bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid PTEFb-dependent transcriptional reorganization underpins the glioma adaptive response to radiotherapy
Authors: Walker Faye M. , Sobral Lays Martin , Danis Etienne , Sanford Bridget , Balakrishnan Ilango , Wang Dong , Pierce Angela , Karam Sana D. , Serkova Natalie J. , Foreman Nicholas K. , Venkataraman Sujatha , Dowell Robin , Vibhakar Rajeev , Dahl Nathan A. 
Published: January 2023

AbstractDynamic regulation of gene expression is fundamental for cellular adaptation to exogenous stressors. PTEFb-mediated pause-release of RNA polymerase II (Pol II) is a conserved regulatory mechanism for synchronous transcriptional induction in response to heat shock, but this pro-survival role has not been examined in the applied context of cancer therapy. Using model systems of pediatric high-grade glioma, we show that rapid genome-wide reorganization of active chromatin facilitates PTEFb-mediated nascent transcriptional induction within hours of exposure to therapeutic ionizing radiation. Concurrent inhibition of PTEFb disrupts this chromatin reorganization and blunts transcriptional induction, abrogating key adaptive programs such as DNA damage repair and cell cycle regulation. This combination demonstrates a potent, synergistic therapeutic potential agnostic of glioma subtype, leading to a marked induction of tumor cell apoptosis and prolongation of xenograft survival. These studies reveal a central role for PTEFb underpinning the early adaptive response to radiotherapy, opening new avenues for combinatorial treatment in these lethal malignancies.
Identification of Immune-Related Candidate Biomarkers in Plasma of Patients with Sporadic Vestibular Schwannoma
Authors: Vasilijic Sasa , Atai Nadia A. , Hyakusoku Hiroshi , Worthington Steven , Ren Yin , Sagers Jessica E. , Sahin Mehmet I , Fujita Takeshi , Landegger Lukas D. , Lewis Richard , Welling D. Bradley , Stankovic Konstantina M. 
Published: January 2023

AbstractVestibular schwannoma (VS) is intracranial tumor arising from neoplastic Schwann cells, causing hearing loss in about 95% of patients. The traditional belief that hearing deficit is caused by physical expansion of the VS, compressing the auditory nerve, does not explain the common clinical finding that patients with small tumors can have profound hearing loss, suggesting that tumor-secreted factors could influence hearing ability in VS patients. Here, we conducted profiling of patients’ plasma for 67 immune-related factors on a large cohort of VS patients (N>120) and identified candidate biomarkers associated with tumor growth (IL-16 and S100B) and hearing (MDC). We identified the 7-biomarker panel composed of MCP-3, BLC, S100B, FGF-2, MMP-14, eotaxin, and TWEAK that showed outstanding discriminatory ability for VS. These findings revealed possible therapeutic targets for VS-induced hearing loss and provided a unique diagnostic tool that may predict hearing change and tumor growth in VS patients and may help inform the ideal timing of tumor resection to preserve hearing.TeaserProfiling of plasma in vestibular schwannoma patients revealed biomarkers that could predict hearing change and tumor growth.
An antagonism between Spinophilin and Syd-1 operates upstream of memory-promoting presynaptic long-term plasticity
Authors: Ramesh Niraja , Escher Marc , Turrel Oriane , Lützkendorf Janine , Matkovic Tanja , Liu Fan , Sigrist Stephan J. 
Published: January 2023

AbstractWe still face fundamental gaps in understanding how molecular plastic changes of synapses intersect with circuit operation to define behavioral states. Here we show that an antagonism between two conserved regulatory proteins, Spinophilin (Spn) and Syd-1, controls presynaptic long-term plasticity and the maintenance of olfactory memories inDrosophila. WhileSpnmutants could not trigger nanoscopic active zone remodeling under homeostatic challenge and failed to stably potentiate neurotransmitter release, concomitant reduction of Syd-1 rescued all these deficits. The Spn/Syd-1 antagonism converged on active zone close F-actin, and genetic or acute pharmacological depolymerization of F-actin rescued theSpndeficits by allowing access to synaptic vesicle release sites. Within the intrinsic mushroom body neurons, the Spn/Syd-1 antagonism specifically controlled olfactory memory stabilization but not initial learning. Thus, this evolutionarily conserved protein complex controls behaviorally relevant presynaptic long-term plasticity, also observed in the mammalian brain but still enigmatic concerning its molecular mechanisms and behavioral relevance.
Molecular Jackhammers Eradicate Cancer Cells by Vibronic-Driven Action
Authors: Ayala-Orozco Ciceron , Galvez-Aranda Diego , Corona Arnoldo , Seminario Jorge M. , Rangel Roberto , Myers Jeffrey N. , Tour James M. 
Published: January 2023

AbstractThrough the actuation of vibronic modes in cell-membrane-associated aminocyanines, a new type of molecular mechanical action can be exploited to rapidly kill cells by necrosis. This is done using near-infrared light, a low energy source hitherto thought to be insufficient to permit molecular mechanical disruption of a cell membrane. Vibronic-driven action (VDA) is distinct from both photodynamic therapy and photothermal therapy in that the VDA mechanical effect on the cell membrane is not retarded by high doses of inhibitors of reactive oxygen species (ROS), and VDA does not itself induce an increase in the temperature of the media; it is also unaffected by cooling the media to 2 °C. The picosecond concerted whole-molecule-vibrations of VDA-induced mechanical disruption can be done with very low concentrations (500 nM) of the aminocyanines or low doses of light (12 Jcm-2, 80 mWcm-2for 2.5 min) to causein vitronecrotic cell death in >99% of human melanoma cells. The effect is also studiedin vivoin murine B16-F10 and human A375 melanoma in mice, underscoring the high efficiency of this approach, achieving a survival rate of 60% at day 120, and 50% of the mice becoming tumor free. The molecules that destroy cell membranes through VDA are termed molecular jackhammers (MJH) because they undergo concerted whole-molecule vibrations. Different than traditional chemotherapy, it is unlikely that a cell could develop a resistance to molecular mechanical forces, thereby providing a new modality for inducing cancer cell death.
A deep learning approach for the discovery of tumor-targeting small organic ligands from DNA-Encoded Chemical Libraries
Authors: Torng Wen , Biancofiore Ilaria , Oehler Sebastian , Xu Jin , Xu Jessica , Watson Ian , Masina Brenno , Prati Luca , Favalli Nicholas , Bassi Gabriele , Neri Dario , Cazzamalli Samuele , Feng Jianwen A. 
Published: January 2023

AbstractDNA-Encoded Chemical Libraries (DELs) emerged as efficient and cost-effective ligand discovery tools, which enable the generation of protein-ligand interaction data of unprecedented size. In this article, we present an approach that combines DEL screening and instance-level deep learning modeling to identify tumor-targeting ligands against Carbonic Anhydrase IX (CAIX), a clinically validated marker of hypoxia and clear cell Renal Cell Carcinoma. We present a new ligand identification and HIT-to-LEAD strategy driven by Machine Learning (ML) models trained on DELs, which expand the scope of DEL-derived chemical motifs. CAIX screening datasets obtained from three different DELs were used to train ML models for generating novel HITs, dissimilar to elements present in the original DELs. Out of the 152 novel potential HITs that were identified with our approach and screened in anin vitroenzymatic inhibition assay, 70% displayed submicromolar activities (IC50< 1 μM). Based on the first HIT set, the model was further used to prioritize and generate LEAD compounds with nanomolar affinity forin vivotumor-targeting applications. Three LEAD candidates showed accumulation on the surface of CAIX-expressing tumor cells in cellular binding assays. The best compound displayedin vitroKDof 5.7 nM and selectively targeted tumors in mice bearing human Renal Cell Carcinoma lesions. Our results demonstrate the synergy between DEL and machine learning for the identification of novel HITs and for the successful translation of LEAD candidates forin vivotargeting applications.Graphical Abstracts
adgrl3.1-deficient zebrafish show noradrenaline-mediated externalizing behaviors, and altered expression of externalizing disorder-candidate genes, suggesting functional targets for treatment
Authors: Fontana Barbara D. , Reichmann Florian , Tilley Ceinwen A. , Lavlou Perrine , Shkumatava Alena , Alnassar Nancy , Hillman Courtney , Karlsson Karl Ægir , Norton William H.J. , Parker Matthew O. 
Published: January 2023

AbstractExternalising disorders (ED) are a cause of concern for public health, and their high heritability make genetic risk factors a priority for research. Adhesion G Protein-Coupled Receptor L3 (ADGRL3) is strongly linked to several EDs, and loss-of-function models have shown impacts of this gene on several core ED-related behaviors. For example,adgrl3.1-/-zebrafish show high levels of hyperactivity. However, our understanding of the mechanisms by which this gene influences behavior is incomplete. Here we characterized, for the first time, externalizing behavioral phenotypes ofadgrl3.1-/-zebrafish and found them to be highly impulsive, show boldness in a novel environment, have attentional deficits, and show high levels of hyperactivity. All of these phenotypes were rescued by atomoxetine, demonstrating noradrenergic mediation of the externalizing effects ofadgrl3.1. Transcriptomic analyses of the brains ofadgrl3.1-/-vs wild type fish revealed several differentially expressed genes and enriched gene clusters that were independent of noradrenergic manipulation. This suggests new putative functional pathways underlying ED-related behaviors, and potential targets for the treatment of ED.
Lifelong olfactory deprivation-dependent cortical reorganization restricted to orbitofrontal cortex
Authors: Peter Moa G. , Darki Fahimeh , Thunell Evelina , Mårtensson Gustav , Postma Elbrich M. , Boesveldt Sanne , Westman Eric , Lundström Johan N. 
Published: January 2023

ABSTRACTProlonged sensory deprivation has repeatedly been linked to cortical reorganization. We recently demonstrated that individuals with congenital anosmia (CA, complete olfactory deprivation since birth) have seemingly normal morphology in piriform (olfactory) cortex despite profound morphological deviations in the orbitofrontal cortex (OFC), a finding contradictory to both the known effects of blindness on visual cortex and to the sparse literature on brain morphology in anosmia. To establish whether these unexpected findings reflect the true brain morphology in CA, we first performed a direct replication of our previous study. Individuals with CA (n=30) were compared to age and sex matched controls (n=30) using voxel- and surface-based morphometry. The replication results were near identical to the original study: bilateral clusters of group differences in the OFC, including CA atrophy around the olfactory sulci and volume increases in the medial orbital gyri. Importantly, no group differences in piriform cortex were detected. Subsequently, to assess any subtle patterns of group differences not detectable by our mass-univariate analysis, we explored the data from a multivariate perspective. Combining the newly collected data with data from the replicated study (CA=49, Control=49) we performed support vector machine classification based on gray matter volume. In line with the mass-univariate analyses, the multivariate analysis could accurately differentiate between the groups in bilateral OFC (75-96% accuracy), whereas the classification accuracy in piriform cortex was at chance level. Our results suggest that despite lifelong olfactory deprivation, piriform (olfactory) cortex is morphologically unaltered and the morphological deviations in CA are confined to the OFC.
Strain tracking with uncertainty quantification
Authors: Kim Younhun , Worby Colin J. , Acharya Sawal , van Dijk Lucas R. , Alfonsetti Daniel , Gromko Zackary , Azimzadeh Philippe , Dodson Karen , Gerber Georg , Hultgren Scott , Earl Ashlee M. , Berger Bonnie , Gibson Travis E. 
Published: January 2023

AbstractThe ability to detect and quantify microbiota over time has a plethora of clinical, basic science, and public health applications. One of the primary means of tracking microbiota is through sequencing technologies. When the microorganism of interest is well characterized or knowna priori, targeted sequencing is often used. In many applications, however, untargeted bulk (shotgun) sequencing is more appropriate; for instance, the tracking of infection transmission events and nucleotide variants across multiple genomic loci, or studying the role of multiple genes in a particular phenotype. Given these applications, and the observation that pathogens (e.g.Clostridioides difficile, Escherichia coli, Salmonella enterica) and other taxa of interest can reside at low relative abundance in the gastrointestinal tract, there is a critical need for algorithms that accurately track low-abundance taxa with strain level resolution. Here we present a sequence quality- and time-aware model,ChronoStrain, that introduces uncertainty quantification to gauge low-abundance species and significantly outperforms the current state-of-the-art on both real and synthetic data. ChronoStrain leverages sequences’ quality scores and the samples’ temporal information to produce a probability distribution over abundance trajectories for each strain tracked in the model. We demonstrate Chronostrain’s improved performance in capturing post-antibioticEscherichia colistrain blooms among women with recurrent urinary tract infections (UTIs) from the UTI Microbiome (UMB) Project. Other strain tracking models on the same data either show inconsistent temporal colonization or can only track consistently using very coarse groupings. In contrast, our probabilistic outputs can reveal the relationship between low-confidence strains present in the sample that cannot be reliably assigned a single reference label (either due to poor coverage or novelty) while simultaneously calling high-confidence strains that can be unambiguously assigned a label. We also analyze samples from the Early Life Microbiota Colonisation (ELMC) Study demonstrating the algorithm’s ability to correctly identifyEnterococcus faecalisstrains using paired sample isolates as validation.
Adjustments to the reference dataset design improves cell type label transfer
Authors: Mölbert Carla , Haghverdi Laleh 
Published: January 2023

AbstractThe transfer of cell type labels from prior annotated (reference) to newly collected data is an important task in single-cell data analysis. As the number of publicly available annotated datasets which can be used as a reference, as well as the number of computational methods for cell type label transfer are constantly growing, rationals to understand and decide which reference design and which method to use for a particular query dataset is needed. Here, we benchmark a set of five popular cell type annotation methods, study the performance on different cell types and highlight the importance of the design of the reference data (number of cell samples for each cell type, inclusion of multiple datasets in one reference, gene set selection, etc.) for more reliable predictions.
Aminobenzoic acid derivatives obstruct induced fit in the catalytic center of the ribosome
Authors: Majumdar Chandrima , Walker Joshua A. , Francis Matthew B. , Schepartz Alanna , Cate Jamie H. D. 
Published: January 2023

AbstractTheEscherichia coliribosome can incorporate a variety of non-l-α-amino acid monomers into polypeptide chains, but with poor efficiency. Although these monomers span a diverse set of compounds, there exists no high-resolution structural information regarding their positioning within the catalytic center of the ribosome, the peptidyl transferase center (PTC). Thus, details regarding the mechanism of amide bond formation and the structural basis for differences and defects in incorporation efficiency remain unknown. Within a set of three aminobenzoic acid derivatives–3-aminopyridine-4-carboxylic acid (Apy),ortho-aminobenzoic acid (oABZ), andmeta-aminobenzoic acid (mABZ)–the ribosome incorporates Apy into polypeptide chains with the highest efficiency, followed byoABZ and thenmABZ, a trend that does not track with the nucleophilicity of the reactive amines. Here, we report high resolution cryo-EM structures of the ribosome with these three aminobenzoic acid derivatives charged on tRNA bound in the aminoacyl-tRNA site (A site). These structures reveal how the aromatic ring of each monomer sterically blocks positioning of nucleotide U2506, thereby preventing rearrangement of nucleotide U2585 and the resulting induced fit in the PTC required for efficient amide bond formation. They also reveal disruptions to the “proton wire” responsible for facilitating formation and breakdown of the tetrahedral intermediate. Together, the cryo-EM structures reported here provide a clear rationale for differences in reactivity of aminobenzoic acid derivatives relative tol-α-amino acids and each other, and point to stereochemical constraints on the size and geometry of non-proteinogenic monomers that can be accepted efficiently by wild-type ribosomes.
A supervised Bayesian factor model for the identification of multi-omics signatures
Authors: Gygi Jeremy P. , Konstorum Anna , Pawar Shrikant , Aron Edel , Kleinstein Steven H. , Guan Leying 
Published: January 2023

AbstractMotivationPredictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are identified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive modeling. However, multi-omics integration and predictive modeling are generally performed independently in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.ResultsWe developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the reconstruction of underlying factors in synthetic examples and prediction accuracy of COVID-19 severity and breast cancer tumor subtypes.AvailabilitySPEAR is a publicly available R-package hosted athttps://bitbucket.org/kleinstein/SPEAR.Contactjeremy.gygi@yale.edu;leying.guan@yale.edu
Activated Sludge Microbial Community Assembly: The Role of Influent Microbial Community Immigration
Authors: Gibson Claire , Jauffur Shameem , Guo Bing , Frigon Dominic 
Published: January 2023

AbstractWastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater, however the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilised controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analysed by harvesting wastewater biomass solids from 3 different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 25 % of the sequencing reads in the AS. By modelling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principals for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs.ImportanceIn biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. To allow future process optimisation to meet new treatment goals, we need a better understanding of factors influencing the microbial community assembly in WWTPs. This study developed a reproducible protocol to investigates the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls. We demonstrate herein that influent immigration contributed up to 25 % of the sequencing reads in the activated sludge under the studied conditions, highlighting the need to consider this process in future WWTP modelling and design.