bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Functional Order (FunOrder) tool – Identification of essential biosynthetic genes through computational molecular co-evolution
Authors: Vignolle Gabriel A. , Schaffer Denise , Mach Robert L. , Mach-Aigner Astrid R. , Derntl Christian 
Published: February 2021

ABSTRACTSecondary metabolites (SMs) are a vast group of compounds with different structures and properties. Humankind uses SMs as drugs, food additives, dyes, and as monomers for novel plastics. In many cases, the biosynthesis of SMs is catalysed by enzymes whose corresponding genes are co-localized in the genome in biosynthetic gene clusters (BGCs). Notably, BGCs may contain so-called gap genes, that are not involved in the biosynthesis of the SM. Current genome mining tools can identify BGCs but they have problems with distinguishing essential genes from gap genes and defining the borders of a BGC. This can and must be done by expensive, laborious, and time-consuming comparative genomic approaches or co-expression analyses. In this study, we developed a novel tool that allows automated identification of essential genes in a BGC based solely on genomic data. The Functional Order (FunOrder) tool – Identification of essential biosynthetic genes through computational molecular co-evolution – searches for co-evolutionary linked genes in the BGCs. In light of the growing number of genomic data available, this will contribute to the studies of BGCs in native hosts and facilitate heterologous expression in other organisms with the aim of the discovery of novel SMs, including antibiotics and other pharmaceuticals.
Chronic nicotine increases midbrain dopamine neuron activity and biases individual strategies towards reduced exploration in a foraging task
Authors: Dongelmans Malou , Durand-de Cuttoli Romain , Nguyen Claire , Come Maxime , Duranté Etienne K. , Lemoine Damien , Britto Raphael , Yahia Tarek Ahmed , Mondoloni Sarah , Didienne Steve , Bousseyrol Elise , Hannesse Bernadette , Reynolds Lauren M. , Torquet Nicolas , Dalkara Deniz , Marti Fabio , Mourot Alexandre , Naudé Jérémie , Faure Philippe 
Published: February 2021

SummaryLong-term exposure to nicotine alters brain circuits and induces profound changes in decision-making strategies, affecting behaviors both related and unrelated to drug seeking and consumption. Using an intracranial self-stimulation reward-based foraging task, we investigated the impact of chronic nicotine on the trade-off between exploitation and exploration, and the role of ventral tegmental area (VTA) dopamine (DA) neuron activity in decision-making unrelated to nicotine-seeking. Model-based and archetypal analysis revealed a substantial inter-individual variability in decision-making strategies, with mice passively exposed to chronic nicotine visiting more frequently options associated with higher reward probability and therefore shifting toward a more exploitative profile compared to non-exposed animals. We then mimicked the effect of chronic nicotine on the tonic activity of VTA DA neurons using optogenetics, and found that photo-stimulated mice had a behavioral phenotype very close to that of mice exposed to nicotine, suggesting that the dopaminergic control of the exploration/exploitation balance is altered under nicotine exposure. Our results thus reveal a key role of tonic midbrain DA in the exploration/exploitation trade-off and highlight a potential mechanism by which nicotine affects decision-making.
Fat and carbohydrate interact to potentiate food reward in healthy weight but not in overweight or obesity
Authors: Perszyk Emily E. , Hutelin Zach , Trinh Jessica , Kanyamibwa Arsene , Fromm Sophie , Davis Xue S. , Wall Kathryn M. , Flack Kyle D. , DiFeliceantonio Alexandra , Small Dana M. 
Published: February 2021

AbstractPrior work suggests that actual, but not estimated, energy density drives the reinforcing value of food [1,2] and that energy from fat and carbohydrate can interact to potentiate reward [2]. Here we sought to replicate these findings in an American sample and to determine if the effects are influenced by body mass index (BMI). Thirty participants with healthy weight (HW; BMI 21.92 ± 1.77;M±SD) and 30 participants with overweight/obesity (OW/OB; BMI 29.42 ± 4.44) rated pictures of common American snacks in 120-kcal portions for liking, familiarity, frequency of consumption, expected satiety, healthiness, energy content, energy density, and price. Participants then completed an auction task where they bid for the opportunity to consume each food. Snacks contained either primarily carbohydrate, primarily fat, or roughly equal portions of fat and carbohydrate (combo). Replicating prior work, we found that participants with HW bid the most for combo foods in linear mixed model analyses. This effect was not observed among individuals with OW/OB. Additionally, in contrast with previous reports [1,2], our linear regression analyses revealed a negative relationship between the actual energy density of the snacks and bid amount that was mediated by food price. Our findings support altered macronutrient reinforcement in obesity and highlight potential influences of the food environment on the regulation of food reward.
Mutagenesis of the Ammonium TransporterAcAmtReveals a Reproductive Role and a Novel Ammonia-Sensing Mechanism in the Malaria Vector MosquitoAnopheles coluzzii
Authors: Ye Zi , Liu Feng , Ferguson Stephen T. , Baker Adam , Pitts R. Jason , Zwiebel Laurence J. 
Published: February 2021

AbstractAnopheline mosquitoes are the sole vectors of malaria and rely on olfactory cues for host seeking in which ammonia derived from human sweat plays an essential role. To investigate the function of theAnopheles coluzziiammonium transporter (AcAmt) in the mosquito olfactory system, we generated anAcAmtnull mutant line using CRISPR/Cas9.AcAmt-/-mutants displayed a series of novel phenotypes compared with wild-type mosquitoes including significantly lower insemination rates during mating and increased mortality during eclosion. Furthermore,AcAmt-/-males showed significantly lower sugar consumption whileAcAmt-/-females and pupae displayed significantly higher ammonia levels than their wild-type counterparts. Surprisingly, in contrast to previous studies inDrosophilathat revealed that the mutation of the ammonium transporter (DmAmt) induces a dramatic reduction of ammonia responses in antennal coeloconic sensilla, no significant differences were observed across a range of peripheral sensory neuron responses to ammonia and other odorants between wild-type andAcAmt-/-females. Taken together, these data support the existence of a unique ammonia-sensing mechanism in mosquitoes and that the ammonium transporter may be an important molecular target for vector control.Key MessagesMutagenesis ofAn. coluzziiammonium transporterAcAmtfollowed by comprehensive electrophysiological investigation suggest a novel ammonia-sensing pathway inAnophelesmosquitoes.AcAmt-/-mutants displayed significant deficiencies in reproduction and eclosion, which are likely due to elevated ammonia levels and reduced ability of sugar feeding.An. coluzziicoeloconic sensilla primarily detect amines and acids.
Deciphering active prophages from metagenomes
Authors: Kieft Kristopher , Anantharaman Karthik 
Published: February 2021

ABSTRACTTemperate phages (prophages) are ubiquitous in nature and persist as dormant components of host cells (lysogenic stage) before activating and lysing the host (lytic stage). Actively replicating prophages contribute to central community processes, such as enabling bacterial virulence, manipulating biogeochemical cycling, and driving microbial community diversification. Recent advances in sequencing technology have allowed for the identification and characterization of diverse phages, yet no approaches currently exist for identifying if a prophage has activated. Here, we present PropagAtE (Prophage Activity Estimator), an automated software tool for estimating if a prophage is in the lytic or lysogenic stage of infection. PropagAtE uses statistical analyses of prophage-to-host read coverage ratios to decipher actively replicating prophages, irrespective of whether prophages were induced or spontaneously activated. We demonstrate that PropagAtE is fast, accurate and sensitive, regardless of sequencing depth. Application of PropagAtE to prophages from 348 complex metagenomes from human gut, murine gut and soil environments identified distinct spatial and temporal prophage activation signatures, with the highest proportion of active prophages in murine gut samples. Among the soil habitats evaluated (bog, fen and palsa), we identified unique populations of Myxococcales, Acetobacteraceae and Acidimicrobiaceae prophages to be active in fen, palsa and bog habitats, respectively. Within the human gut, 11 prophage populations, some encoding the sulfur metabolism gene cysH or a rhuM-like virulence factor, were consistently present over time but not active. Overall, PropagAtE will facilitate accurate representations of viruses in microbiomes by associating prophages with their active roles in shaping microbial communities in nature.
Whole-genome analysis ofde novoand polymorphic retrotransposon insertions in Autism Spectrum Disorder
Authors: Borges-Monroy Rebeca , Chu Chong , Dias Caroline , Choi Jaejoon , Lee Soohyun , Gao Yue , Shin Taehwan , Park Peter J. , Walsh Christopher A. , Lee Eunjung Alice 
Published: February 2021

AbstractRetrotransposons are dynamic forces in evolutionary genomics and have been implicated as causes of Mendelian disease and hereditary cancer, but their role in Autism Spectrum Disorder (ASD) has never been systematically defined. Here, we report 86,154 polymorphic retrotransposon insertions including >60% not previously reported and 158de novoretrotransposition events identified in whole genome sequencing (WGS) data of 2,288 families with ASD from the Simons Simplex Collection (SSC). As expected, the overall burden ofde novoevents was similar between ASD individuals and unaffected siblings, with 1de novoinsertion per 29, 104, and 192 births for Alu, L1, and SVA respectively, and 1de novoinsertion per 20 births total, while the location of transposon insertions differed between ASD and unaffected individuals. ASD cases showed morede novoL1 insertions than expected in ASD genes, and we also foundde novointronic retrotransposition events in known syndromic ASD genes in affected individuals but not in controls. Additionally, we observed exonic insertions in genes with a high probability of being loss-of-function intolerant, including a likely causative exonic insertion inCSDE1, only in ASD individuals. Althoughde novoretrotransposition occurs less frequently than single nucleotide and copy number variants, these findings suggest a modest, but important, impact of intronic and exonic retrotransposition mutations in ASD and highlight the utility of developing specific bioinformatic tools for high-throughput detection of transposable element insertions.
DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization
Authors: Green Harrison , Durrant Jacob D. 
Published: February 2021

1AbstractLead optimization, a critical step in early-stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve its drug-like properties (e.g., binding affinity). We recently developed DeepFrag, a deep-learning model capable of recommending such modifications. Though a powerful hypothesis-generating tool, DeepFrag is currently implemented in Python and so requires a certain degree of computational expertise. To encourage broader adoption, we have created the DeepFrag browser app, which provides a user-friendly graphical user interface that runs the DeepFrag model in users’ web browsers. The browser app does not require users to upload their molecular structures to a third-party server, nor does it require the separate installation of any third-party software. We are hopeful that the app will be a useful tool for both researchers and students. It can be accessed free of charge, without requiring registration, athttp://durrantlab.com/deepfrag. The source code is also available athttp://git.durrantlab.com/jdurrant/deepfrag-app, released under the terms of the open-source Apache License, Version 2.0.
Aperiodic measures of neural excitability are associated with anticorrelated hemodynamic networks at rest: a combined EEG-fMRI study
Authors: Jacob Michael S. , Roach Brian J. , Sargent Kaia , Mathalon Daniel H. , Ford Judith M. 
Published: February 2021

ABSTRACTThe hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.HIGHLIGHTSPeriodic and aperiodic EEG parameters associated with distinct resting-state networksIncreases in aperiodic power associated with an auditory-salience-cerebellar networkDecreases in aperiodic power associated with prefrontal regionsGlobal neural excitability may reflect stimulus processing or arousal attributable to the uniqueness of the resting-state MR-scanner environment
Water as a reactant in the first step of triosephosphate isomerase catalysis
Authors: Yates Max , Callis Patrik R. 
Published: February 2021

ABSTRACTThe enzyme triosephosphate isomerase (TIM) performs a crucial role in the extraction of energy from glucose, doing so by converting dihydroxyacetone phosphate (DHAP) into glyceraldehyde phosphate, thereby doubling the yield of ATP molecules during glycolysis. The initial step of the mechanism is the seemingly unlikely abstraction of thepro-Rmethylene hydrogen from C1 by a conserved glutamate (Glu165), an assignment that has been both universally accepted yet a much-studied phenomenon for decades. In this work we introduce an alternative mechanism in which water as a strong general base abstracts the carbon proton acting effectively as hydroxide. We posit that strong electric fields associated with the substrate phosphate promote facile autoionization of water trapped near the phosphate dianion of DHAP and Glu165, an example of substrate assisted catalysis. Classical molecular dynamics simulations assert that the closest water oxygen atom is consistently closer to thepro-RH than the carboxylate oxygen atoms of the accepted base Glu165. Our proposal is further supported by quantum computations that confirm the implausibility of abstraction of the methylene hydrogen by glutamate and the ease with which it is abstracted by hydroxide. The necessity of Glu165 for efficient catalysis is attributed to its crucial involvement in trapping the vital water in an environment of high electric fields which promote ionization far more rapidly than in bulk solvent.
PATO: Pangenome Analysis Toolkit
Authors: Fernández-de-Bobadilla Miguel D. , Talavera-Rodríguez Alba , Chacón Lucía , Baquero Fernando , Coque Teresa M. , Lanza Val F. 
Published: February 2021

AbstractMotivationComparative genomics is a growing field but one that will be eventually overtaken by sample size studies and the increase of available genomes in public databases. We present the Pangenome Analysis Toolkit (PATO) designed to simultaneously analyze thousands of genomes using a desktop computer. The tool performs common tasks of pangenome analysis such as core-genome definition and accessory genome properties and includes new features that help characterize population structure, annotate pathogenic features and create gene sharedness networks. PATO has been developed in R to integrate with the large set of tools available for genetic, phylogenetic and statistical analysis in this environment.ResultsPATO can perform the most demanding bioinformatic analyses in minutes with an accuracy comparable to state-of-the-art software but 20–30x times faster. PATO also integrates all the necessary functions for the complete analysis of the most common objectives in microbiology studies. Lastly, PATO includes the necessary tools for visualizing the results and can be integrated with other analytical packages available in R.AvailabilityThe source code for PATO is freely available athttps://github.com/irycisBioinfo/PATOunder the GPLv3 license.Contactval.fernandez@salud.madrid.orgSupplementary informationSupplementary data are available at Bioinformatics online
Larval zebrafish display dynamic learning of aversive stimuli in a constant visual surrounding
Authors: Xu Jiale , Casanave Romelo , Guo Su 
Published: February 2021

AbstractBalancing exploration and anti-predation are fundamental to the fitness and survival of all animal species from early life stages. How these basic survival instincts drive learning remains poorly understood. Here, employing a light/dark preference paradigm with well-controlled luminance history and constant visual surrounding in larval zebrafish, we analyzed intra- and inter-trial dynamics for two behavioral components, dark avoidance and center avoidance. We uncover that larval zebrafish display short-term learning of dark avoidance with initial sensitization followed by habituation; they also exhibit long-term learning that is sensitive to trial interval length. We further show that such stereotyped learning patterns is stimulus specific, as they are not observed for center avoidance. Finally, we demonstrate at individual levels that long-term learning is under homeostatic control. Together, our work has established a novel paradigm to understand learning, uncovered sequential sensitization and habituation, and demonstrated stimulus specificity, individuality, as well as dynamicity in learning.
Surviving hypothermia by ferritin-mediated iron detoxification
Authors: Pekec Tina , Lewandowski Jaroslaw , Komur Alicja A. , Sobanska Daria , Guo Yanwu , Świtońska-Kurkowska Karolina , Frankowski Marcin , Figiel Maciej , Ciosk Rafal 
Published: February 2021

SUMMARYHow animals rewire cellular programs to survive cold is a fascinating problem with potential biomedical implications, ranging from emergency medicine to space travel. Studying a hibernation-like response in the free-living nematodeCaenorhabditis elegans, we uncovered a regulatory axis that enhances the natural resistance of nematodes to severe cold. This axis involves conserved transcription factors, DAF-16/FoxO and PQM-1, which jointly promote cold survival by upregulating FTN-1, a protein related to mammalian Fth1/ferritin. Moreover, we show that inducing expression of Fth1 also promotes cold survival of mammalian neurons, a cell type particularly sensitive to deterioration in hypothermia. Our findings in both animals and cells suggest that FTN-1/Fth1 facilitates cold survival by detoxifying ROS-generating iron species. We finally show that mimicking the effects of FTN-1/Fth1 with drugs protects neurons from cold-induced degeneration, opening a potential avenue to improved treatments of hypothermia.
Genome-scale CRISPR screening in a single mouse liver
Authors: Keys Heather R. , Knouse Kristin A. 
Published: February 2021

SUMMARYA complete understanding of the genetic determinants underlying mammalian physiology and disease is limited by the availability of tools for high-throughput genetic dissection in the living organism. Genome-wide screening using CRISPR-Cas9 has emerged as a powerful method for uncovering the genetic regulation of cellular processes, but the need to stably deliver single guide RNAs to millions of cells has largely restricted its implementation toex vivosystems. There thus remains a pressing need for accessible high-throughput functional genomics in a living organism. Here, we establish genome-wide enrichment and depletion screening in the liver of a single mouse and use this approach to uncover the complete regulation of cellular fitness in a living organism. We uncover regulation of cell fitness not previously identified in cell culture screens, underscoring the power of bringing high-throughput functional genomics into the organism. The approach we developed is accessible, robust, scalable, and adaptable to diverse phenotypes and CRISPR applications. We have hereby established a foundation for high-throughput functional genomics in a living mammal, enabling unprecedented insight into physiology and disease.
A gene expression platform to predict benefit from adjuvant external beam radiation in resected non-small cell lung cancer
Authors: Ahmed Kamran A. , Creelan Ben C. , Peacock Jeffrey , Mellon Eric A , Kim Youngchul , Grass G. Daniel , Perez Bradford A , Rosenberg Stephen A. , Dilling Thomas J. , Eschrich Steven A. , Chiappori Alberto A. , Torres-Roca Javier F. 
Published: February 2021

ABSTRACTBackgroundWe hypothesized that the radiosensitivity index (RSI), would classify non-small cell lung cancer (NSCLC) patients into radioresistant (RR) or radiosensitive (RS).MethodsWe identified resected pathologic stage III NSCLC. For the radiation group (RT) group, at least 45 Gy of external beam radiation was required. mRNA was extracted from primary tumor. The predefined cut-point was the median RSI with a primary endpoint of local control. Similar criteria were then applied to two extramural datasets (E1; E2) with progression free survival as the primary endpoint.ResultsMedian follow-up from diagnosis was 23.5 months (range: 4.8-169.6 months). RSI was associated with time to local failure in the RT group with a two-year rate of local control of 80% and 56% between RS and RR groups, respectively p=0.02. RSI was the only variable found to be significant on Cox local control analysis (HR 2.9; 95% CI: 1.2-8.2; p=0.02). There was no significance of RSI in predicting local control in patients not receiving RT, p=0.48. A cox regression model between receipt of radiotherapy and RSI combining E1 and E2 showed that the interaction term was significant for PFS (3.7; 95% CI 1.4-10; p=0.009). A summary measure combining E1 and E2 showed statistical significance for PFS between RR and RS patients treated with radiotherapy (HR 2.7l; 95% CI 1.3-5.6; p=0.007) but not in patients not treated with radiotherapy (HR 0.94; 95% CI 0.5-1.78; p=0.86).ConclusionsRSI appears to be predictive for benefit from adjuvant radiation. Prospective validation is required.