bluuebunny/crossref_metadata_2025_split huggingface dataset:
The trichothecene mycotoxin deoxynivalenol facilitates cell-to-cell invasion during wheat-tissue colonisation byFusarium graminearum
Authors: Armer Victoria , Urban Martin , Ashfield Tom , Deeks Michael J. , Hammond-Kosack Kim E. 
Published: December 2023

AbstractFusarium Head Blight (FHB) disease on small grain cereals is primarily caused by the ascomycete fungal pathogenFusarium graminearum.Infection of floral spike tissues is characterised by the biosynthesis and secretion of potent trichothecene mycotoxins, of which deoxynivalenol (DON) is widely reported due to its negative impacts on grain quality and consumer safety. TheTRI5gene encodes an essential enzyme in the DON biosynthesis pathway and the single gene deletion mutant,ΔTri5, is widely reported to restrict disease progression to the inoculated spikelet. In this study, we present novel bioimaging evidence revealing that DON facilitates the traversal of the cell wall through plasmodesmata, a process essential for successful colonisation of host tissue. Chemical complementation ofΔTri5did not restore macro- or microscopic phenotypes, indicating that DON secretion is tightly regulated both spatially and temporally. A comparative qualitative and quantitative morphological cellular analysis revealed infections had no impact on plant cell wall thickness. Immuno- labelling of callose at plasmodesmata during infection indicates that DON can increase deposits when applied exogenously, but is reduced whenF. graminearumhyphae are present. This study highlights the complexity of the inter-connected roles of mycotoxin production, cell wall architecture and plasmodesmata in this highly specialised interaction.
Enhancing Recognition and Interpretation of Functional Phenotypic Sequences through Fine-Tuning Pre-Trained Genomic Models
Authors: Du Duo , Zhong Fan , Liu Lei 
Published: December 2023

AbstractDecoding high-quality human genomic sequences requires comprehensive analysis of DNA sequence functionality. Through computational and experimental approaches, researchers study the genotype-phenotype relationship and generate important datasets that help unravel complicated genetic blueprints. This study explores the use of deep learning, particularly pre-trained models like DNA_bert_6 and human_gpt2-v1, in interpreting and representing human genome sequences. We meticulously construct multiple datasets linking genotypes and phenotypes to fine-tune pre-trained models for precise DNA sequence classification. Furthermore, we specifically focused on the human endogenous retrovirus (HERV) dataset with commendable classification performance (both binary and multi-classification accuracy and F1 values above 0.935 and 0.888, respectively). We evaluate the influence of sequence length on classification results and analyze the impact of feature extraction in the model’s hidden layers using the HERV dataset. To further understand the phenotype-specific patterns learned by the model, we perform enrichment, pathogenicity and conservation analyzes of specific motifs in the HERV sequence with high average local representation weight (LRAW) scores. Overall, the generated datasets further provide numerous additional genotype-phenotype datasets for evaluating the performance of genomic models. The findings highlight the potential of large models in learning DNA sequence representations, particularly when utilizing the HERV dataset, and provide valuable insights for future research. This work represents an innovative strategy that combines pre-trained model representations with classical omics methods for analyzing the functionality of genome sequences, fostering cross-fertilization between genomics and advanced AI. The source code and data are available athttps://github.com/GeorgeBGM/Genome_Fine-Tuning.
Consensus scHPF Identifies Cell Type-Specific Drug Responses in Glioma by Integrating Large-Scale scRNA-seq
Authors: Levitin Hanna Mendes , Zhao Wenting , Bruce Jeffrey N. , Canoll Peter , Sims Peter A. 
Published: December 2023

AbstractSingle-cell transcriptomic analyses now frequently involve elaborate study designs including samples from multiple individuals, experimental conditions, perturbations, and batches from complex tissues. Dimensionality reduction is required to facilitate integration, interpretation, and statistical analysis. However, these datasets often include subtly different cellular subpopulations or state transitions, which are poorly described by clustering. We previously reported a Bayesian matrix factorization algorithm called single-cell hierarchical Poisson factorization (scHPF) that identifies gene co-expression patterns directly from single-cell RNA-seq (scRNA-seq) count matrices while accounting for transcript drop-out and noise. Here, we describe consensus scHPF, which analyzes scHPF models from multiple random initializations to identify the most robust gene signatures and automatically determine the number of factors for a given dataset. Consensus scHPF facilitates integration of complex datasets with highly multi-modal posterior distributions, resulting in factors that can be uniformly analyzed across individuals and conditions. To demonstrate the utility of consensus scHPF, we performed a meta-analysis of a large-scale scRNA-seq dataset from drug-treated, human glioma slice cultures generated from surgical specimens across three major cell types, 19 patients, 10 drug treatment conditions, and 52 samples. In addition to recapitulating previously reported cell type-specific drug responses from smaller studies, consensus scHPF identified disparate effects of the topoisomerase poisons etoposide and topotecan that are highly consistent with the distinct roles and expression patterns of their respective protein targets.
Genomic location dictates lytic promoter activity during herpes simplex virus latency
Authors: Singh Navneet , Zachariah Sherin , Phillips Aaron T. , Tscharke David 
Published: December 2023

AbstractHerpes simplex virus 1 (HSV-1) is a significant pathogen that establishes life-long latent infections with intermittent episodes of resumed disease. In mouse models of HSV infection, persistent low-level lytic gene expression has been detected during latency in the absence of spontaneous reactivation events leading to new virus production. This viral activity during latency has been reported using a sensitive Cre-marking model for several lytic gene promoters placed in one location in the HSV-1 genome. Here we extend these findings in the same model by examining first, the activity of an ectopic lytic gene promoter in other places in the genome and second, whether native promoter activity might be detectable. We found that both for ectopic and native lytic gene promoters,Creexpression during latency was detected in our model, but only when the promoter was located near the ends of the unique long genome segment. This location is significant because it is in close proximity to the region from which latency associated transcripts (LAT) are derived. These results show for the first time that native HSV-1 lytic gene promoters can produce protein products during latency, but that this activity is only detectable when they are located close to the LAT locus.Author summaryHSV is a significant human pathogen and the best studied model of mammalian virus latency. Traditionally the active (lytic) and inactive (latent) phases of infection were considered to be distinct, but the notion of latency being entirely quiescent is evolving due to the detection of some lytic gene expression during latency. Here we add to this literature by finding that activity can be found for native lytic gene promotors as well as for constructs placed ectopically in the HSV genome. However, this activity was only detectable when these promoters were located close by a region known to be transcriptionally active during latency. These data have implications for our understanding of HSV gene regulation during latency and the extent to which transcriptionally active regions are insulated from adjacent parts of the viral genome.
Molecular determinants of SEC61A1 mutant R236C in two patient-derived cellular platforms
Authors: Weiand Matthias , Sandfort Vanessa , Nadzemova Oksana , Schierwagen Robert , Trebicka Jonel , Kabar Iyad , Schmidt Hartmut , Zibert Andree 
Published: December 2023

AbstractBackground & objectivesSEC61A1 encodes a central protein of the mammalian translocon machinery residing in the ER. Mutations ofSEC61A1are implicated to result in various severe diseases. Recently, mutation R236C was identified in patients having autosomal dominant polycystic liver disease (ADPLD), which originates from defects of cholangiocytes in the liver. The molecular phenotype of R236C was assessed.MethodsTwo cellular platforms were established from the same cell source of an ADPLD patient by different methodology. Cells were immortalized by retroviral transduction of an oncogene (UCi) or reprogrammed to induced pluripotent stem cells (iPSC) that were differentiated to cholangiocyte progenitor-like cells (CPLC). UCi and CPLC were subjected to several analyses of molecular pathways that were previously associated with development of polycystic disease.ResultsUCi displayed markers of epithelial cells, while CPLCs expressed typical markers of both cholangiocytes and hepatocytes. Cells encoding R236C showed a stable, continuous proliferation in both platforms, however growth rates were reduced as compared to wildtype control. Autophagy, cAMP synthesis, and secretion of important marker proteins were reduced in R236C-expressing cells. In addition, R236C induced increased calcium leakiness from the ER to the cytoplasm. Upon oxidative stress, R236C led to a high induction of apoptosis and necrosis.ConclusionAlthough the grade of aberrant cellular functions differed between the two platforms, overall the molecular phenotype of R236C was shared suggesting that the mutation, regardless of the cell type, has a dominant impact on disease-associated pathways that cause ADPLD. Our approach may be valuable to decipher the molecular pathways of other rare genetic diseases using patient-specific cell models.
Spike synchrony as a measure of Gestalt structure
Authors: Zemliak Viktoria , Mayer Julius , Nieters Pascal , Pipa Gordon 
Published: December 2023

AbstractThe function of spike synchrony has long been debated in the neuroscience community. Some researchers view synchrony as a byproduct of brain activity, while others argue that it serves as a mechanism for binding perceptual features. We, however, argue for an alternative view on the computational role of synchrony: it can serve as a mechanism for estimating the prior probability of incoming stimuli. In V1, this probability can be estimated by comparing the input stimulus with previously acquired visual experience. Such experience is encoded in horizontal intracortical connections, as they are subject to change, learn, and adapt to incoming visual stimuli throughout the course of life. Thus, the V1 connectivity structure can encode the acquired visual experience in the form of its aggregate statistics. Since the aggregate statistics of natural images tend to follow the Gestalt principles, we can assume that V1 is more often exposed to Gestalt-like stimuli, and this is manifested in its connectivity structure. At the same time, the connectivity structure has an impact on the synchrony of neuronal firings in V1. In our work, we used a spiking model with V1-like connectivity to demonstrate that spike synchrony reflects the Gestalt structure of the stimulus. We conducted simulation experiments with three Gestalt laws: proximity, similarity, and continuity, and found significant differences in firing synchrony for stimuli with varying degrees of Gestalt-likeness. This allows us to conclude that spike synchrony indeed reflects the Gestalt structure of the stimulus, which can be interpreted as a mechanism for prior probability estimation.Author SummaryNeurons in the brain fire synchronously in different contexts, in response to different stimuli. However, the function of synchrony is very debatable in the neuroscience community. We suggest that synchrony plays an important role in brain computations: it can estimate how well a network is familiar with the incoming stimulus. We tested our hypothesis on the simulation of neuronal activity in a model of primary visual cortex - a brain region which is processing simple visual features, such as lines of different angle orientation. The connections between neurons in this brain area store the acquired visual experience in the form of its statistics, such as edge cooccurrences. We built the connectivity in our model in accordance with principles of connectivity in primary visual cortex, assuming that it reflects natural images statistics. We tested our model on artificial stimuli, which represented more and less experienced visual features. Our results showed that spike synchrony is a global phenomenon which emerges across the large parts of the network, and it reflects the familiarity of the network with the stimulus. Thus, it can serve as a form of recognition memory and has a potential for usage in various applications which require estimation of input familiarity.
Neuronal avalanches in temporal lobe epilepsy as a diagnostic tool: a noninvasive investigation of intrinsic resting state dynamics
Authors: Corsi Marie-Constance , Lopez Emahnuel Troisi , Sorrentino Pierpaolo , Danieli Alberto , Cuozzo Simone , Bonanni Palo , Duma Gian Marco 
Published: December 2023

AbstractBackground and ObjectivesThe epilepsy diagnosis still represents a complex process, with misdiagnosis reaching 40%. Here, we aimed at building an automatable workflow, to help the clinicians in the diagnostic process, differentiating between controls and a population of patients with temporal lobe epilepsy (TLE). While primarily interested in correctly classifying the participants, we used data features providing hints on the underlying pathophysiological processes. Specifically, we hypothesized that neuronal avalanches (NA) may represent a feature that encapsulates the rich brain dynamics better than the classically used functional connectivity measures (Imaginary Coherence; ImCoh).MethodsWe recorded 10 minutes of resting state activity with high-density scalp electroencephalography (hdEEG; 128 channels). We analyzed large-scale activation bursts (NA) from source activation, to capture altered dynamics. Then, we used machine-learning algorithms to classify epilepsy patients vs. controls, and we described the goodness of the classification as well as the effect of the durations of the data segments on the performance.ResultsUsing a support vector machine (SVM), we reached a classification accuracy of 0.87 ± 0.10 (SD) and an area under the curve (AUC) of 0.94 ± 0.06. The use of avalanches-derived features, generated a mean increase of 16% in the accuracy of diagnosis prediction, compared to ImCoh. Investigating the main features informing the model, we observed that the dynamics of the entorhinal cortex, superior and inferior temporal gyri, cingulate cortex and prefrontal dorsolateral cortex were informing the model with NA. Finally, we studied the time-dependent accuracy in the classification. While the classification performance grows with the duration of the data length, there are specific lengths, at 30s and 180s at which the classification performance becomes steady, with intermediate lengths showing greater variability. Classification accuracy reached a plateau at 5 minutes of recording.DiscussionWe showed that NA represents a better EEG feature for an automated epilepsy identification, being related with neuronal dynamics of pathology-relevant brain areas. Furthermore, the presence of specific durations and the performance plateau might be interpreted as the manifestation of the specific intrinsic neuronal timescales altered in epilepsy. The study represents a potentially automatable and noninvasive workflow aiding the clinicians in the diagnosis.
Development of a human heart-on-a-chip model using induced pluripotent stem cells, fibroblasts and endothelial cells
Authors: Liu Yun , Kamran Rumaisa , Han Xiaoxia , Wang Mengxue , Li Qiang , Lai Daoyue , Naruse Keiji , Takahashi Ken 
Published: December 2023

AbstractIn recent years, research on organ-on-a-chip technology has been flourishing, particularly for drug screening and disease model development. Fibroblasts and vascular endothelial cells engage in crosstalk through paracrine signaling and direct cell-cell contact, which is essential for the normal development and function of the heart. Therefore, to faithfully recapitulate cardiac function, it is imperative to incorporate fibroblasts and vascular endothelial cells into a heart-on-a-chip model. Here, we report the development of a human heart-on-a-chip composed of induced pluripotent stem cell (iPSC)-derived cardiomyocytes, fibroblasts, and vascular endothelial cells. Vascular endothelial cells cultured on microfluidic channels responded to the flow of culture medium mimicking blood flow by orienting themselves parallel to the flow direction, akin toin vivovascular alignment in response to blood flow. Furthermore, the flow of culture medium promoted stronger junction formation between vascular endothelial cells, as evidenced by CD31 staining and lower apparent permeability. The triculture condition of iPSC-derived cardiomyocytes, fibroblasts, and vascular endothelial cells resulted in higher expression of the ventricular cardiomyocyte marker IRX4 and increased contractility compared to the biculture condition with iPSC-derived cardiomyocytes and fibroblasts alone. Such triculture-derived cardiac tissues exhibited cardiac responses similar toin vivohearts, including an increase in heart rate upon noradrenaline administration. In summary, we have achieved the development of a heart-on-a-chip composed of cardiomyocytes, fibroblasts, and vascular endothelial cells that mimicsin vivocardiac behavior.
A fur plucking model to study herpes simplex virus reactivation and recurrent disease
Authors: Philip Drake T. , Goins Nigel M. , Lazear Helen M. 
Published: December 2023

ABSTRACTHerpes simplex viruses (HSV-1 and HSV-2) most commonly cause ulcerative epithelial lesions (cold sores, genital herpes). Importantly, HSV establishes life-long persistent (latent) infection in sensory neurons. Reactivation from latency produces recurrent epithelial lesions, which constitute the greatest burden of HSV disease in people. The mechanisms that regulate latency and reactivation remain poorly understood, in part due to limitations in the animal models available for studying HSV reactivation. We have developed a simple and tractable model to induce HSV-1 and HSV-2 reactivation from latently infected sensory ganglia. We infected C57BL/6 mice with 1 × 106FFU of HSV-1 (strain NS) or 500 FFU of HSV-2 (strain 333) on flank skin depilated by manual plucking. 35 days post-infection (dpi) we re-plucked the fur from the infected flank and observed recurrent lesions in the same dermatome as the primary infection. We detected HSV DNA in dermatome skin through 4 days post-re-plucking. We found that shaving the ipsilateral flank or plucking the contralateral flank did not induce recurrent skin lesions, suggesting that fur plucking is a specific stimulus that induces HSV reactivation. Further, we were able to induce multiple rounds of plucking induced recurrent disease, providing a model to investigate the lifelong nature of HSV infection. This new model provides a tractable system for studying pathogenic mechanisms of and therapeutic interventions against HSV reactivation and recurrent disease.
CRISPR screens in 3D tumourspheres identified miR-4787-3p as a transcriptional start site miRNA essential for breast tumour-initiating cell growth
Authors: Stiff Tom , Bayraktar Salih , Dama Paola , Stebbing Justin , Castellano Leandro 
Published: December 2023

AbstractBreast cancer (BC) is a heterogeneous malignancy with distinct molecular subtypes and clinical characteristics. Tumour-initiating cells (TICs) are a small subset of cancer cells that are responsible for tumour initiation and progression.Our study employed pooled CRISPR screens, integrating 2D and 3D culture models, to identify miRNAs critical in BC tumorsphere formation. These screens combined with RNA-seq experiments allowed us to identify the miRNA signature and their targets that are essential for tumoursphere growth. Amongst them, miR-4787-3p exhibited significant up-regulation in BC, particularly in basal-like BCs, suggesting its association with aggressive disease phenotypes. Surprisingly, despite its location within the 5’UTR of a protein coding gene, which define DROSHA-independent transcription start site (TSS)-miRNAs, our findings revealed its dependence on both DROSHA and DICER1 for maturation. Inhibition of miR-4787-3p hindered tumorsphere formation, highlighting its potential as a therapeutic target in BC. Moreover, our study proposes elevated miR-4787-3p expression as a potential prognostic biomarker for adverse outcomes in BC patients. We found that protein-coding genes positively selected in the CRISPR screens were enriched of miR-4787-3p putative targets. Amongst these identified key targets, we selected ARHGAP17, FOXO3A, and PDCD4 because are known tumour suppressors in cancer and experimentally validated the interaction of miR-4787-3p with their 3’UTRs. Our work illuminates the molecular mechanisms underpinning miR-4787-3p’s oncogenic role in BC. These findings advocate for further clinical investigations targeting miR-4787-3p and underscore its prognostic significance, offering promising avenues for tailored therapeutic interventions and prognostic assessments in BC.
Identification of the modulatory Ca2+binding sites of acid-sensing ion channel 1a
Authors: Molton Ophélie , Bignucolo Olivier , Kellenberger Stephan 
Published: December 2023

AbstractAcid-sensing ion channels (ASICs) are neuronal H+-gated, Na+-permeable channels involved in learning, fear sensing, pain sensation and neurodegeneration. An increase in the extracellular Ca2+concentration shifts the pH dependence of ASIC1a to more acidic values. Here, we predicted candidate residues for Ca2+binding on ASIC1a, based on available structural information and molecular dynamics simulations; the function of channels carrying mutations of these residues was then measured. We identify several residues in cavities previously associated with pH-dependent gating, whose mutation decreased the Ca2+-induced shift in ASIC1a pH dependence, likely due to a disruption of Ca2+binding. We show also that Mg2+shares some of the binding sites with Ca2+, and that some of the Ca2+binding sites are functionally conserved in the splice variant ASIC1b. Our identification of divalent cation binding sites in ASIC1a shows how Ca2+affects ASIC1a gating, elucidating a regulatory mechanism present in many ion channels.
Cooperativity in RNA chemical probing experiments modulates RNA 2D structure
Authors: Arnold Ethan B , Cohn Daniel D , Bose Emma M , Wolfe Gregory , Jones Alisha N 
Published: December 2023

AbstractSmall molecule chemical probes that covalently bond atoms of flexible nucleotides are widely employed in RNA structure determination. Atomistic molecular dynamic (MD) simulations recently revealed that the binding of RNA by chemical probes is influenced by cooperative effects, leading to measured reactivities that depend on the concentration of the chemical probe. In this work, we used selective 2’ hydroxyl acylation analyzed by primer extension (SHAPE) and dimethyl sulfate (DMS) chemical probing experiments to explore whether RNA structures are modulated by chemical probe binding events. We find that as the concentration of a chemical probe increases, modified nucleotides locally modulate the RNA structure, resulting in the increase or decrease of chemical probe reactivity in surrounding nucleotides. This cooperative effect is dependent on both chemical probe concentration and size. We find that these cooperative effects can be used to link structurally related nucleotides, and that the cooperative effects result in strikingly different 2D structure predictions as probe concentrations are varied.