bluuebunny/crossref_metadata_2025_split huggingface dataset:
MENTOR: Multiplex Embedding of Networks for Team-Based Omics Research
Authors: Sullivan Kyle A. , Miller J. Izaak , Townsend Alice , Morgan Mallory , Lane Matthew , Pavicic Mirko , Shah Manesh , Cashman Mikaela , Jacobson Daniel A. 
Published: July 2024

AbstractWhile the proliferation of data-driven omics technologies has continued to accelerate, methods of identifying relationships among large-scale changes from omics experiments have stagnated. It is therefore imperative to develop methods that can identify key mechanisms among one or more omics experiments in order to advance biological discovery. To solve this problem, here we describe the network-based algorithm MENTOR - Multiplex Embedding of Networks for Team-Based Omics Research. We demonstrate MENTOR’s utility as a supervised learning approach to successfully partition a gene set containing multiple ontological functions into their respective functions. Subsequently, we used MENTOR as an unsupervised learning approach to identify important biological functions pertaining to the host genetic architectures inPopulus trichocarpaassociated with microbial abundance of multiple taxa. Moreover, as open source software designed with scientific teams in mind, we demonstrate the ability to use the output of MENTOR to facilitate distributed interpretation of omics experiments.
Double Trouble: Multiple infections and the coevolution of virulence-resistance in structured host-parasite populations
Authors: Lombard Julien D. , Massol François , Lion Sébastien 
Published: July 2024

AbstractParasite evolution is expected to modulate selective pressures acting upon host, and alter its response to infection. In such a context, parasite competition seems be a key variable for the evolutionary dynamics and epidemic features. We develop a nested coevolutionary model of host resistance and parasite virulence. From individual-based traits, we define a within-host model and derive from the within-host equilibrium the main epidemiological features of interest -transmission, virulence, recovery-. We use this first model to build an adaptive dynamics model in order to assess the joint evolution of the parasite virulence and host resistance. We compared the coevolutionarily stable states predicted by the model under different competition regimes, including single infections (preemption), superinfection (dominance) and coinfections (mixed). We find that parasite virulence under coinfections evolved towards higher values than under superinfections, while the opposite trend was observed for host resistance. The local coexistence of parasites enables a kin selection effects that reduce both virulence and the subsequent host response. We showed that the magnitude of multiple infections effects varies with the ecological context, and that the coevolutionary outcomes deviate from simple optimization of persistence depending on the degree of spatial coupling of hosts.
The inhibition of three distinct signaling pathways eliminates the oncogenic Tribbles homolog 2 from melanoma cells
Authors: Mayoral-Varo Victor , Orea-Soufi Alba , Jiménez Lucía , Santos Bruno , Serrão Gisela , Jociles Miguel , Obeso Sara , Ferreira Bibiana I. , Link Wolfgang 
Published: July 2024

ABSTRACTTribbles homolog 2 (TRIB2) is one of three members of the Tribbles family of pseudo serine/threonine kinases. It acts as an oncogene whose expression is correlated with tumor stage and therapy response in melanoma. While metastatic melanoma, the most aggressive form of skin cancer now has two effective treatment options, namely MAPK pathway and immune checkpoint inhibitors, the majority of patients primarily fail to respond or acquire secondary resistance. Hence, innovative approaches to identify disease-relevant, druggable targets to remove the roadblock of therapy resistance are urgently needed. TRIB2 has been implicated in conferring resistance to various anti-cancer therapies suggesting TRIB2 as a therapeutic target for resistant tumors. This study explores the pharmacological targeting of TRIB2, revealing several independent routes of pharmacological manipulations. TRIB2 is a short-lived protein stabilized by inhibition of the PI3K/AKT pathway. Conversely, inhibitors of BRAF, MEK and ERK significantly decrease TRIB2 expression by a mechanism that involves transcription. Strikingly, increasing concentrations of the kinase inhibitor PIK75 effectively eliminate TRIB2 in melanoma cells surpassing its PI3K inhibitory activity. Additionally, Polo-Like Kinases (PLKs) inhibitors significantly reduce TRIB2 protein expression and stability. We demonstrate that inhibition or silencing of PLK2 leads to a decrease in TRIB2 levels. Overall, we identify three distinct classes of compounds that efficiently eliminate the oncogenic TRIB2 protein from melanoma cells based on different molecular mechanisms and exhibiting 40 to 200 times greater potency than the previously reported afatinib.
SpeSpeNet: An interactive and user-friendly tool to create and explore microbial correlation networks
Authors: van Eijnatten A.L. , van Zon L. , Manousou E. , Bikineeva M. , Wubs J. , van der Putten W. , Morriën E. , Dutilh B.E. , Snoek B.L. 
Published: July 2024

AbstractCorrelation networks are commonly used to explore microbiome data. In these networks, nodes are taxa and edges represent correlations between their abundance patterns across samples. As clusters of correlating taxa (co-abundance clusters) often indicate a shared response to environmental drivers, network visualization contributes to system understanding. Currently, most tools for creating and visualizing co-abundance networks from microbiome data either require the researcher to have coding skills, or they are not user-friendly, with high time expenditure and limited customizability. Furthermore, existing tools lack focus on the relationship between environmental drivers and the structure of the microbiome, even though many edges in correlation networks can be understood through a shared relationship of two taxa with the environment. For these reasons we developed SpeSpeNet (Species-Species Network,https://tbb.bio.uu.nl/SpeSpeNet), a practical and user-friendly R-shiny tool to construct and visualize correlation networks from taxonomic abundance tables. The details of data preprocessing, network construction, and visualization are automated, require no programming ability for the web version, and are highly customizable, including associations with user-provided environmental data. Here, we present the details of SpeSpeNet and demonstrate its utility using three case studies.
Atypical soluble guanylyl cyclases control brain size inDrosophila
Authors: Prieto Daniel , Egger Boris , Cantera Rafael 
Published: July 2024

AbstractHypoxia-induced proliferation of neural stem cells has a crucial role in brain development. In the brain ofDrosophila melanogaster, the optic lobe exhibits progressive hypoxia during larval development. Here, we investigate an alternative oxygen-sensing mechanism within this brain compartment, distinct from the canonical hypoxia signaling pathway mediated by HIF. Using genetic tools, immunostaining, and confocal microscopy, we demonstrate that the loss of the atypical soluble guanylyl cyclase (asGC) subunitGyc88E, or the ectopic expression ofGyc89Dbin neural stem cells leads to increased optic lobe volume. We propose the existence of a link between cGMP signaling and neurogenesis in the developing brain.
Adolescent alcohol exposure alters age-related progression of behavioral and neurotrophic dysfunction in the TgF344-AD model in a sex-specific manner
Authors: Reitz Nicole L. , Nunes Polliana T. , Savage Lisa M. 
Published: July 2024

AbstractAlzheimer’s Disease (AD) and heavy alcohol use are widely prevalent and lead to brain pathology. Both alcohol-related brain damage (ABRD) and AD result in cholinergic dysfunction, reductions in hippocampal neurogenesis, and the emergence of hippocampal-dependent cognitive impairments. It is still unknown how ARBD caused during a critical developmental timepoint, such as adolescence, interacts with AD-related pathologies to accelerate disease progression later in life. The current study utilized a longitudinal design to characterize behavioral and pathological changes in a transgenic rat model of AD (TgF344-AD) following adolescent intermittent ethanol (AIE) exposure. We found that AIE accelerates cognitive decline associated with AD transgenes in female rats at 6 months of age, and male AD-rats are impaired on spatial navigation by 3-months with no additional deficits due to AIE exposure. Protein levels of various AD-pathological markers were analyzed in the dorsal and ventral hippocampus of male and female rats. The data suggests that AIE-induced alterations of the tropomyosin-related kinase A receptor (TrkA) / p75 neurotrophin receptor (p75NTR) ratio creates a brain that is vulnerable to age- and AD-related pathologies, which leads to an acceleration of cognitive decline, particularly in female rats.
Computational investigation of missense somatic mutations in cancer and potential links to pH-dependence and proteostasis
Authors: Sallah Shalaw , Warwicker Jim 
Published: July 2024

AbstractMetabolic changes during tumour development lead to acidification of the extracellular environment and a smaller increase of intracellular pH. Searches for somatic missense mutations that could reveal adaptation to altered pH have focussed on arginine to histidine changes, part of a general arginine depletion that originates from DNA mutational mechanisms. Analysis of mutations to histidine, potentially a simple route to the introduction of pH-sensing, shows no clear biophysical separation overall of subsets that are more and less frequently mutated in cancer genomes. Within the more frequently mutated subset, individual sites predicted to mediate pH-dependence upon mutation include NDST1 (a Golgi-resident heparan sulphate modifying enzyme), the HLA-C chain of MHCI complex, and the water channel AQP-7. Arginine depletion is a general feature that persists in the more frequently mutated subset, and is complemented by over-representation of mutations to lysine. Arginine to lysine balance is a known factor in determining protein solubility, with higher lysine content being more favourable. Proteins with greater change in arginine to lysine balance are enriched for cell periphery location, where proteostasis is likely to be challenged in tumour cells. Somatic missense mutations in a cancer genome number only in the 10s typically, although can be much higher. Whether the altered arginine to lysine balance is of sufficient scale to play a role in tumour development is unknown.
Quantifying higher-order epistasis: beware the chimera
Authors: Chitra Uthsav , Arnold Brian J. , Raphael Benjamin J. 
Published: July 2024

AbstractEpistasis, or interactions in which alleles at one locus modify the fitness effects of alleles at other loci, plays a fundamental role in genetics, protein evolution, and many other areas of biology. Epistasis is typically quantified by computing the deviation from the expected fitness under an additive or multiplicative model using one of several formulae. However, these formulae are not all equivalent. Importantly, one widely used formula – which we call thechimericformula – measures deviations from amultiplicativefitness model on anadditivescale, thus mixing two measurement scales. We show that for pairwise interactions, the chimeric formula yields a different magnitude, but the same sign (synergistic vs. antagonistic) of epistasis compared to the multiplicative formula that measures both fitness and deviations on a multiplicative scale. However, for higher-order interactions, we show that the chimeric formula can have both different magnitudeandsign compared to the multiplicative formula — thus confusing negative epistatic interactions with positive interactions, and vice versa. We resolve these inconsistencies by deriving fundamental connections between the different epistasis formulae and the parameters of themultivariate Bernoulli distribution. Our results demonstrate that the additive and multiplicative epistasis formulae are more mathematically sound than the chimeric formula. Moreover, we demonstrate that the mathematical issues with the chimeric epistasis formula lead to markedly different biological interpretations of real data. Analyzing multi-gene knockout data in yeast, multi-way drug interactions inE. coli, and deep mutational scanning (DMS) of several proteins, we find that 10 − 60% of higher-order interactions have a change in sign with the multiplicative or additive epistasis formula. These sign changes result in qualitatively different findings on functional divergence in the yeast genome, synergistic vs. antagonistic drug interactions, and and epistasis between protein mutations. In particular, in the yeast data, the more appropriate multiplicative formula identifies nearly 500 additional negative three-way interactions, thus extending the trigenic interaction network by 25%.
Using state space models to understand trait evolution in fossil lineages
Authors: Hunt Gene , Martinez Rivera Wilmer , Hopkins Melanie , Fricks John , Sterner Beckett 
Published: July 2024

AbstractLinear state space models provide a useful framework for investigating phenotypic evolution in fossil lineages in a wide variety of models including Brownian motion, Ornstein-Uhlenbeck processes, and models that incorporate potentially explanatory environmental covariates. A state space framework also provides access to residuals for the predicted and observed values at each time point as well as improved numerical stability. We illustrate the value of the state space approach by re-analyzing a classic dataset of diatom evolution in Yellowstone Lake. We find that number of spines is best explained by adaptation to changing solar insolation as an exogenous environmental covariate.
Single laboratory evaluation of the (Q20+) nanopore sequencing kit for bacterial outbreak investigations
Authors: Hoffmann Maria , Jang Jay Hee , Tallent Sandra , Gonzalez-Escalona Narjol 
Published: July 2024

AbstractThis study aimed to evaluate the potential of Oxford Nanopore Technologies (ONT) GridION with Q20+ chemistry as a rapid and accurate method for identifying and clustering foodborne pathogens. The study focuses on assessing whether ONT Q20+ technology could offer near real-time pathogen identification, including SNP differences, serotypes, and antimicrobial resistance genes, to overcome the drawbacks of existing methodologies. This pilot study evaluated different combinations of two DNA extraction methods (Maxwell RSC Cultured Cell DNA kit, and Monarch high molecular weight extraction kits) and two ONT library preparation protocols (ligation and the rapid barcoding sequencing kit) using five well-characterized strains representing diverse foodborne pathogens. The results showed that any combination of extraction and sequencing kits produced high-quality closed bacterial genomes. However, there were variations in assembly length and genome completeness based on different combinations of methods, indicating the need for further optimization.in silicoanalyses demonstrated that the Q20+ nanopore sequencing chemistry accurately identified species, genotyped, and detected virulence factors comparable to Illumina sequencing. Phylogenomic clustering methods showed that ONT assemblies clustered with reference genomes, although some indels and SNP differences were observed. There were also differences on SNP accuracy among the different species. The observed SNP differences were likely due to sequencing and analysis processes rather than genetic variations in the sampled bacteria. The study also compared a change in the basecaller model with the previous model (SUP 4Khz 260 bps) and found no significant difference in accuracy (SUP 5Khz 400 bps). In conclusion, the evaluation of ONT Q20+ nanopore sequencing chemistry demonstrated its potential as an alternative for rapid and comprehensive bacterial genome analysis in outbreak investigations. However, further research, verification studies, and optimization efforts are needed to address the observed limitations to adopt and fully realize the impact of nanopore sequencing on public health outcomes and more efficient responses to foodborne disease threats.
EngineeringCandida boidiniiformate dehydrogenase for activity with NMN(H)
Authors: Vainstein Salomon , Banta Scott 
Published: July 2024

AbstractMulti-step enzymatic reaction cascades often involve cofactors that serve as electron donors/acceptors in addition to the primary substrates. The co-localization of cascades can lead to cross-talk and competition, which can be unfavorable for the production of a targeted product. Orthogonal pathways allow reactions of interest to operate independently from the metabolic reactions within a cell; non-canonical cofactor analogs have been explored as a means to create these orthogonal pathways. Here, we aimed to engineer the formate dehydrogenase fromCandid boidinii(CbFDH) for activity with the non-canonical cofactor nicotinamide adenine mononucleotide (NMN(H)). We used PyRosetta and structural alignment to design mutations that enable CbFDH to use NMN+for the oxidation of formate. Although the suggested mutations did not result in enhanced activity with NMN+, we found that PyRosetta was able to easily design single mutations that disrupted all enzymatic activity.
A neurofunctional signature of affective arousal generalizes across valence domains and distinguishes subjective experience from autonomic reactivity
Authors: Zhang Ran , Gan Xianyang , Xu Ting , Yu Fangwen , Wang Lan , Song Xinwei , Jiao Guojuan , Liu Xiqin , Zhou Feng , Becker Benjamin 
Published: July 2024

AbstractArousal is fundamental for affective experience and, together with valence, defines the core affective space. Precise brain models of affective arousal are lacking, leading to continuing debates of whether the neural systems generalize across valence domains and are separable from those underlying autonomic arousal or wakefulness. Here, we combined naturalistic fMRI with predictive modeling to develop a brain affective arousal signature (BAAS, discovery-validation design, n=60, 36). We demonstrate its (1) sensitivity and generalizability across mental processes and valence, and (2) neural distinction from autonomic arousal, wakefulness, and stimulation modality (24 studies, n=868). Affective arousal was encoded in distributed cortical-subcortical (e.g., prefrontal, PAG) systems with local similarities in thalamo-amygdala-insula systems between affective and autonomous arousal. We demonstrate application of the BAAS to improve specificity of established valence-specific neuromarkers. Our study provides a biologically plausible model for affective arousal that aligns with the affective space and has a high application potential.
Dnmt1 determines bone length by regulating energy metabolism of growth plate chondrocytes
Authors: Yanagihara Yuta , Takahashi Masatomo , Izumi Yoshihiro , Kinoshita Tomofumi , Takao Masaki , Bamba Takeshi , Imai Yuuki 
Published: July 2024

AbstractChondrocytes differentiated from mesenchymal stem cells play a role in determining skeletal patterns by ossification. However, the mechanism by which maintenance DNA methylation in chondrocytes regulates differentiation and skeletal formation is unclear. In the Musculoskeletal Knowledge Portal, Dnmt1 was significantly associated with “Height”. Long bones in the limbs of Dnmt1-deficient (Dnmt1ΔPrx1) mice are significantly shortened due to decreased chondrocyte proliferation and accelerated differentiation. Integrated analysis of RNA-Seq and MBD-Seq revealed that inDnmt1ΔPrx1chondrocytes reduced DNA methylation resulted in increased expression of genes related to energy metabolism and to ossification. Metabolomic analyses confirmed that levels of nearly all energy metabolites were increased inDnmt1ΔPrx1chondrocytes. These results indicate that Dnmt1-mediated maintenance DNA methylation governs chondrocyte differentiation by regulating energy metabolism through both gene expression and modulation of metabolite supplies. Taken together, this study suggests that appropriate DNA methylation status in chondrocytes can orchestrate growth plate mineralization and subsequently determine bone length.
Genetic and functional characterization of inherited complex chromosomal rearrangements in a family with multisystem anomalies
Authors: Fang He , Eacker Stephen M. , Wu Yu , Neufeld-Kaiser Whitney , Laurino Mercy , Keel Siobán , Horwitz Marshall S. , Liu Yajuan J. 
Published: July 2024

PurposeComplex chromosomal rearrangements (CCRs) are rare structural variants involving three or more chromosomal breakpoints. Most de novo reported CCRs pose challenges for diagnosis and management. They often require karyotyping, fluorescence in situ hybridization (FISH), and chromosomal microarray analysis (CMA) for clinical diagnosis because of the limitations of each method. Here we report an inherited exceptionally complex CCR involving 4 chromosomes and 11 breakpoints in a family with multisystem anomalies.MethodsWe evaluated the CCRs using karyotyping, FISH, CMA, and two emerging genomic technologies: high-throughput chromosome conformation capture sequencing (Hi-C; aka genomic proximity mapping, GPM) and optical genome mapping (OGM). We also performed functional studies using transcriptome and methylome analyses.ResultsThe proband, who had intellectual disability and immune deficiency, shared CCRs with her unaffected mother involving chromosomes 1, 7, and 11 by karyotyping. However, CMA revealed a duplication and three deletions in the proband in contrast to her mother’s balanced genome. Hi-C (GPM) and OGM detected the CCRs and copy number alterations but also uncovered additional breakpoints at high resolution, including an insertion in 4p and two cryptic rearrangements at 7p. Transcriptome and methylome analyses identified likely biological pathways associated with the proband’s phenotypes.ConclusionCombining cytogenetic and genomic methods provided comprehensive characterization and defined the breakpoints at high resolution in both proband and mother. This underscores the value of novel cytogenetic and genomic techniques in deciphering complex genome rearrangements and the significance of integrative genomic analysis and functional characterization in understanding clinical phenotypes.