yihang , Lin Guan Ning 
Published: September 2024

AbstractPredicting the effects of non-coding mutations on DNA methylation is crucial for advancing our understanding of gene expression, epigenetic inheritance, and its role in disease mechanisms. Current methods lack the capability to predict the impact of non-coding mutations on DNA methylation at single-cell resolution and long range, while remain challenges in tracking SNP influences throughout disease progression. Here, we introduce Methven, a deep learning-based framework designed to predict the effects of non-coding mutations on DNA methylation at single-cell resolution, to overcome the challenges. Methven integrates DNA sequences and ATAC-seq data, employing a divide-and-conquer approach to handle varying scales of SNP-CpG interactions. By leveraging a pretrained DNA language model, Methven accurately predicts both the direction and magnitude of methylation changes across a 100kbp range with a lightweight architecture. The evaluation results demonstrate the superior performance of Methven in prioritizing functional non-coding mutation, model interpretability, and its potential for revealing personalized mutation-disease associations.
Gradients of Recognition Molecules Shape Synaptic Specificity of Visuomotor Transformation
Authors: Dombrovski Mark , Zang Yixin , Frighetto Giovanni , Vaccari Andrea , Jang Hyojong , Mirshahidi Parmis S. , Xie Fangming , Sanfilippo Piero , Hina Bryce W. , Rehan Aadil , Hussein Roni H. , Mirshahidi Pegah S. , Lee Catherine , Morris Aileen , Frye Mark A. , von Reyn Catherine R. , Kurmangaliyev Yerbol Z. , Card Gwyneth M. , Zipursky S. Lawrence 
Published: September 2024

AbstractConverting sensory information into motor commands is fundamental to most of our actions1,2. InDrosophila, visuomotor transformations are mediated by Visual Projection Neurons (VPNs)3,4. These neurons encode object location and motion to drive directional behaviors through a synaptic gradient mechanism5. However, the molecular origins of such graded connectivity remain unknown. We addressed this question in a VPN cell type called LPLC26, which integrates looming motion and transforms it into an escape response through two separate dorsoventral synaptic gradients at its inputs and outputs. We identified two corresponding dorsoventral expression gradients of cell recognition molecules within the LPLC2 population that regulate this synaptic connectivity. Dpr13 determines synaptic outputs of LPLC2 axons by interacting with its binding partner, DIP-ε, expressed in the Giant Fiber – a neuron that mediates escape7. Similarly, Beat-VI regulates synaptic inputs onto LPLC2 dendrites by interacting with Side-II expressed in upstream motion-detecting neurons. Behavioral, physiological, and molecular experiments demonstrate that these coordinated molecular gradients regulate synaptic connectivity, enabling the accurate transformation of visual features into motor commands. As continuous variation in gene expression within a neuronal type is also observed in the mammalian brain8, graded expression of cell recognition molecules may represent a common mechanism underlying synaptic specificity.
Surface-Based vs. Voxel-Based Finite Element Head Models: Comparative Analyses of Strain Responses
Authors: Zhou Zhou , Li Xiaogai , Kleiven Svein 
Published: September 2024

AbstractFinite element (FE) models of the human head are important injury assessment tools but developing a high-quality, hexahedral-meshed FE head model without compromising geometric accuracy is a challenging task. Important brain features, such as the cortical folds and ventricles, were captured only in a handful of FE head models that were primarily developed from two meshing techniques, i.e., surface-based meshing with conforming elements to capture the interfacial boundaries and voxel-based meshing by converting the segmented voxels into elements with and without mesh smoothing. Despite these advancements, little knowledge existed of how similar the strain responses were between surface- and voxel-based FE head models. This study uniquely addressed this gap by presenting three anatomically detailed models - a surface-based model with conforming meshes to capture the cortical folds-subarachnoid cerebrospinal fluid and brain-ventricle interfaces, and two voxel-based models (with and without mesh smoothing) - derived from the same imaging dataset. These three models were employed to simulate head impacts. The results showed that, when calculating commonly used injury metrics, including the percentile strains below the maximum (e.g., 99 percentile strain) and the volume of brain element with the strain over certain thresholds, the responses of the three models were virtually identical. Different strain patterns existed between the surface- and the voxel-based models at the interfacial boundary (e.g., sulci and gyri in the cortex, regions adjacent to the falx and tentorium) with strain differences exceeding 0.1, but remarkable similarities were noted at the non-interfacial region. The mesh smoothing procedure marginally reduced the strain discrepancies between the voxel- and surface-based model. This study yielded new quantitative insights into the general similarity in the strain responses between the surface- and voxel-based FE head models and underscored that caution should be exercised when using the strain at the interface to predict injury.
Mitochondrial Hyperactivity and Reactive Oxygen Species Drive Innate Immunity to the Yellow Fever Virus-17D Live-Attenuated Vaccine
Authors: Muccilli Samantha G. , Schwarz Benjamin , Jessop Forrest , Shannon Jeffrey G. , Bohrnsen Eric , Shue Byron , Hong Seon-Hui , Hsu Thomas , Ashbrook Alison W. , Guarnieri Joseph W. , Lack Justin , Wallace Douglas C. , Bosio Catharine M. , MacDonald Margaret R. , Rice Charles M. , Yewdell Jonathan W. , Best Sonja M. 
Published: September 2024

SummaryThe yellow fever virus 17D (YFV-17D) live attenuated vaccine is considered one of the successful vaccines ever generated associated with high antiviral immunity, yet the signaling mechanisms that drive the response in infected cells are not understood. Here, we provide a molecular understanding of how metabolic stress and innate immune responses are linked to drive type I IFN expression in response to YFV-17D infection. Comparison of YFV-17D replication with its parental virus, YFV-Asibi, and a related dengue virus revealed that IFN expression requires RIG-I-like Receptor signaling through MAVS, as expected. However, YFV-17D uniquely induces mitochondrial respiration and major metabolic perturbations, including hyperactivation of electron transport to fuel ATP synthase. Mitochondrial hyperactivity generates reactive oxygen species (mROS) and peroxynitrite, blocking of which abrogated IFN expression in non-immune cells without reducing YFV-17D replication. Scavenging ROS in YFV-17D-infected human dendritic cells increased cell viability yet globally prevented expression of IFN signaling pathways. Thus, adaptation of YFV-17D for high growth uniquely imparts mitochondrial hyperactivity generating mROS and peroxynitrite as the critical messengers that convert a blunted IFN response into maximal activation of innate immunity essential for vaccine effectiveness.
Harmonizing terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) with multiplexed iterative immunofluorescence enriches spatial contextualization of cell death
Authors: Sherman Marc S , McMahon-Skates Thomas , Gaston Lindsey S. , Majzoub Joseph A , Goessling Wolfram 
Published: September 2024

AbstractTerminal deoxynucleotidyl transferase dUTP Nick End Labeling (TUNEL) is an essential tool for the detection of cell death in tissues. Although TUNEL is not known to be compatible with multiplexed spatial proteomic methods, harmonizing TUNEL with such methods offers the opportunity to delineate cell-type specific cell death labeling and precise spatial contextualization of cell death in complex tissues. Here we evaluated variations of the TUNEL assay for their compatibility with a multiplexed immunofluorescence method, multiple iterative labeling by antibody neodeposition (MILAN), in two different tissues and injury models for cell death, acetaminophen-induced hepatocyte necrosis and dexamethasone-induced adrenocortical apoptosis. Using a commercial Click-iT-based assay as a standard, TUNEL signal could be reliably produced independent of antigen-retrieval method, with tissue-specific minor differences in signal-to-noise. In contrast, proteinase K treatment consistently reduced or even abrogated protein antigenicity, while pressure cooker treatment consistently enhanced protein antigenicity for the targets tested. Antibody-based TUNEL protocols using pressure-cooker antigen retrieval were MILAN erasure-compatible thus enabling harmonization of TUNEL with MILAN. As many as four staining cycles could be performed without loss of subsequent TUNEL signal, while first-round TUNEL did not influence protein antigenicity in subsequent rounds. We conclude this harmonized assay performs comparably to an established commercial assay, but preserves protein antigenicity, thus enabling versatile integration with multiplexed immunofluorescence using MILAN. We anticipate this harmonized protocol will enable broad and flexible integration of TUNEL into multiplexed spatial proteomic assays, thus vastly enhancing the spatial contextualization of cell death in complex tissues.
Differential Effectiveness of Poloxamer 188 in Dystrophic Cardiomyopathy Reveals Complex Pathophysiology
Authors: Stevens Jackie , Banyard F. Parker , Millner Balagtas Danielle , Williams Derek , Townsend DeWayne 
Published: September 2024

AbstractSynthetic membrane stabilizers, such as poloxamer 188 (P188), have great promise in the treatment of Duchenne muscular dystrophy and other diseases associated with disrupted membranes. The aim of this study was to assess the efficacy of P188 to limit myocardial damage in models of muscular dystrophy subjected to highly injurious stress. These studies use male and female mdx and β-sarcoglycan null (β-SG-/-) mice subjected to an isoproterenol stress protocol in the presence or absence of P188. We show that P188 provides a significant level of protection to male mdx hearts from the isoproterenol induced injury. Surprisingly, we find that P188 has no protective actions in female mdx mice or in β-SG-/-mice of either sex. These results suggest that the mechanism of action of P188 is more complicated than previously thought. The presence of sex differences in the absence of dystrophin is not consistent with a model of P188 working by biophysical restoration of membrane integrity. Furthermore, the absence of protective effects of P188 in β-SG-/-myocardium indicates that there are important differences in the mechanisms of membrane damage in hearts lacking dystrophin and hearts lacking the sarcoglycan complex. Developing a better understanding of these differences will be important in the development of therapies for dystrophic cardiomyopathy and other forms of heart disease.
Limited O-specific polysaccharide (OSP)-specific functional antibody responses in young children with Shigella infection in Bangladesh
Authors: Bernshtein Biana , Zhiteneva Julia A. , Janardhanan Jeshina , Wagh Chanchal , Kelly Meagan , Verma Smriti , Jung Wonyeong , Basher Salima Raiyan , Amin Mohammad Ashraful , Mahamud Shakil , Rajib Nazmul Hasan , Chowdhury Fahima , Khan Ashraful Islam , Charles Richelle C. , Xu Peng , Kováč Pavol , Chakraborty Subhra , Kaminski Robert W. , Alter Galit , Bhuiyan Taufiqur R. , Qadri Firdausi , Ryan Edward T. 
Published: September 2024

AbstractShigellosis is the second leading cause of diarrheal death in children younger than five years of age globally. At present, there is no broadly licensed vaccine against shigella infection. Previous vaccine candidates have failed at providing protection for young children in endemic settings. Improved understanding of correlates of protection against Shigella infection and severe shigellosis in young children living in endemic settings is needed. Here, we applied a functional antibody profiling approach to define Shigella-specific antibody responses in young children versus older individuals with culture-confirmed shigellosis in Bangladesh, a Shigella endemic area. We analyzed Shigella-specific antibody isotypes, FcR binding and antibody-mediated innate immune cell activation in longitudinal serum samples collected at clinical presentation and up to 1 year later. We found that higher initial Shigella O-specific polysaccharide (OSP)-specific and protein-specific IgG and FcγR binding levels correlated with less severe disease regardless of patient age, but that individuals under 5 years of age developed a less prominent class switched, FcR-binding, functional and durable antibody response against both OSP and protein Shigella antigens than older individuals. Focusing on the largest cohort, we found that functionalS. flexneri2a OSP-specific responses were significantly induced only in individuals over age 5 years, and that these responses promoted monocyte phagocytosis and activation. Our findings suggest that in a Shigella endemic region, young children with shigellosis harbor a functional antibody response that fails to maximally activate monocytes; such a response may be important in facilitating subsequent innate cell clearance of Shigella, especially via recruitment and activation of polymorphonuclear cells capable of directly killing Shigella.
Direct contact of bacterial surface induces phase separation of the host phagosome membrane
Authors: Bhausaheb Aher Jayesh , Aniruddha N , Koiri Debraj , Shaikh Jafarulla , Choubey Sandeep , Saleem Mohammed 
Published: September 2024

AbstractPathogenic bacteria evade host defense by rupturing the phagosomal compartment, enabling their escape into the host cytosol. The bacteria is known to establish direct physical contact with the host compartment prior to phagosome disruption. However, the impact of direct-physical contact on the phagosome remodeling and deformation remains elusive. To probe this, we first developed a method wherein we reconstitute a phagosome-like giant compartment encapsulatingMycobacterium smegmatis, a non-motile opportunistic bacterium. We discover that the direct contact between the bacteria and the encapsulating host membrane induces membrane bending, lipid wrapping, and local lipid phase separation at the contact site. The degree of phase separation is driven by the bacterial load leading to fluidization of the membrane, as evident from the decreased area stretch and bending modulus, making the host compartment more deformable. Surprisingly, for saturating bacterial load the fluid host membrane transforms into a scaffold-like rigid layer. We also find that the direct contact of the bacteria enhances the membranolytic potential of ESAT-6 thus contributing to its virulence. Together our findings provide mechanistic insights into the role of direct physical contact of the bacteria during phagosome disruption.
Structural stability determines evolutionary stability in mutualistic model ecosystems
Authors: Lurgi Miguel , Pascual-García Alberto 
Published: September 2024

AbstractUnderstanding the factors that influence the persistence and stability of complex ecological networks is a central focus of ecological research. Recent research into these factors has predominantly attempted to unveil the ecological processes and structural constraints that influence network stability. Comparatively little attention has been given to the consequences of evolutionary events, despite the fact that the interplay between ecology and evolution has been recognised as fundamental to understand the formation of ecological communities and predict their reaction to change. In light of current environmental challenges, there is a compelling need for a quantitative framework to predict biodiversity loss under environmental perturbations while accounting for evolutionary processes.We extend existing mutualistic population dynamical models by incorporating evolutionary adaptation events to address this critical gap. We relate ecological aspects of mutualistic community stability to the stability of persistent evolutionary pathways. Our findings highlight the significance of the structural stability of ecological systems in predicting biodiversity loss under both evolutionary and environmental changes, particularly in relation to species-level selection. Notably, our simulations reveal that the evolution of mutualistic networks tends to increase a network-dependent parameter termed critical competition, which places systems in a regime in which mutualistic interactions enhance structural stability and, consequently, biodiversity.This research emphasizes the pivotal role of natural selection in shaping ecological networks, steering them towards reduced effective competition below a critical threshold where mutualistic interactions foster stability. The outcomes of our study contribute to the development of a predictive framework for eco-evolutionary dynamics, offering insights into the interplay between ecological and evolutionary processes in the face of environmental change.
How can interspecific pollen transfer affect the coevolution and coexistence of two closely related plant species?
Authors: Morita Keiichi , Sasaki Akira , Iritani Ryosuke 
Published: September 2024

AbstractInterspecific pollen transfer (IPT), the movement of pollen grains between different plant species by sharing pollinators, incurs costs (fitness reduction) for seed production. IPT thereby reduces the reproductive success of co-flowering plants sharing pollinators, thus preventing their coexistence. However, the impact of IPT on the evolutionary dynamics and evolution-mediated ecological dynamics of sex allocation resource investment to pollen versus ovules) is poorly understood. Here, we investigate the consequences of the female costs incurred by IPT for the co-evolution and coexistence of two plants, by using a mathematical model where two plant species interact with each other via resource competition, pollen movements within and between species, and reduced fertilization due to IPT. The ecological situation we consider here is that an invasive species with female-biased sex allocation immigrates into a habitat of a resident species whose sex allocation is evolutionarily maintained at Fisherian sex allocation (FSA). By using adaptive dynamics theory, we found that regardless of the strength of IPT, natural selection favours the equal allocation to pollen grains and ovules (FSA) for both species. If the mutual impact of IPT on two species is similar in magnitude, we find that the eco-evolutionary dynamics can lead to their stable coexistence. In contrast, when only the invasive species negatively impacts the resident species through IPT, the evolution in invasive species from female-biased sex allocation to FSA causes the extinction of the resident species. Given that local mate competition in small populations is expected to result in female-based sex allocation, our finding suggests that if invasive species are relaxed from local mate competition, they may drive the resident species to extinction. Our study highlights the importance and complexity of the evolution of biased sex allocation driven by IPT to understand the coexistence of closely related plant species.
Sarcolemmal and mitochondrial membrane potentials measuredex vivoandin vivoin the heart by pharmacokinetic modelling of [99mTc]sestamibi
Authors: Waters Edward CT. , Baark Friedrich , Orton Matthew R. , Shattock Michael J. , Southworth Richard , Eykyn Thomas R. 
Published: September 2024

AbstractWe present a compartmental modelling approach to analyse radioactive time activity curves for first pass kinetics of [99mTc]sestamibi in the heart. Reparametrizing the kinetic equations using the Nernst membrane-potential equation provides a novel means of non-invasively estimating the sarcolemmal (Em) and mitochondrial (ΔΨm) membrane potentials in the heart. A Markov Chain Monte Carlo (MCMC) fitting approach was applied to data derived from established interventions in Langendorff perfused rat hearts where the sarcolemmal membrane was depolarised using hyperkalaemic Krebs Henseleit buffers; the mitochondrial membrane was depolarised using carbonylcyanide-3-chlorophenylhydrazone (CCCP); or both membranes were depolarised using their combination. Translating this approach to single photon emission planar scintigraphy kinetics from healthy rats allowed an estimate of these membrane potentials (voltages)in vivofor the first time; the values wereEm= –62 ± 5 mV and ΔΨm= –151 ± 5 mV (n = 4, mean ± SD).