bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep screening of proximal and distal splicing-regulatory elements in a native sequence context
Authors: Recinos Yocelyn , Ustianenko Dmytro , Yeh Yow-Tyng , Wang Xiaojian , Jacko Martin , Yesantharao Lekha V. , Wu Qiyang , Zhang Chaolin 
Published: August 2023

ABSTRACTPre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is impeded by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically dead CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied toSMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identified not only known SREs, but also a novel distal intronic splicing enhancer, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.
Spatial patterns in the diet ofGypsvultures in India and their implications for conservation
Authors: Ghosh-Harihar Mousumi , Yadav Nidhi , Gurung Nehal , C.S. Darshan , B. Shashikumar , C.K. Vishnudas , Prakash Vibhu , Green Rhys E. , Ramakrishnan Uma 
Published: August 2023

AbstractDietary analyses are particularly useful for developing conservation programmes for species threatened by resource depletion, poisoning and environmental pollution.Gypsvultures in South Asia represent one such case, having undergone a population collapse caused by feeding on carcasses of cattle treated with the non-steroidal anti-inflammatory drug diclofenac. Following a ban on the veterinary use of diclofenac, populations of vultures remain low and mostly concentrated near protected areas. Understanding the role of protected areas in the recovery of these critically endangered species requires analyses of spatial variation in their diet. We used faecal metabarcoding to investigate the spatial variation in the diet ofGypsvultures across four landscapes from sites located inside and outside protected areas. We collected faecal 642 samples, of which 419 yielded adequate molecular data to identify the vulture species and 30 molecular operational taxonomic units corresponding to at least 28 diet species. The diet was dominated by large ungulates and varied across landscapes, protection status and vulture species, with the observed variation largely explained by differential intake of wild and domestic species. Domestic livestock was present in >95% of the samples from central, west and north India, but 77% of the samples had only wild species in south India. This variation was explained by livestock density within 100 km radius of the sampling site. Our results imply that protected areas may not offer a respite from possibility of diclofenac-poisoning across most parts of the country and efforts should continue unabated to remove nephrotoxic drugs from veterinary use.
Factorial state-space modelling for kinetic clustering and lineage inference
Authors: Gupta R. , Claassen M. 
Published: August 2023

AbstractSingle-cell RNA sequencing (scRNAseq) protocols measure the abundance of expressed transcripts for single cells. Gene expression profiles of cells (cell-states) represent the functional properties of the cell and are used to cluster cell-states that have a common functional identity (cell-type). Standard clustering methods for scRNAseq data performhardclustering based on KNN graphs. This approach implicitly assumes that variation among cell-states within a cluster does not correspond to changes in functional properties. Differentiation is a directed process of transitions between cell-types via gradual changes in cell-states over the course of the process. We propose a latent state-space Markov model that utilises cell-state transitions derived from RNA velocity to model differentiation as a sequence of latent state transitions and to performsoftkinetic clustering of cell-states that accommodates the transitional nature of cells in a differentiation process. We applied this model to the differentiation of Radial-glia cells into mature neurons and demonstrate the utility of our method in discriminating between functional and transitional cell-states.
Identification of Cholangiocarcinoma (CCA) Subtype-Specific Biomarkers
Authors: Croft Jacob , Gao Liyuan , Quintanar Odalys , Sheng Victor , Zhang Jun 
Published: August 2023

AbstractLiver cancer ranks sixth globally in diagnoses and second in cancer-related deaths. Cholangiocarcinoma (CCA), a relatively rare cancer originating from bile duct epithelium, constitutes 2% of all cancers, with increasing occurrences in Westerns. Incidence is influenced by inflammation, genetics, risk factors, and regional disparities, with higher rates in the Eastern hemisphere. Diagnostic and prognostic biomarkers are pivotal for effective cancer prevention and management. Recent research explores serum proteins for non-invasive CCA diagnosis and proposes targeted receptor approaches for therapeutics.This study aims to identify these biomarkers via bioinformatics analysis of public datasets, focusing on CCA patient transcriptomes to uncover gene biomarkers linked to age and survival. Pathway analysis reveals functions and pathways associated with these biomarkers. Additionally, the study employs the ESM-TFpredict machine learning model to predict transcription factors (TFs) using protein sequence data.Leveraging publicly available data enhances our understanding of liver cancer’s molecular profiles and clinical relevance, particularly concerning CCA, This study integrates bioinformatics analysis, transcriptomic exploration, and machine learning to unveil a novel set of potential diagnostic and prognostic biomarkers for CCA.
Drug-target interaction prediction using a multi-modal transformer network demonstrates high generalizability to unseen proteins
Authors: Kroll Alexander , Ranjan Sahasra , Lercher Martin J. 
Published: August 2023

ABSTRACTMost drugs are small molecules, with their activities typically arising from interactions with protein targets. Accurate predictions of these interactions could greatly accelerate pharmaceutical research. Current machine learning models designed for this task have a limited ability to generalize beyond the proteins used for training. This limitation is likely due to a lack of information exchange between the protein and the small molecule during the generation of the required numerical representations. Here, we introduce ProSmith, a machine learning framework that employs a multimodal Transformer Network to simultaneously process protein amino acid sequences and small molecule strings in the same input. This approach facilitates the exchange of all relevant information between the two types of molecules during the computation of their numerical representations, allowing the model to account for their structural and functional interactions. Our final model combines gradient boosting predictions based on the resulting multimodal Transformer Network with independent predictions based on separate deep learning representations of the proteins and small molecules. The resulting predictions outperform all previous models for predicting drug-target interactions, and the model demonstrates unprecedented generalization capabilities to unseen proteins. We further show that the superior performance of ProSmith is not limited to drug-target interaction predictions, but also leads to improvements in other protein-small molecule interaction prediction tasks, the prediction of Michaelis constantsKMof enzyme-substrate pairs and the identification of potential substrates for enzymes. The Python code provided can be used to easily implement and improve machine learning predictions of interactions between proteins and arbitrary drug candidates or other small molecules.
The pathogenic roles of the p.R130S prestin variant in DFNB61 hearing loss
Authors: Takahashi Satoe , Zhou Yingjie , Cheatham Mary Ann , Homma Kazuaki 
Published: August 2023

ABSTRACTDFNB61 is a recessively inherited nonsyndromic hearing loss caused by mutations inSLC26A5, the gene that encodes the voltage-driven motor protein, prestin. Prestin is abundantly expressed in the auditory outer hair cells that mediate cochlear amplification. Two DFNB61-associatedSLC26A5variants, p.W70X and p.R130S, were identified in patients who are compound heterozygous for these nonsense and missense changes (SLC26A5W70X/R130S). Our recent study showed that mice homozygous for p.R130S (Slc26a5R130S/R130S) suffer from hearing loss that is ascribed to significantly reduced motor kinetics of prestin. Given that W70X-prestin is nonfunctional, compound heterozygousSlc26a5R130S/-mice were used as a model for humanSLC26A5W70X/R130S. By examining the pathophysiological consequences of p.R130S prestin when it is the sole allele for prestin protein production, we determined that this missense change results in progressive outer hair cell loss in addition to its effects on prestin’s motor action. Thus, this study fully defines the pathogenic roles for the p.R130S prestin, which points to the presence of a limited time window for potential clinical intervention.
Relationship between reactive astrocytes, by [18F]SMBT-1 imaging, with amyloid-beta, tau, glucose metabolism, and microgliosis in mouse models of Alzheimer’s disease
Authors: Kong Yanyan , Maschio Cinzia A. , Shi Xuefeng , Yao Bolin , Xie Fang , Zuo Chuantao , Konietzko Uwe , Shi Kuangyu , Rominger Axel , Xiao Jianfei , Huang Qi , Nitsch Roger M. , Guan Yihui , Ni Ruiqing 
Published: August 2023

AbstractPurposeReactive astrocytes play an important role in the development of Alzheimer’s disease (AD). Here, we aim to investigate the temporospatial relationship between reactive astrocytes, tau and amyloid-β, glucose metabolism, and microgliosis by using multitracer imaging in AD transgenic mouse models.MethodsPositron emission tomography (PET) imaging with [18F]SMBT-1 (monoamine oxidase-B), [18F]florbetapir (Aβ), [18F]PM-PBB3 (tau), [18F]FDG, and [18F]DPA-714 (translocator protein) was carried out in 5- and 10-month-old APP/PS1, 11-month-old 3×Tg mice, and aged-matched wild-type mice. The brain regional referenced standard uptake value (SUVR) was computed with the cerebellum as the reference region. Immunofluorescence staining was performed in mouse brain tissue slices.Results[18F]SMBT-1 and [18F]florbetapir SUVRs were higher in the cortex and hippocampus of 10-month-old APP/PS1 mice than in 5-month-old APP/PS1 mice and wild-type mice. Reduced [18F]FDG SUVR was observed in the thalamus and midbrain of 5-month-old APP/PS1 mice compared to wild-type mice. No significant difference in brain regional [18F]DPA-714 SUVR was observed in 5- and 10-month-old APP/PS1 mice compared to wild- type mice. No significant difference in the SUVRs of any tracers was observed in 11-month-old 3×Tg mice compared to age-matched wild-type mice. A positive correlation between the SUVRs of [18F]SMBT-1 and [18F]DPA-714 in the cortex was observed. Immunostaining validated the distribution of MAO-B and TSPO, amyloid and tau inclusions in brain tissue from 10-month-old APP/PS1 mice and limited changes in 11-month- old 3×Tg mice.ConclusionThe findings provide in vivo evidence for reactive astrocytes along with amyloid plaque and tau deposition preceding microgliosis in animal models of AD pathologies.
Histone mark age of human tissues and cells
Authors: de Lima Camillo Lucas Paulo , Asif Muhammad Haider , Horvath Steve , Larschan Erica , Singh Ritambhara 
Published: August 2023

BackgroundAging involves intricate epigenetic changes, with histone modifications playing a pivotal role in dynamically regulating gene expression. Our research comprehensively analyzes seven key histone modifications across various tissues to understand their behavior during human aging and formulate age prediction models.ResultsThese histone-centric prediction models exhibit remarkable accuracy and resilience against experimental and artificial noise. They showcase comparable efficacy when compared with DNA methylation age predictors through simulation experiments. Intriguingly, our gene set enrichment analysis pinpoints vital developmental pathways crucial for age prediction. Unlike in DNA methylation age predictors, genes previously recognized in animal studies as integral to aging are amongst the most important features of our models. We also introduce a pan-histone-mark, pan-tissue age predictor that operates across multiple tissues and histone marks, reinforcing that age-related epigenetic markers are not restricted to particular histone modifications.ConclusionOur findings underscore the potential of histone marks in crafting robust age predictors and shed light on the intricate tapestry of epigenetic alterations in aging.
The nasopharyngeal virome in adults with acute respiratory infection
Authors: Sandybayev N.T. , Beloussov V.Yu. , Strochkov V.M. , Solomadin M.V. , Granica J. , Yegorov S. 
Published: August 2023

AbstractBackgroundRespiratory infections are a leading cause of morbidity and mortality worldwide, with a significant proportion thought to have a viral aetiology. Traditional diagnostic approaches often rely on targeted assays for “common” respiratory pathogens, leaving a substantial fraction of infections unidentified. Here, we used metagenomic next generation sequencing (mNGS) to characterize the nasopharyngeal virome associated with acute respiratory infection (ARI), with and without a positive PCR test result for a panel of common respiratory viruses.MethodsNasopharyngeal swabs from symptomatic outpatients (n=49), of whom 32 tested positive by a multiplex viral PCR, and asymptomatic controls (n=4) were characterized by mNGS. The virome taxa were stratified into human, non-human eukaryotic host, and bacteriophage sub-groups. We used a phage host classification as a proxy to establish bacterial taxa present in the nasopharynx. We then compared the virome biodiversity and presence of pathogens with known respiratory effects across the participant sub-groups.ResultsThe nasopharyngeal virome exhibited similar diversity across the PCR-positive and - negative subsets. Among the top ARI-associated human viruses were enterovirus (16.3%, human rhinovirus, HRV-A), roseolovirus (14.3%, human betaherpesvirus 7, HBV-7) and lymphocryptovirus (8.16%, Epstein-Barr virus, EBV). The top three ARI-associated phage hosts wereStreptococcusspp (32.7%),Pseudomonas aeruginosa(24.5%) andBurkholderiaspp. (20.4%). The virome of both asymptomatic and symptomatic subjects was also abundant in theStaphylococcus(60.4%) andPropionibacterium (Cutibacterium) acnesbacteriophages (90.6%). The PCR and mNGS results were relatively concordant for human rhinovirus (HRV), but not for other PCR panel targets, including human parainfluenza (HPIV), adenovirus (HAdV), bocavirus (BoV) and seasonal coronavirus (HCoV).ConclusionsmNGS revealed a high diversity of pathogens that could be cause to respiratory symptomatology, either as a single infection or a co-infection between viral and bacterial species. The clinical significance of the mNGS versus multiplex PCR findings warrants further investigation.
Near Infrared Reflectance Spectroscopy Phenomic and Genomic Prediction of Maize Agronomic and Composition Traits Across Environments
Authors: DeSalvio Aaron J. , Adak Alper , Murray Seth C. , Jarquín Diego , Winans Noah D. , Crozier Daniel , Rooney William 
Published: August 2023

AbstractFor nearly two decades, genomic selection has supported efforts to increase genetic gains in plant and animal improvement programs. However, novel phenomic strategies helping to predict complex traits in maize have proven beneficial when integrated into across– and within-environment genomic prediction models. One phenomic data modality is near infrared spectroscopy (NIRS), which records reflectance values of biological samples (e.g., maize kernels) based on chemical composition. Predictions of seven maize agronomic traits and three kernel composition traits across two years (2011-2012) and two management conditions (water stressed and well-watered) were conducted using combinations of NIRS and genomic data within four different cross-validation prediction scenarios. In aggregate, models incorporating NIRS data alongside genomic data improved predictive ability over models using only genomic data in 5 of 28 trait/cross-validation scenarios for across-environment prediction and 15 of 28 trait/environment scenarios for within-environment prediction, while the model with NIRS data alone had the highest prediction ability in only 1 of 28 scenarios for within-environment prediction. Potential causes of the surprisingly lower phenomic than genomic prediction power in this study are discussed, including sample size, sample homogenization, and low G×E. A genome-wide association study (GWAS) implicated known (i.e.,MADS69,ZCN8, sh1, wx1, du1) and unknown candidate genes linked to plant height and flowering-related agronomic traits as well as compositional traits such as kernel protein and starch content. This study demonstrated that including NIRS with genomic markers is a viable method to predict multiple complex traits with improved predictive ability and elucidate underlying biological causes.Key messageGenomic and NIRS data from a maize diversity panel were used for prediction of agronomic and kernel composition traits while uncovering candidate genes for kernel protein and starch content.
A Biotin Targeting Chimera (BioTAC) System to Map Small Molecule Interactomesin situ
Authors: Tao Andrew J. , Jiang Jiewei , Gadbois Gillian E. , Goyal Pavitra , Boyle Bridget T. , Mumby Elizabeth J. , Myers Samuel A , English Justin G. , Ferguson Fleur M. 
Published: August 2023

ABSTRACTUnbiased chemical biology strategies for direct readout of protein interactome remodelling by small molecules provide advantages over target-focused approaches, including the ability to detect previously unknown targets, and the inclusion of chemical off-compete controls leading to high-confidence identifications. We describe the BioTAC system, a small-molecule guided proximity labelling platform, to rapidly identify both direct and complexed small molecule binding proteins. The BioTAC system overcomes a limitation of current approaches, and supports identification of both inhibitor bound and molecular glue bound complexes.
Microglia mediate contact-independent neuronal pruning via secreted Neuraminidase-3 associated with extracellular vesicles
Authors: Delaveris Corleone S. , Wang Catherine L. , Riley Nicholas M. , Li Sherry , Kulkarni Rishikesh U. , Bertozzi Carolyn R. 
Published: August 2023

AbstractNeurons communicate with each other through electrochemical transmission at synapses. Microglia, the resident immune cells of the central nervous system, can prune these synapses through a variety of contact-dependent and -independent means. Microglial secretion of active sialidase enzymes upon exposure to inflammatory stimuli is one unexplored mechanism of pruning. Recent work from our lab showed that treatment of neurons with bacterial sialidases disrupts neuronal network connectivity. Here, we find that activated microglia secrete Neuraminidase-3 (Neu3) associated with fusogenic extracellular vesicles. Furthermore, we show Neu3 mediates contact-independent pruning of neurons and subsequent disruption of neuronal networks through neuronal glycocalyx remodeling. We observe thatNEU3is transcriptionally upregulated upon exposure to inflammatory stimuli, and that a genetic knock-out ofNEU3abrogates the sialidase activity of inflammatory microglial secretions. Moreover, we demonstrate that Neu3 is associated with a subpopulation of extracellular vesicles, possibly exosomes, that are secreted by microglia upon inflammatory insult. Finally, we demonstrate that Neu3 is both necessary and sufficient to both desialylate neurons and decrease neuronal network connectivity. These results implicate Neu3 in remodeling of the glycocalyx leading to aberrant network-level activity of neurons, with implications in neuroinflammatory diseases such as Parkinson’s disease and Alzheimer’s disease.Graphical AbstractNeuroinflammation induces secretion of the sialidase Neu3 via extracellular vesicles from microglia that prune neuronal synapses and disrupt neuronal communication.
A hyperpolarizing neuron recruits undocked innexin hemichannels to transmit neural information inCaenorhabditis elegans
Authors: Nakayama Airi , Watanabe Masakatsu , Yamashiro Riku , Kuroyanagi Hiroo , Oshima Atsunori , Mori Ikue , Nakano Shunji 
Published: August 2023

AbstractWhile depolarization of neuronal membrane is known to evoke the neurotransmitter release from synaptic vesicles, hyperpolarization is regarded as a resting state of chemical neurotransmission. Here we report that hyperpolarizing neurons can actively signal neural information by employing undocked hemichannels. We show that UNC-7, a member of the innexin family inCaenorhabditis elegans,functions as a hemichannel in thermosensory neurons and transmits temperature information from the thermosensory neurons to their post-synaptic interneurons. By monitoring neural activities in freely behaving animals, we find that hyperpolarizing thermosensory neurons inhibit the activity of the interneurons and that UNC-7 hemichannels regulate this process. UNC-7 is required to control thermotaxis behavior and functions independently of synaptic vesicle exocytosis. Our findings suggest that innexin hemichannels mediate neurotransmission from hyperpolarizing neurons in a manner that is distinct from the synaptic transmission, expanding the way of neural circuitry operations.
Genomic and epigenomic evolution of metastatic prostate cancer: the first warm autopsy in China
Authors: Zhang Wenhui , Wang Yan , Qu Min , Shi Haoqing , Lu Xin , Yang Qingsong , Liu Fang , Wang Tao , Wang Ziwei , Lian Bijun , Chen Ling , Yin Xiaoyi , Yu Yongwei , Li Jing , Gao Xu , Liao Zhuan 
Published: August 2023

AbstractBackgroundThe development and expansion of warm autopsy program have important implications in dissecting the heterogeneity during cancer dissemination and resistance. However, in China, the practice of warm autopsy has not yet been officially launched and documented.MethodsTo explore and establish the procedures and standards for warm autopsy in China, we followed the disease course of a male patient with terminal metastatic prostate cancer. We assembled a multidisciplinary team to perform warm autopsy immediately after death. Through longitudinal sampling from biopsy and autopsy, we performed integrative and comprehensive genomic and epigenomic analysis using multi-omics approaches.ResultsWe traced the dynamic evolution and heterogeneity of this prostate tumor, and identified many critical driver events in both the original tumor and its disseminations. TruncatedCDKN1Bmay result in downregulation of expression, which represent a key driver event in the metastatic progression of prostate cancer. We also delineated the congruence of genetic and epigenetic clonal evolution during tumor metastasis.ConclusionsOur data and analysis elucidated the mechanisms and drivers during metastasis, which represent a valuable resource for the study and treatment of prostate cancer. We also call on more investigators to improve warm autopsy of prostate cancer for clinical and experimental investigations.