bluuebunny/crossref_metadata_2025_split huggingface dataset:
Germline-specific role for unconventional components of the γ-tubulin complex inCaenorhabditis elegans
Authors: Haruta Nami , Sumiyoshi Eisuke , Honda Yu , Terasawa Masahiro , Uchiyama Chihiro , Toya Mika , Kubota Yukihiko , Sugimoto Asako 
Published: December 2022

ABSTRACTThe γ-tubulin complex (γTuC) is a widely conserved microtubule nucleator, but some of its components GCP4–6. Here, we identified two γTuC-associated proteins inC. elegans, namely GTAP−1 and −2, for which apparent orthologs were detected only in the genusCaenorhabditis. Their centrosomal localization was interdependent. In earlyC. elegansembryos, whereas the conserved γTuC component MZT-1/MOZART1 was essential for the localization of centrosomal γ-tubulin, depletion of GTAP-1 and/or −2 caused up to 50% reduction of centrosomal γ-tubulin and precocious disassembly of spindle poles during mitotic telophase. In the adult germline, GTAP-1 and GTP-2 contributed to the efficient recruitment of γTuC to the plasma membrane. Depletion of GTAP-1, but not GTAP-2, severely disrupted both the microtubule array and the honeycomb-like structure in the adult germline.We propose that GTAP-1 and −2 are unconventional components of γTuC that contribute to the organization of both centrosomal and non-centrosomal microtubules by targeting the γTuC to specific subcellular sites in a tissue-specific manner.SUMMARY STATEMENTHaruta et al. show that GTAP-1 and −2, two unconventional components of the γ-tubulin complex (γTuC) inC. elegans, contribute to targeting the γTuC to embryonic centrosomes and germ-cell membrane in adults.
Few temporally distributed brain connectivity states predict human cognitive abilities
Authors: Wehrheim Maren H. , Faskowitz Joshua , Sporns Olaf , Fiebach Christian J. , Kaschube Matthias , Hilger Kirsten 
Published: December 2022

AbstractHuman functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N= 263,p< .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N= 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
High-throughput profiling of drug interactions in Gram-positive bacteria
Authors: Cacace Elisabetta , Kim Vladislav , Knopp Michael , Tietgen Manuela , Brauer-Nikonow Amber , Inecik Kemal , Mateus André , Milanese Alessio , Mårli Marita Torrissen , Mitosch Karin , Selkrig Joel , Brochado Ana Rita , Kuipers Oscar P. , Kjos Morten , Zeller Georg , Savitski Mikhail M. , Göttig Stephan , Huber Wolfgang , Typas Athanasios 
Published: December 2022

AbstractDrug combinations present a powerful strategy to tackle antimicrobial resistance, but have not been systematically tested in many bacterial species. Here, we used an automated high-throughput setup to profile ∼ 8000 combinations between 65 antibacterial drugs in three Gram-positive species: the model species,Bacillus subtilisand two prominent pathogens,Staphylococcus aureusandStreptococcus pneumoniae. Thereby, we recapitulate previously known drug interactions, but also identify ten times more interactions than previously reported in the pathogenS. aureus, including two synergies that were also effective in multi-drug resistant clinicalS. aureusisolatesin vitroandin vivo. Interactions were largely species-specific and mostly synergistic for drugs targeting the same cellular process, as observed also for Gram-negative species1. Yet, the dominating synergies are clearly distinct between Gram-negative and Gram-positive species, and are driven by different bottlenecks in drug uptake and vulnerabilities of their cell surface structures. To further explore interactions of commonly prescribed non-antibiotic drugs with antibiotics, we tested 2728 of such combinations inS. aureus, detecting a plethora of unexpected antagonisms that could compromise the efficacy of antimicrobial treatments in the age of polypharmacy. We uncovered even more synergies than antagonisms, some of which we could demonstrate as effective combinations in vivo against multi-drug resistant clinical isolates. Among them, we showed that the antiaggregant ticagrelor interferes with purine metabolism and changes the surface charge ofS. aureus,leading to strong synergies with cationic antibiotics. Overall, this exemplifies the untapped potential of approved non-antibacterial drugs to be repurposed as antibiotic adjuvants. All data can be browsed through an interactive interface (https://apps.embl.de/combact/).
Neural Networks beyond explainability: Selective inference for sequence motifs
Authors: Villié Antoine , Veber Philippe , De Castro Yohann , Jacob Laurent 
Published: December 2022

AbstractOver the past decade, neural networks have been successful at making predictions from biological sequences, especially in the context of regulatory genomics. As in other fields of deep learning, tools have been devised to extract features such as sequence motifs that can explain the predictions made by a trained network. Here we intend to go beyond explainable machine learning and introduce SEISM, a selective inference procedure to test the association between these extracted features and the predicted phenotype. In particular, we discuss how training a one-layer convolutional network is formally equivalent to selecting motifs maximizing some association score. We adapt existing sampling-based selective inference procedures by quantizing this selection over an infinite set to a large but finite grid. Finally, we show that sampling under a specific choice of parameters is sufficient to characterize the composite null hypothesis typically used for selective inference—a result that goes well beyond our particular framework. We illustrate the behavior of our method in terms of calibration, power and speed and discuss its power/speed trade-off with a simpler data-split strategy. SEISM paves the way to an easier analysis of neural networks used in regulatory genomics, and to more powerful methods for genome wide association studies (GWAS).
Dystrophin is a mechanical tension modulator
Authors: Hofemeier Arne D. , Muenker Till M. , Herkenrath Fabian , Ristau Mariam , Brandt Matthias , Shahriyari Mina , Tiburcy Malte , Zimmermann Wolfram H. , Lenz Christof , Mamchaoui Kamel , Bigot Anne , Gilbert Penney M. , Betz Timo 
Published: December 2022

AbstractDuchenne muscular dystrophy (DMD) represents the most common inherited muscular disease, where increasing muscle weakness leads to loss of ambulation and premature death. DMD is caused by mutations in the dystrophin gene, and is known to reduce the contractile capacity of muscle tissue bothin vivo, and also in reconstituted systemsin vitro. However, these observations result from mechanical studies that focused on stimulated contractions of skeletal muscle tissues. Seemingly paradoxical, upon evaluating bioengineered skeletal muscles produced from DMD patient derived myoblasts we observe an increase in unstimulated contractile capacity that strongly correlates with decreased stimulated tissue strength, suggesting the involvement of dystrophin in regulating the baseline homeostatic tension level of tissues. This was further confirmed by comparing a DMD patient iPSC line directly to the gene-corrected isogenic control cell line. From this we speculate that the protecting function of dystrophin also supports cellular fitness via active participation in the mechanosensation to achieve and sustain an ideal level of tissue tension. Hence, this study provides fundamental novel insights into skeletal muscle biomechanics and into a new key mechanical aspect of DMD pathogenesis and potential targets for DMD drug development: increased homeostatic tissue tension.
Shortwave-Infrared Line-Scan Confocal Microscope for Deep Tissue Imaging in Intact Organs
Authors: Lingg Jakob G. P. , Bischof Thomas S. , Arús Bernardo A. , Cosco Emily D. , Sletten Ellen M. , Rowlands Christopher J. , Bruns Oliver T. , Chmyrov Andriy 
Published: December 2022

AbstractImaging at wavelengths beyond the visible spectrum enables imaging depths of hundreds of microns in intact tissue, making this attractive for volumetric imaging applications. The development of fluorophores with photoemission beyond 1000nm provide the opportunity to develop novel fluorescence microscopes sensitive to those wavelengths. Here, we present a shortwave-infrared line-scan confocal microscope that is capable of deep imaging of biological specimens, as demonstrated by visualization of labelled glomeruli in a fixed uncleared kidney at depths beyond 400 μm. We also show imaging of brain vasculature labelled with the near-infrared organic dye indocyanine green, the shortwave-infrared organic dye Chrom7, and rare earth-doped nanoparticles, thus encompassing the entire spectrum detectable by a typical shortwave-infrared sensitive InGaAs detector.
The origin of floral quartet formation - Ancient exon duplications shaped the evolution of MIKC-type MADS-domain transcription factor interactions
Authors: Rümpler Florian , Tessari Chiara , Gramzow Lydia , Gafert Christian , Blohs Marcus , Theißen Günter 
Published: December 2022

ABSTRACTDuring development of flowering plants, some MIKC-type MADS-domain transcription factors (MTFs) exert their regulatory function as heterotetrameric complexes bound to two sites on the DNA of target genes. This way they constitute „floral quartets“ or related „floral quartet-like complexes“ (FQCs), involving a unique multimeric system of paralogous protein interactions. Tetramerisation of MTFs is brought about mainly by interactions of keratin-like (K) domains. The K-domain associated with the more ancient DNA-binding MADS-domain during evolution in the stem group of extant streptophytes (charophyte green algae + land plants). However, whether this was sufficient for MTF tetramerisation and FQC formation to occur, remains unknown. Here, we provide biophysical and bioinformatic data indicating that the ancestral MTFs were not able to form FQCs. According to our data, FQC formation originated in the stem group of land plants in a sublineage of MIKC-type genes termed MIKCC-type genes. In the stem group of this gene lineage, the duplication of the most downstream exon encoding the K-domain led to a C-terminal elongation of the second K-domain helix, thus generating the tetramerisation interface found in extant MIKCC-type proteins. In the stem group of the sister lineage of the MIKCC-type genes, termed MIKC*-type genes, the duplication of two other exons of the K-domain occurred, extending the K-domain at its N-terminal end. Our data indicate that this structural change prevents heterodimerisation between MIKCC-type and MIKC*-type proteins. This way, two largely independent gene regulatory networks could be established, featuring MIKCC-type or MIKC*-type proteins, respectively, that control different aspects of plant development.
Ecology-relevant bacteria drive the evolution of host antimicrobial peptides in Drosophila
Authors: Hanson M.A. , Grollmus L. , Lemaitre B. 
Published: December 2022

AbstractAntimicrobial peptides are host-encoded immune effectors that combat pathogens and shape the microbiome in plants and animals. However, little is known about how the host antimicrobial peptide repertoire is adapted to its microbiome. Here we characterize the function and evolution of theDiptericinantimicrobial peptide family of Diptera. Using mutations affecting the twoDiptericins(Dpt) ofDrosophila melanogaster, we reveal the specific role ofDptAfor the pathogenProvidencia rettgeriandDptBfor the gut mutualistAcetobacter. Strikingly, presence ofDptA-orDptB-like genes across Diptera correlates with the presence ofProvidenciaandAcetobacterin their environment. Moreover,DptA-andDptB-like sequence predicts host resistance against infection by these bacteria across the genusDrosophila. Our study explains the evolutionary logic behind the bursts of rapid evolution of an antimicrobial peptide family, and reveals how the host immune repertoire adapts to changing microbial environments.
The importance of reaction norms in dietary restriction and ageing research
Authors: Simons Mirre J P , Dobson Adam J 
Published: December 2022

AbstractAgeing research has progressed rapidly through our ability to modulate the ageing process. Pharmacological and dietary treatments can increase lifespan and have been instrumental in our understanding of the mechanisms of ageing. Recently, several studies have reported genetic variance in response to these anti-ageing interventions, questioning their universal application and making a case for personalised medicine in our field. As an extension of these findings the response to dietary restriction was found to not be repeatable when the same genetic mouse lines were retested. We show here that this effect is more widespread with the response to dietary restriction also showing low repeatability across genetic lines in the fly (Drosophila melanogaster). We further argue that variation in reaction norms, the relationship between dose and response, can explain such conflicting findings in our field. We simulate genetic variance in reaction norms and show that such variation can: 1) lead to over- or under-estimation of treatment responses, 2) dampen the response measured if a genetically heterogeneous population is studied, and 3) illustrate that genotype-by-dose-by-environment interactions can lead to low repeatability of DR and potentially other anti-ageing interventions. We suggest that putting experimental biology and personalised geroscience in a reaction norm framework will aid progress in ageing research.
DNA primase large subunitis an essential plant gene for geminiviruses, putatively priming viral ss-DNA replication
Authors: Siskos Lampros , Antoniou Maria , Riado Jose , Enciso Montserrat , Garcia Carlos , Liberti Daniele , Esselink Danny , Baranovskiy Andrey G. , Tahirov Tahir H. , Visser Richard G.F. , Kormelink Richard , Bai Yuling , Schouten Henk J. 
Published: December 2022

AbstractThe family ofGeminiviridaeconsists of more than 500 circular single-stranded (ss) DNA viral species that can infect numerous dicot and monocot plants. Geminiviruses replicate their genome in the nucleus of a plant cell, taking advantage of the host’s DNA replication machinery. For converting their DNA into double-stranded DNA, and subsequent replication, these viruses rely on host DNA polymerases. However, the priming of the very first step of this process, i.e. the conversion of incoming circular ssDNA into a dsDNA molecule, has remained elusive for almost 30 years. In this study, sequencing of melon (Cucumis melo) accession K18 carrying the Tomato leaf curl New Delhi virus (ToLCNDV) recessive resistance quantitative trait locus (QTL) in chromosome 11, and analyses of DNA sequence data from 100 melon genomes, showed a conservation of a shared mutation in theDNA Primase Large subunit(PRiL) of all accessions that exhibited resistance upon a challenge with ToLCNDV. Silencing of (native)Nicotiana benthamiana PriLand subsequent challenging with three different geminiviruses showed a severe reduction in titers of all three viruses, altogether emphasizing an important role ofPRiLin geminiviral replication. A model is presented explaining the role ofPriLduring initiation of geminiviral DNA replication, i.e. as a regulatory subunit of primase that generates an RNA primer at the onset of DNA replication in analogy toDNA Primase-mediated initiation of DNA replication in all living organisms.
C-ToMExO: Learning Cancer Progression Dynamics from Clonal Composition of Tumors
Authors: Neyshabouri Mohammadreza Mohaghegh , Dimitrakopoulou Smaragda , Lagergren Jens 
Published: December 2022

AbstractCancer is an evolutionary process involving the accumulation of somatic mutations in the genome. The tumor’s evolution is known to be highly influenced by specific somatic mutations in so-called cancer driver genes. Cancer progression models are computational tools used to infer the interactions among cancer driver genes by analyzing the pattern of absence/presence of mutations in different tumors of a cohort. In an abundance of subclonal mutations, discarding the heterogeneity of tumors and investigating the interrelations among the driver genes solely based on tumor-level data can result in misleading interpretations. In this paper, we introduce a computational approach to infer cancer progression models from the clone-level data gathered from a cohort of tumors. Our method leverages the rich clone-level data to identify the patterns of interactions among cancer driver genes and produce significantly more robust and reliable cancer progression models. Using a novel efficient Markov Chain Monte Carlo inference algorithm, our method provides outstanding scalability to the rapidly increasing size of available datasets. Using an extensive set of synthetic data experiments, we demonstrate the performance of our inference method in recovering the generative progression models. Finally, we present our analysis of two sub-types of lung cancer using biological multi-regional bulk data.
Unraveling the therapeutic mechanism of deep-brain stimulation
Authors: van den Boom Bastijn J.G. , Fernandez Alfredo Elhazaz , Rasmussen Peter A. , van Beest Enny H. , Parthasarathy Aishwarya , Denys Damiaan , Willuhn Ingo 
Published: December 2022

ABSTRACTDeep-brain stimulation (DBS) is an effective treatment for patients suffering from otherwise therapy-resistant psychiatric disorders, including obsessive-compulsive disorder. Modulation of cortico-striatal circuits has been suggested as a mechanism of action. To gain mechanistic insight, we monitored neuronal activity in cortico-striatal regions in a mouse model for compulsive behavior, while systematically varying clinically-relevant parameters of internal-capsule DBS. DBS showed dose-dependent effects on both brain and behavior: An increasing, yet balanced, number of excited and inhibited neurons was recruited, scattered throughout cortico-striatal regions, while compulsive grooming decreased. Such neuronal recruitment did not alter basic brain function such as resting-state activity, and only occurred in awake animals, indicating a dependency on network activity. In addition to these widespread effects, we observed specific involvement of the medial orbitofrontal cortex in therapeutic outcomes, which was corroborated by optogenetic stimulation. Together, our findings provide mechanistic insight into how DBS exerts its therapeutic effects on compulsive behaviors.
A practical bacterial biodosimetry procedure to assess performance of lab-scale flow-through ultraviolet water disinfection reactors
Authors: Sperle Philipp , Khan Mohammad S. , Drewes Jörg E. , Wurzbacher Christian 
Published: December 2022

ABSTRACTBiodosimetry can be used to estimate the fluence of a reactor by determining its ability to inactivate a challenge organism. Especially for small-scale flow-through reactors, inconsistent procedures are reported for bacterial cells. This study aims to develop a standardized, simple procedure for bacterial biodosimetry in flow-through UV systems with relevant biofilm forming bacteria in order to evaluate biofouling control by UV. In particular, the challenge organism, the type of experimental setup and the execution of single steps during biodosimetry with bacterial cells can cause largely deviating results. Since previous work was restricted to model organism, which are not relevant for biofouling, we critically reevaluated all reported steps for the biofilm formingAquabacterium citratiphilumand identified three main factors for biodosimetry reproducibility in flow-through systems: Protractions of cells from negative controls can heavily impact inactivation efficacy, but can be reduced by ordering samples by decreasing fluence. Further, to avoid photo repair, samples must be processed under red light only. Lastly, biofilm forming bacteria can strongly absorb on plastic labware, which requires counter measures in form of special labware and the addition of surfactants. Overall, the developed protocol provides a biodosimetry standardization for bacterial cells of flow-through systems, facilitating reproducibility and transferability of results between studies that use bacterial cells as challenge organism.SynopsisBiodosimetry is used to characterize performance of flow-through ultraviolet reactors, but artifacts can occur if not addressed properly.
Individual differences in the effects of salience and reward on impulse control and action selection
Authors: Schutte I. , Schutter D.J.L.G. , Kenemans J.L. 
Published: December 2022

AbstractImpulse control and adequate decision making are vital functions when it comes to detection and adherence to societal rules, especially in critical circumstances such as the Covid pandemic. In the current study we tested the hypothesis that increasing the salience of environmental cues would be most effective in improving impulse control, as assessed in a stop-signal task, in subjects with low environmental susceptibility as indexed by low pre-stimulus EEG alpha power. In addition, we anticipated that an external-reward intervention improves performance during a Go/No go task, especially in individuals with low task-induced motivation as indexed by low theta/ beta power ratios. High salience of stop signals enhanced stopping performance but there was no difference in responsivity to the salience intervention between participants with high and low EEG alpha power. Individuals with low theta/ beta power ratios responded more accurately when rewards were at stake. Together these results suggest that increasing the salience of external cues may help impulse control in general, whereas the effectiveness of external-reward interventions is higher in individuals with low task-induced motivation.