bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-resolution structure of a mercury cross-linked ZIP metal transporter reveals delicate motions and metal relay for regulated zinc transport
Authors: Zhang Tuo , Zhang Yao , Sui Dexin , Hu Jian 
Published: April 2023

AbstractZrt-/Irt-like protein (ZIP) divalent metal transporters play a central role in maintaining trace element homeostasis. The prototypical ZIP fromBordetella bronchiseptica(BbZIP) is an elevator-type transporter, but the dynamic motions and detailed transport mechanism remain to be elucidated. Here, we report a high-resolution crystal structure of a mercury-crosslinked BbZIP variant at 1.95 Å, revealing an upward rotation of the transport domain in the new inward-facing conformation and a water-filled metal release channel that is divided into two parallel pathways by the previously disordered cytoplasmic loop. Mutagenesis and transport assays indicated that the newly identified high-affinity metal binding site in the primary pathway acts as a “metal sink” to reduce the transport rate. The discovery of a hinge motion around an extracellular axis allowed us to propose a sequential hinge-elevator-hinge movement of the transport domain to achieve alternating access. These findings provide key insights into the transport mechanisms and activity regulation.
Genetic basis of aposematic coloration in a mimetic radiation of poison frogs
Authors: Linderoth Tyler , Aguilar-Gómez Diana , White Emily , Twomey Evan , Stuckert Adam , Bi Ke , Ko Amy , Graham Natalie , Rocha Joana L. , Chang Jason , MacManes Matthew D. , Summers Kyle , Nielsen Rasmus 
Published: April 2023

AbstractThe evolution of mimicry in a single species or population has rippling inter and intraspecific effects across ecological communities, providing a fascinating mechanism of phenotypic diversification. In this study we present the first identification of genes underlying Müllerian mimicry in a vertebrate, the Peruvian mimic poison frog,Ranitomeya imitator. We sequenced 124R. imitatorexomes and discovered loci with both strong divergence between different mimetic morphs and phenotypic associations within an intraspecific admixture zone, implicatingmc1r,asip,bsn,retsat, andkrt8.2in the evolution of mimetic color phenotypes. We confirmed these associations for most candidate genes through linkage mapping in a lab-reared pedigree. We also sequenced transcriptomes from the model species, allowing tests for introgression and revealing that the mimetic resemblance betweenR. imitatorand the models evolved independently. Selection analyses of the candidate genes show that the mimicry phenotypes likely have evolved through selective sweeps acting on polygenic variation. Our results suggest that the evolutionary origins and molecular mechanisms underlying mimicry phenotypes in vertebrates may be radically different from those previously documented in invertebrates such as the iconicHeliconiusbutterfly mimicry complex.One Sentence SummaryMüllerian mimicry evolved through independent selective sweeps on color and pattern loci in the mimic poison frog.
Circadian redox rhythm gates immune-induced cell death distinctly from the genetic clock
Authors: Karapetyan Sargis , Mwimba Musoki , Dong Xinnian 
Published: April 2023

ABSTRACTOrganisms use circadian clocks to synchronize physiological processes to anticipate the Earth’s day-night cycles and regulate responses to environmental stresses to gain competitive advantage1. While divergent genetic clocks have been studied extensively in bacteria, fungi, plants, and animals, a conserved circadian redox rhythm has only recently been reported and hypothesized to be a more ancient clock2, 3. However, it is controversial whether the redox rhythm serves as an independent clock and controls specific biological processes4. Here, we uncovered the coexistence of redox and genetic rhythms with distinct period lengths and transcriptional targets through concurrent metabolic and transcriptional time-course measurements in anArabidopsislong-period clock mutant5. Analysis of the target genes indicated regulation of the immune-induced programmed cell death (PCD) by the redox rhythm. Moreover, this time-of-day-sensitive PCD was eliminated by redox perturbation and by blocking the signalling pathway of the plant defence hormones jasmonic acid/ethylene, while remaining intact in a genetic-clock-impaired line. We demonstrate that compared to robust genetic clocks, the more sensitive circadian redox rhythm serves as a signalling hub in regulating incidental energy-intensive processes, such as immune-induced PCD6, to provide organisms a flexible strategy to prevent metabolic overload caused by stress, a unique role for the redox oscillator.
Multidimensional analysis of matched primary and recurrent glioblastoma identifies Fcγ receptors upregulation on microglia as a contributor of tumor recurrence
Authors: Shekarian Tala , Hogan Sabrina , Martins Tomás A. , Schmassmann Philip , Gerber Alexandra , Roux Julien , Kaymak Deniz , Durano Célia , Burger Bettina , Matter Matthias , Ritz Marie-Françoise , Hutter Gregor 
Published: April 2023

AbstractBackground: Glioblastoma (GBM) is a lethal brain tumor without effective treatment options. The aim of this study was to characterize longitudinal tumor immune microenvironment (iTME) changes in order to find potential actionable targets to prevent GBM-induced immune evasion mechanisms.Methods: This study included 15 patient-matched treatment-naïve WHO grade 4 primary (pGBM) and recurrent (rGBM) tumors. RNA and proteins extracted from fresh frozen tumor samples from matched pGBM and rGBM were profiled via transcriptomics and proteomics, respectively. A tissue microarray containing paired formalin-fixed paraffin-embedded tumor samples was processed for spatial transcriptomics analysis.Results: Differentially expressed genes and proteins between pGBM and rGBM were involved in pathways responsible for synapse development and myelination which have been shown to play a role in GBM recurrence. By categorizing patients into short and long time-to-relapse (STTR vs LTTR), we identified genes positively or negatively associated with TTR. Expression of Fcγ receptors and complement system genes such asFCGR1A(CD64),FCGR3AandC3in rGBM samples were negatively correlated with TTR, whereas expression ofDNMT1/3A, andSMARCA4, involved in DNA methylation, were positively correlated with TTR. Spatial transcriptomic analysis of the tumor cell compartment showed enrichment of oligodendrocytes in rGBM, whereas the myeloid cell compartment switched from quiescent to activated microglia, was enriched in B and T cells, specifically in rGBM with STTR.Conclusions:Our results uncover a role for CD64-expressing activated microglia in GBM recurrence and suggest that interfering with these cells may represent a therapeutic option for hindering GBM relapse.Key points:Transcriptomic and proteomic differences exist between patient-paired primary and recurrent GBM tumorsHigh expression of Fcy receptors genes on activated microglia at tumor recurrence is associated with shorter time to relapse.Importance of this study:In glioblastoma (GBM), the tumor recurs in almost all cases after standard treatment such as surgery and chemo-radiotherapy. In this study, we longitudinally evaluated the immune- and neoplastic compartments using transcriptomic, proteomic, and spatial transcriptomics in patient-matched treatment-naive and recurrent tumor samples. By correlating gene expression with time-to-relapse, we identified a geneset associated with treatment resistance and faster tumor recurrence. Moreover, this study highlighted the plasticity of the myeloid compartment during disease progression and an unfavorable role of activated microglia in tumor recurrence.
Translating deep learning to neuroprosthetic control
Authors: Deo Darrel R. , Willett Francis R. , Avansino Donald T. , Hochberg Leigh R. , Henderson Jaimie M. , Shenoy Krishna V. 
Published: April 2023

AbstractAdvances in deep learning have given rise to neural network models of the relationship between movement and brain activity that appear to far outperform prior approaches. Brain-computer interfaces (BCIs) that enable people with paralysis to control external devices, such as robotic arms or computer cursors, might stand to benefit greatly from these advances. We tested recurrent neural networks (RNNs) on a challenging nonlinear BCI problem: decoding continuous bimanual movement of two computer cursors. Surprisingly, we found that although RNNs appeared to perform well in offline settings, they did so by overfitting to the temporal structure of the training data and failed to generalize to real-time neuroprosthetic control. In response, we developed a method that alters the temporal structure of the training data by dilating/compressing it in time and re-ordering it, which we show helps RNNs successfully generalize to the online setting. With this method, we demonstrate that a person with paralysis can control two computer cursors simultaneously, far outperforming standard linear methods. Our results provide evidence that preventing models from overfitting to temporal structure in training data may, in principle, aid in translating deep learning advances to the BCI setting, unlocking improved performance for challenging applications.
TopoDoE: A Design of Experiment strategy for selection and refinement in ensembles of executable Gene Regulatory Networks
Authors: Bouvier Matteo , Zreika Souad , Vallin Elodie , Fourneaux Camille , Giraud-Gonin Sandrine , Bonnaffoux Arnaud , Gandrillon Olivier 
Published: April 2023

AbstractBackgroundInference of Gene Regulatory Networks (GRNs) is a difficult and long-standing question in Systems Biology. Numerous approaches have been proposed with the latest methods exploring the richness of single-cell data. One of the current difficulties lies in the fact that many methods of GRN inference do not result in one proposed GRN but in a collection of plausible networks that need to be further refined. In this work, we present a Design of Experiment strategy to use as a second stage after the inference process. It is specifically fitted for identifying the next most informative experiment to perform for deciding between multiple network topologies, in the case where proposed GRNs are executable models. This strategy first performs a topological analysis to reduce the number of perturbations that need to be tested, then predicts the outcome of the retained perturbations by simulation of the GRNs and finally compares predictions with novel experimental data.ResultsWe apply this method to the results of our divide-and-conquer algorithm called WASABI, adapt its gene expression model to produce perturbations and compare our predictions with experimental results. We show that our networks were able to producein silicopredictions on the outcome of a gene knock-out, which were qualitatively validated for 48 out of 49 genes. Finally, we eliminate as many as two thirds of the candidate networks for which we could identify an incorrect topology, thus greatly improving the accuracy of our predictions.ConclusionThese results both confirm the inference accuracy of WASABI and show how executable gene expression models can be leveraged to further refine the topology of inferred GRNs. We hope this strategy will help systems biologists further explore their data and encourage the development of more executable GRN models.
Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior
Authors: Ger Yoav , Nachmani Eliya , Wolf Lior , Shahar Nitzan 
Published: April 2023

AbstractReinforcement learning (RL) models are used extensively to study human behavior. These rely on normative models of behavior and stress interpretability over predictive capabilities. More recently, neural network models have emerged as a descriptive modeling paradigm that is capable of high predictive power yet with limited interpretability. Here, we seek to augment the expressiveness of theoretical RL models with the high flexibility and predictive power of neural networks. We introduce a novel framework, which we term theoretical-RNN (t-RNN), whereby a recurrent neural network is trained to predict trial-by-trial behavior and to infer theoretical RL parameters using artificial data of RL agents performing a two-armed bandit task. In three studies, we then examined the use of our approach to dynamically predict unseen behavior along with time-varying theoretical RL parameters. We first validate our approach using synthetic data with known RL parameters. Next, as a proof-of-concept, we applied our framework to two independent datasets of humans performing the same task. In the first dataset, we describe differences in theoretical RL parameters dynamic among clinical psychiatric vs. healthy controls. In the second dataset, we show that the exploration strategies of humans varied dynamically in response to task phase and difficulty. For all analyses, we found better performance in the prediction of actions for t-RNN compared to the stationary maximum-likelihood RL method. We discuss the use of neural networks to facilitate the estimation of latent RL parameters underlying choice behavior.Author summaryCurrently, neural network models fitted directly to behavioral human data are thought to dramatically outperform theoretical computational models in terms of predictive accuracy. However, these networks do not provide a clear theoretical interpretation of the mechanisms underlying the observed behavior. Generating plausible theoretical explanations for observed human data is a major goal in computational neuroscience. Here, we provide a proof-of-concept for a novel method where a recurrent neural network (RNN) is trained on artificial data generated from a known theoretical model to predict both trial-by-trial actions and theoretical parameters. We then freeze the RNN weights and use it to predict both actions and theoretical parameters of empirical data. We first validate our approach using synthetic data where the theoretical parameters are known. We then show, using two empirical datasets, that our approach allows dynamic estimation of latent parameters while providing better action predictions compared to theoretical models fitted with a maximum-likelihood approach. This proof-of-concept suggests that neural networks can be trained to predict meaningful time-varying theoretical parameters.
Effects of repeated developmental GLP-1R agonist exposure on adult behavior and hippocampal structure in mice
Authors: Cerroni Catherine , Steiner Alex , Seanez Leann , Kwon Sam , Lewis Alan S. 
Published: April 2023

AbstractGlucagon-like peptide-1 receptor (GLP-1R) agonists are common type 2 diabetes medications that have been repurposed for adult chronic weight management. Clinical trials suggest this class may also be beneficial for obesity in pediatric populations. Since several GLP-1R agonists cross the blood-brain barrier, it is important to understand how postnatal developmental exposure to GLP-1R agonists might affect brain structure and function in adulthood. Toward that end, we systemically treated male and female C57BL/6 mice with the GLP-1R agonist exendin-4 (0.5 mg/kg, twice daily) or saline from postnatal day 14 to 21, then allowed uninterrupted development to adulthood. Beginning at 7 weeks of age, we performed open field and marble burying tests to assess motor behavior and the spontaneous location recognition (SLR) task to assess hippocampal-dependent pattern separation and memory. Mice were sacrificed, and we counted ventral hippocampal mossy cells, as we have recently shown that most murine hippocampal neuronal GLP-1R is expressed in this cell population. We found that GLP-1R agonist treatment did not alter P14-P21 weight gain, but modestly reduced adult open field distance traveled and marble burying. Despite these motor changes, there was no effect on SLR memory performance or time spent investigating objects. Finally, we did not detect any changes in ventral mossy cell number using two different markers. These data suggest developmental exposure to GLP-1R agonists might have specific rather than global effects on behavior later in life and that extensive additional study is necessary to clarify how drug timing and dose affect distinct constellations of behavior in adulthood.
Upstream Stimulatory Factors regulate HIV-1 latency and are required for robust T cell activation
Authors: Horvath Riley M. , Sadowski Ivan 
Published: April 2023

AbstractRBF-2, composed minimally of the factors USF1, USF2, and TFII-I, is the cognate binding complex of stringently conservedcis-elements on the HIV-1 LTR, designated RBE3 and RBE1. Mutations of these elements prevent induction of provirus in response to T cell signaling. However, the function of USF1 and USF2 for this effect are relatively uncharacterized. Here, we find that deletion of theUSF2but notUSF1gene in T cells abrogates HIV-1 expression. Loss ofUSF2caused a reduction in expression of USF1 protein, an effect that was not associated with decreasedUSF1mRNA abundance. USF1 and USF2 were previously shown to exist predominately as heterodimers on DNAin vivoand cooperatively regulate target genes. To examine this, we performed RNA-seq analysis of T cell lines bearing knockouts of genes encoding these factors. In untreated cells we found limited evidence of coordinated global gene regulation between USF1 and USF2. In contrast we observed a high degree of genome-wide cooperative regulation of RNA expression between these factors in cells stimulated with the combination of PMA and ionomycin. In particular, we found thatUSF1deletion resulted in a restricted T cell activation response, and this phenotype was exaggerated inUSF2knockout cells. These observations indicate that USF2, but not USF1, is crucial for HIV-1 expression, but the combined function of these factors is required for full T cell response.
Genetic Loss of Nicotinamide Nucleotide Transhydrogenase Prevents from Cardiometabolic Heart Failure with Preserved Ejection Fraction
Authors: Pepin Mark E. , Nazir Sumra , Konrad Philipp J.M. , Schreiter Friederike , Dewenter Matthias , Backs Johannes 
Published: April 2023

ABSTRACTRationaleHeart failure with preserved ejection fraction (HFpEF) represents a common clinical endpoint of cardiometabolic diseases which impair myocardial diastolic relaxation. Although myocardial redox perturbations are known to accompany HFpEF, the specific role of mitochondrial oxidative stress has not been demonstrated yet.ObjectiveBased on an observation that C57BL6/N – but not C57BL6/J – mice develop diastolic dysfunction when provided anad libitumhigh-fat and 0.5% N(ω)-nitro-L-arginine methyl ester (HFD+L-NAME) diet, we conducted a multi-cohort murine study to determine whether the loss of Nicotinamide Nucleotide Transhydrogenase (NNT), a mitochondrial transhydrogenase that couples NADPH:NADP+to NADH:NAD+homeostasis, protects mice from developing cardiometabolic alterations.Methods and ResultsTwo cohorts of 12-week-old male and female mice possessing wild-type (Nnt+/+) or deleted (Nnt-/-) NNT were challenged by HFD+L-NAME for 9 weeks (n = 6-10). MaleNnt+/+mice developed obesity (23.2% Δ,P= 0.003), arterial hypertension (24 ± 5 Δ mmHg,P= 0.023), impaired glucose tolerance (P= 0.006), and reduced maximal treadmill running distance (−172 ± 73.1 Δ m,P= 0.006) following 9 weeks HFD+L-NAME, whereas maleNnt-/-mice did not. Female mice were protected from cardiometabolic dysfunction regardless ofNntgenotype. Cardiac functional and morphologic characterization revealed similar NNT-dependent and sex-specific increases in E/e’ (42.8 vs. 21.5,P< 0.001) and E/A (2.3 vs 1.4,P= 0.007) ratios, diastolic stiffness (0.09 vs 0.04 mmHg/μL,P= 0.02), and myocardial fibrosis (P= 0.02). Unsupervised transcriptomic analysis identified distinct genetic and dietary signatures, whereinNnt+/+exhibited disproportionate perturbations in various mitochondrial oxidative pathways following HFD+L-NAME. Our search for putative transcriptional regulators identified NNT-dependent suppression of NAD+ dependent deacetylaseSirt3.ConclusionsTaken together, these observations support that the genetic disruption ofNntprotects against both cardiac and metabolic consequences of HFD+L-NAME, thus highlighting a novel etiology-specific avenue for HFpEF therapeutics.
Long-Distance Electrical and Calcium Signals Evoked by Hydrogen Peroxide in Physcomitrella
Authors: Koselski Mateusz , Hoernstein Sebastian N. W. , Wasko Piotr , Reski Ralf , Trebacz Kazimierz 
Published: April 2023

AbstractElectrical and calcium signals in plants are one of the basic carriers of information transmitted over a long distance. Together with reactive oxygen species (ROS) waves, electrical and calcium signals can participate in cell-to-cell signaling, conveying information about different stimuli, e.g. abiotic stress, pathogen infection, or mechanical injury. There is no information on the ability of ROS to evoke systemic electrical or calcium signals in the model moss Physcomitrella and on the relationships between these responses. Here, we show that external application of hydrogen peroxide evokes electrical signals in the form of long-distance changes in the membrane potential, which transmit through the plant instantly after stimulation. The responses were calcium dependent, since their generation was inhibited by lanthanum, a calcium channel inhibitor (2 mM) or EDTA, a calcium chelator (0.5 mM). The electrical signals were partially dependent on glutamate receptor ion channels (GLR), since the knockout of GLR genes only slightly reduced the amplitude of the responses. The basal part of the gametophyte, which is rich in protonema cells, was the most sensitive to hydrogen peroxide. The measurements carried out on the protonema expressing fluorescent calcium biosensor GCaMP3 proved that. We also demonstrate upregulation of a stress-related gene which appears in a distant section of the moss 8 minutes after H2O2treatment. The results help to understand the importance of both types of signals in the transmission of information about the appearance of ROS in the plant cell apoplast.
Notch regulated long non-coding RNA TUG1 regulates smooth muscle cell differentiation in aortic aneurysm
Authors: Bharadhwaj Ravi Abishek , Kumarswamy Regalla 
Published: April 2023

AbstractAbdominal Aortic Aneurysms (AAAs) are asymptomatic vascular diseases with life threatening outcomes. Smooth-muscle cell (SMC) dysfunction plays an important role in AAA development. The contributions of non-coding genome, specifically the role of long non-coding RNAs (lncRNAs) in SMC dysfunction are relatively unexplored. We investigated the role of lncRNA TUG1 in the pathology of AAA. TUG1 was identified through lncRNA profiling in Angiotensin-II (Ang-II) treated SMCs. TUG1 was upregulated in Ang-II treated SMCsin vitroand its expression increased with progression of aneurysm in mouse model of Ang-II induced AAA. Ang-II induced TUG1 was blunted by inhibition of Notch signaling and TUG1 is demonstrated to be a transcriptional target of Notch. AAA tissues exhibited inversely correlated expression of TUG1 and SMC contractile markers. TUG1 knock-down via siRNA/shRNA increased SMC differentiation. ChIP, DNA-RNA IP, and RNA-IP experiments demonstrated that TUG1 interacts with transcriptional repressor KLF4 and aides in its recruitment to Myocardin promoter, thereby repressing SMC differentiation. In summary, we show a novel role for lncRNA TUG1 in Ang-II induced AAA wherein it modulates SMC differentiation via KLF4-Myocardin axis.
WITHDRAWN: Spatial enrichment of the type 1 interferon signature in the brain of a neuropsychiatric lupus murine model
Authors: Aw Ernest , Lin Stacie L. , Zhang Yingying , Herrmann Uli , Yalcin Esra , Langston Kent , Castrillion Carlos , Ma Minghe , Moffitt Jeffrey R. , Carroll Michael C. 
Published: April 2023

Withdrawal StatementbioRxiv has withdrawn this manuscript because it was posted without the consent of all authors. If you have any questions, please contact the corresponding author.