bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthetic lethality in large-scale integrated metabolic and regulatory network models of human cells
Authors: Barrena Naroa , Valcárcel Luis V. , Olaverri-Mendizabal Danel , Apaolaza Iñigo , Planes Francisco J. 
Published: January 2023

AbstractSynthetic lethality (SL) is a promising concept in cancer research. A wide array of computational tools has been developed to predict and exploit synthetic lethality for the identification of tumour-specific vulnerabilities. Previously, we introduced the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to SL for genome-scale metabolic networks. The major challenge in our gMCS framework is to go beyond metabolic networks and extend existing algorithms to more complex protein-protein interactions. We present here a novel computation approach that adapts our previous gMCS formulation to incorporate linear regulatory pathways. Our novel approach is applied to calculate gMCSs in integrated metabolic and regulatory models of human cells. In particular, we integrate the most recent genome-scale metabolic network, Human1, with 3 different regulatory network databases: Omnipath, Dorothea and TRRUST. Based on the computed gMCSs and transcriptomic data, we detail new essential genes and their associated synthetic lethals for different cancer cell lines. The performance of the different integrated models is assessed with available large-scalein-vitrogene silencing data. Finally, we discuss the most relevant gene essentiality predictions based on published literature in cancer research.
Prefrontal Cortex Encodes Value Pop-out in Visual Search
Authors: Abbaszadeh Mojtaba , Panjehpour Armin , Alemohammad Mohammad Amin , Ghavampour Ali , Ghazizadeh Ali 
Published: January 2023

AbstractRecent evidence shows that long-term object value association can lead to efficient visual search. However, the neural mechanism of this value pop-out has yet to be understood. Given the known role of the ventrolateral prefrontal cortex (vlPFC) in visual search and value memory, we recorded its single-unit activity (n=526) in two macaque monkeys while they engaged in the value-driven search. Monkeys had to determine whether a high-value target was present within a variable number of low-value objects. Interestingly, differential neural firing, as well as gamma-band power, indicated the presence of a target within ∼150ms of display onset. This differential activity was negatively correlated with search time and became less display size-dependent for more efficient searches. On the other hand, neural firing and its variability were higher in inefficient searches. These findings reveal the neural code within vlPFC for rapid detection of valuable targets, which can be crucial for animals faced with competition.Significance StatementSearch for rewarding objects is ubiquitous and crucial for animals and humans alike. Up until recently, it was thought that visual search for valuable targets that were otherwise not distinct by low-level features should be serial and slow. Contrary to this belief, we showed that given sufficient reward training, valuable objects can be found efficiently in search suggesting a value pop-out neural mechanism. Importantly, we reveal the neural activity in the prefrontal cortex (PFC) to be predictive of the degree of value-driven search efficiency. Given the role of PFC in object value memory, these results show how PFC can translate such memories to emulate the parallel processing of visual information independent of low-level visual features.
Two conserved vocal central pattern generators broadly tuned for fast and slow rates generate species-specific vocalizations inXenopusclawed frogs
Authors: Yamaguchi Ayako , Peltier Manon 
Published: January 2023

ABSTRACTAcross phyla, species-specific vocalizations are used by males to attract females. Functional analyses of the neural circuitry underlying behavior have been difficult, particularly in vertebrates. However, using anex vivobrain preparation that produces fictive vocalizations, we previously identified anatomically distinct fast and slow central pattern generators (CPGs) that drive the fast and slow clicks of male courtship calls in male African clawed frogs,Xenopus laevis. To gain insight into the evolution of neural circuits underlying courtship calls, we extended this approach to four additional species. Here, we show that although the exact rate and duration of the clicks are unique to each species, fast and slow CPGs identified in maleX. laevisare conserved across species. Further, we show that the development of fast CPGs depends on testosterone in a species-specific manner: testosterone facilitates the development of fast CPGs in a species with a courtship call containing fast clicks, but not in a species with a courtship call made entirely of slow clicks. Finally, we showed that, unlike other vestigial neural circuits that remain latent, the fast CPGs are not inherited by all species; rather, they are possessed only by the species that produce fast clicks. The results suggest that species-specific calls of the genusXenopushave evolved by utilizing conserved fast or slow CPGs that are broadly tuned to generate fast or slow trains of clicks, the development of which appear to be regulated by a strategic expression of testosterone receptors in the brain of each species.
Natural variation in salt-induced root growth phases and their contribution to root architecture plasticity
Authors: van Zelm Eva , Bugallo-Alfageme Silvia , Behrouzi Pariya , Meyer A. Jessica , Testerink Christa , Gommers Charlotte M.M. 
Published: January 2023

AbstractDuring salt stress, the root system architecture of a plant is important for survival. Different accessions ofArabidopsis thalianahave adopted different strategies in remodeling their root architecture during salt stress. Salt induces a multiphase growth response in roots, consisting of a stop phase, quiescent phase, recovery phase and eventually a new level of homeostasis. We explored natural variation in the length of and growth rate during these phases in both main and lateral roots and find that some accessions lack the quiescent phase. Using mathematical models and correlation-based network, allowed us to correlate dynamic traits to overall root architecture and discover that both the main root growth rate during homeostasis and lateral root appearance are the strongest determinants of overall root architecture. In addition, this approach revealed a trade-off between investing in main or lateral root length during salt stress. By studying natural variation in high-resolution temporal root growth using mathematical modeling, we gained new insights in the interactions between dynamic root growth traits and we identified key traits that modulate overall root architecture during salt stress.Summary statementBy studying natural variation in salt-induced root growth phases inArabidopsis, we show that main root growth rate during homeostasis and lateral root appearance contribute most to root architecture and we reveal a trade-off between investing in main and lateral root growth during salt stress.
N-of-one differential gene expression without control samples using a deep generative model
Authors: Prada-Luengo Iñigo , Schuster Viktoria , Liang Yuhu , Terkelsen Thilde , Sora Valentina , Krogh Anders 
Published: January 2023

AbstractDifferential gene expression analysis of bulk RNA sequencing data plays a major role in the diagnosis, prognosis, and understanding of disease. Such analyses are often challenging due to a lack of good controls and the heterogeneous nature of the samples. Here, we present a deep generative model that can replace control samples. The model is trained on RNA-seq data from healthy tissues and learns a low-dimensional representation that clusters tissues very well without supervision. When applied to cancer samples, the model accurately identifies representations close to the tissue of origin. We interpret these inferred representations as the closest normal to the disease samples and use the resulting count distributions to perform differential expression analysis ofsinglecancer sampleswithoutcontrol samples. In a detailed analysis of breast cancer, we demonstrate how our approach finds subtype-specific cancer driver and marker genes with high specificity and greatly outperforms the state-of-the-art method in detecting differentially expressed genes, DESeq2. We further show that the significant genes found using the model are highly enriched within cancer-specific driver genes across different cancer types. Our results show that thein silicoclosest normal provides a more favorable comparison than control samples.
Lateral gene transfer leaves lasting traces in Rhizaria
Authors: van Hooff Jolien J.E. , Eme Laura 
Published: January 2023

AbstractEukaryotic lineages acquire numerous prokaryotic genes via lateral gene transfer (LGT). However, LGT in eukaryotes holds many unknowns, especially its frequency, its long-term impact, and the importance of eukaryote-to-eukaryote LGT. LGT, and genome evolution in general, has not been rigorously studied in Rhizaria, which is a large and diverse eukaryotic clade whose members are mostly free-living, single-celled phagotrophs. We here explore LGT across Rhizaria since their origin until modern-day representatives, using a systematic, phylogenetic approach. On average, 30% of the genes present in current-day rhizarian genomes have originated through LGT at some point during the history of Rhizaria, which emerged about one billion years ago. We show that while LGTs are outnumbered by gene duplications, transferred genes themselves duplicate frequently, thereby amplifying their impact on the recipient lineage. Strikingly, eukaryote-derived LGTs were more prevalent than prokaryotic ones, and carry distinct signatures. Altogether, we here quantitatively and qualitatively reveal how LGT affected an entire eukaryotic phylum, thereby further demystifying LGT in eukaryotes.
Spindle-locked ripples mediate memory reactivation during human NREM sleep
Authors: Schreiner Thomas , Griffiths Benjamin J. , Kutlu Merve , Vollmar Christian , Kaufmann Elisabeth , Quach Stefanie , Remi Jan , Noachtar Soheyl , Staudigl Tobias 
Published: January 2023

AbstractMemory consolidation relies on the reactivation of previous experiences during sleep. The precise interplay of sleep-related oscillations (slow oscillations, spindles and ripples) is thought to coordinate the information flow between relevant brain areas, with ripples mediating memory reactivation. However, in humans empirical evidence for a role of ripples in memory reactivation is lacking. Here, we investigated the relevance of sleep oscillations and specifically ripples for memory reactivation during human sleep using targeted memory reactivation (TMR). Intracranial electrophysiology in epilepsy patients and scalp EEG in healthy participants revealed that elevated levels of SO-spindle activity promoted the read-out of TMR induced memory reactivation. Importantly, spindle-locked ripples recorded intracranially from the medial temporal lobe were found to be instrumental for memory reactivation to unfold during non-rapid eye movement (NREM) sleep. Our findings establish ripples as key-oscillation in human systems consolidation and emphasize the importance of the coordinated interplay of the cardinal sleep oscillations.
Overlap in the cortical representation of hand and forearm muscles as assessed by navigated TMS
Authors: Jin Fang , Bruijn Sjoerd M. , Daffertshofer Andreas 
Published: January 2023

AbstractThe representation of upper limb muscles in the motor cortex is complex. It contains areas of excitability that may overlap between muscles. We expected the cortical representations of synergistic muscle pairs to overlap more than those of non-synergistic muscles. To detail this, we used navigated transcranial magnetic stimulation in eight hand and forearm muscles of twenty healthy participants. We transformed the cortical representations of muscles to a template MRI to allow for group analysis. We found that the amount of overlap in cortical representations differed significantly between within-hand and within-forearm muscle combinations. Most synergistic muscle pairs, both within the hand, within the forearm and between them, had a larger overlap than non-synergistic muscle pairs. Our study supports the largely overlapping nature of cortical representations of upper limb muscles. We can particularly underscore that the overlap is elevated in muscles that usually act in a synergistic manner.
Conformational Stability of Peroxidase from latex ofArtocarpus lakoocha: Influence of pH, Chaotropes, and Temperature
Authors: Sonkar Kirti Shila , Pachauri Manendra , Kumar Amit , Jagannadham Medicherla V. 
Published: January 2023

AbstractA novel heme-peroxidase has been extracted from the latex of the medicinal plantArtocarpus lakoocha (A. lakoocha), known for its potential anti-inflammatory and wound healing properties. To study its stability, structure, and dynamics, this protein was analyzed using far-UV circular dichroism, fluorescence spectroscopy, and activity measurements. The results demonstrated the presence of three folding states: thenative state(N) at neutral pH,intermediate statesincluding molten globule (MG) at pH 2 and acid-unfolded (UA) at pH 1.5 or lower, and acid-refolded (A) at pH 0.5, along with alkaline denatured (UB) at pH 8-12 and the thirddenatured state(D) at GuHCl concentrations exceeding 5 M. Absorbance studies indicated the presence of free heme in the pH range of 1-2. The protein showed stability and structural integrity across a wide pH range (3-10), temperature (70 °C), and high concentrations of GuHCl (5 M) and urea (8 M). This study is the first to report multiple ‘partially folded intermediate states’ ofA. lakoochaperoxidase, with varying amounts of secondary structure, stability, and compactness. These results demonstrate the high stability ofA. lakoochaperoxidase and its potential for biotechnological and industrial applications, making it a valuable model system for further studies on its structure-function relationship.
Heat dissipation from photosynthesis contributes to maize thermoregulation under suboptimal temperature conditions
Authors: Sobejano-Paz Verónica , Mo Xingguo , Liu Suxia , Mikkelsen Teis Nørgaard , He Lihong , Jin Hongxiao , García Mónica 
Published: January 2023

AbstractThe extent to which plants thermoregulate to maintain relatively stable metabolic function in response to gradual and rapid temperature changes that jeopardize crop production is unclear. Maize thermoregulation was investigated based on leaf temperature (TL) measurements and its relationship with photochemistry and stomatal conductance (gs) under dry and wet soil scenarios. Seasonal climatology was simulated in a growth chamber according to Beijing’s climatology with extreme “hot days” based on historical maxima.Maize behaved as a limited homeotherm, an adaptive strategy to maintain photosynthesis around optimum temperatures (Topt). Plants on drier soil had lower thermoregulatory capacity, with reduced gs, photosynthesis and transpiration, which impacted final yields, despite acclimation with a higher Toptto sustained stress. On hot days thermoregulation was affected by heat stress and water availability, suggesting that strong and frequent heatwaves will reduce crop activity although increased temperatures could bring photosynthesis closer to Toptin the region.We propose a novel mechanism to explain thermoregulation from the contribution of heat dissipation via non-photochemical quenching (NPQ) to TL, supporting our hypothesis that NPQ acts as a negative feedback mechanism from photosynthesis by increasing TLin suboptimal conditions. These results could help to design adaptation strategies based on deficit irrigation.HighlightMaize was able to maintain leaf temperatures in narrower ranges than air temperatures by dissipating sunlight not used in photosynthesis as heat energy with a key role of transpiration cooling to sustain optimum photosynthesis temperature.
Rapid genome functional annotation pipeline anchored to the House sparrow (Passer domesticus, Linnaeus 1758) genome reannotation
Authors: Magallanes-Alba Melisa Eliana , Barricalla Agustín , Rego Natalia , Brun Antonio , Karasov William H. , Caviedes-Vidal Enrique 
Published: January 2023

AbstractHouse sparrow (Passer domesticus) is an important avian model for both laboratory and field-based studies of evolutionary genetics, development, neurobiology, physiology, behavior, and ecology. The current annotation of theP. domesticusgenome is available at Ensembl Rapid Release site, which currently only focuses on gene set building. Here, we provide the first functional reannotation of theP. domesticusgenome based on enrichment with intestinal Illumina RNA-Seq libraries. This revised annotation describes 38592 transcripts, compared to 23574 currently for Ensembl, and 14717 predicted protein-coding genes, with 96.4% complete Passeriformes lineage BUSCOs. A key improvement in this revised annotation is the definition of untranslated region (UTR) sequences, with 82.7% and 93.8% of transcripts containing 5’ and 3’ UTRs, respectively. Our reannotation highlights the benefits to genome annotation improvement when additional specific RNA-Seq data is available for analysis and rapid data throughput (>200 Mb h−1) is used.
LIMBARE: an Advanced Linear Mixed-effects Breakpoint Analysis with Robust Estimation Method with Applications to Longitudinal Ophthalmic Studies
Authors: Lee TingFang , Schuman Joel S , Ramos Cadena Maria de los Angeles , Zhang Yan , Wollstein Gadi , Hu Jiyuan 
Published: January 2023

AbstractPurposeBroken stick analysis is a widely used approach for detecting unknown breakpoints where association between measurements is non-linear. We propose LIMBARE, an advancedlinearmixed-effectsbreakpointanalysis withrobustestimation, especially designed for longitudinal ophthalmic studies. LIMBARE accommodates repeated measurements from both eyes and overtime, and effectively address the presence of outliers.MethodsThe model setup of LIMBARE and computing algorithm for point and confidence interval estimates of the breakpoint was introduced. The performance of LIMBARE and other competing methods was assessed via comprehensive simulation studies and application to a longitudinal ophthalmic study with 216 eyes (145 subjects) followed for an average of 3.7±1.3 years to examine the longitudinal association between structural and functional measurements.ResultsIn simulation studies, LIMBARE showed the smallest bias and mean squared error (MSE) for estimating the breakpoint, with empirical coverage probability of corresponding CI estimate closest to the nominal level for scenarios with and without outlier data points. In the application to the longitudinal ophthalmic study, LIMBARE detected two breakpoints between visual field mean deviation (MD) and retinal nerve fiber layer thickness (RNFL) and one breakpoint between MD and cup to disc ratio (CDR), while the cross-sectional analysis approach only detected one and none, respectively.ConclusionsLIMBARE enhances breakpoint estimation accuracy in longitudinal ophthalmic studies, while cross-sectional analysis approach is not recommended for future studies.Translational RelevanceOur proposed method and companion software R package provides a valuable computational tool for advancing longitudinal ophthalmology research and exploring the association relationships between ophthalmic variables.
FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries
Authors: Montepietra Daniele , Tesei Giulio , Martins João M. , Kunze Micha B. A. , Best Robert B. , Lindorff-Larsen Kresten 
Published: January 2023

AbstractHere, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available atgithub.com/KULL-Centre/FRETpredictand as a Python PyPI package atpypi.org/project/FRETpredict.Author SummaryWe present FRETpredict, an open-source software to calculate FRET observables from protein structures. Using a previously developed Rotamer Library Approach, FRETpredict helps place multiple conformations of the selected FRET probes at the labeled sites, and use these to calculate FRET efficiencies. Through several case studies, we illustrate the ability of FRETpredict to interpret experimental results and validate protein conformations. We also explain a methodology for generating new rotamer libraries of FRET probes of interest.
A quantitative approach to measure and predict microbiome response to antibiotics
Authors: Tu Vince , Ren Yue , Tanes Ceylan , Mukhopadhyay Sagori , Daniel Scott G. , Li Hongzhe , Bittinger Kyle 
Published: January 2023

AbstractBackgroundAlthough antibiotics induce sizable perturbations in the human microbiome, we lack a systematic and quantitative method to measure and predict the microbiome’s response to specific antibiotics. Here, we introduce such a method, which takes the form of a Microbiome Response Index (MiRIx) for each antibiotic. Antibiotic-specific MiRIx values quantify the overall susceptibility of the microbiota to an antibiotic, based on databases of bacterial phenotypes and published data on intrinsic antibiotic susceptibility.ResultsWe applied our approach to five published microbiome studies that carried out antibiotic interventions with vancomycin, metronidazole, ciprofloxacin, amoxicillin, and doxycycline. We show how MiRIx can be used in conjunction with existing microbiome analytical approaches to gain a deeper understanding of the microbiome response to antibiotics. Finally, we generate antibiotic response predictions for the oral, skin, and gut microbiome in healthy humans.ConclusionsOur approach is implemented as open-source software and is readily applied to microbiome data sets generated by 16S rRNA marker gene sequencing or shotgun metagenomics.