bluuebunny/crossref_metadata_2025_split huggingface dataset:
Applying the auxin-inducible degradation (AID) system for rapid protein depletion in mammalian cells
Authors: Lambrus Bramwell G. , Moyer Tyler C. , Holland Andrew J. 
Published: September 2017

AbstractThe ability to deplete a protein of interest is critical for dissecting cellular processes. Traditional methods of protein depletion are often slow-acting, which can be problematic when characterizing a cellular process that occurs within a short period of time. Furthermore, these methods are usually not reversible. Recent advances to achieve protein depletion function by inducibly trafficking proteins of interest to an endogenous E3 ubiquitin ligase complex to promote ubiquitination and subsequent degradation by the proteasome. One of these systems, the auxin-inducible degron (AID) system, has been shown to permit rapid and inducible degradation of AID-tagged target proteins in mammalian cells. The AID system can control the abundance of a diverse set of cellular proteins, including those contained within protein complexes, and is active in all phases of the cell cycle. Here we discuss considerations for the successful implementation of the AID system and describe a protocol using CRISPR/Cas9 to achieve bi-allelic insertion of an AID degron in human cells. This method can also be adapted to insert other tags, such as fluorescent proteins, at defined genomic locations.
Neck muscle spindle noise biases reaches in a multi-sensory integration task
Authors: Khoozani Parisa Abedi , Blohm Gunnar 
Published: September 2017

AbstractReference frame Transformations (RFTs) are crucial components of sensorimotor transformations in the brain. Stochasticity in RFTs has been suggested to add noise to the transformed signal due to variability in transformation parameter estimates (e.g. angle) as well as the stochastic nature of computations in spiking networks of neurons. Here, we varied the RFT angle together with the associated variability and evaluated the behavioral impact in a reaching task that required variability-dependent visual-proprioceptive multi-sensory integration. Crucially, reaches were performed with the head either straight or rolled 30deg to either shoulder and we also applied neck loads of 0 or 1.8kg (left or right) in a 3×3 design, resulting in different combinations of estimated head roll angle magnitude and variance required in RFTs. A novel 3D stochastic model of multi-sensory integration across reference frames was fitted to the data and captured our main behavioral findings: (1) neck load biased head angle estimation across all head roll orientations resulting in systematic shifts in reach errors; (2) Increased neck muscle tone led to increased reach variability, due to signal-dependent noise; (3) both head roll and neck load created larger angular errors in reaches to visual targets away from the body compared to reaches toward the body. These results show that noise in muscle spindles and stochasticity in general have a tangible effect on RFTs underlying reach planning. Since RFTs are omnipresent in the brain, our results could have implication for processes as diverse as motor control, decision making, posture / balance control, and perception.New & NoteworthyWe show that increasing neck muscle tone systematically biases reach movements. A novel 3D multisensory integration across reference frames model captures the data well and provides evidence that the brain must have online knowledge of full body geometry together with the associated variability to accurately plan reach movements.
Single-cell analysis of early antiviral gene expression reveals a determinant of stochasticIFNB1expression
Authors: Doğanay Sultan , Lee Maurice Youzong , Baum Alina , Peh Jessie , Hwang Sun-Young , Yoo Joo-Yeon , Hergenrother Paul J. , García-Sastre Adolfo , Myong Sua , Ha Taekjip 
Published: September 2017

AbstractRIG-I-like receptors (RLRs) are cytoplasmic sensors of viral RNA that trigger the signaling cascade that leads to type I interferon (IFN) production. Transcriptional induction of RLRs by IFN is believed to play the role of positive feedback to further amplify viral sensing. We found that RLRs and several other IFN-stimulated genes (ISGs) are induced early in viral infection independent of IFN. Expression of these early ISGs requires IRF3/IRF7 and is highly correlated amongst them. Simultaneous detection of mRNA ofIFNB1, viral replicase, and ISGs revealed distinct populations ofIFNB1expressing and non-expressing cells which are highly correlated with the levels of early ISGs but are uncorrelated with IFN-dependent ISGs and viral gene expression. Individual expression of RLRs madeIFNB1expression more robust and earlier, suggesting a causal relation between levels of RLR and induction of IFN.
CancerDiscover: A configurable pipeline for cancer prediction and biomarker identification using machine learning framework
Authors: Mohammed Akram , Biegert Greyson , Adamec Jiri , Helikar Tomáš 
Published: September 2017

AbstractMotivationUse of various high-throughput screening techniques has resulted in an abundance of data, whose complete utility is limited by the tools available for processing and analysis. Machine learning holds great potential for deciphering these data in the context of cancer classification and biomarker identification. However, current machine learning tools require manual processing of raw data from various sequencing platforms, which is both tedious and time-consuming. The current classification tools lack flexibility in choosing the best feature selection algorithms from a range of algorithms and most importantly inability to compare various learning algorithms.ResultsWe developed CancerDiscover, an open-source software pipeline that allows users to efficiently and automatically integrate large high-throughput datasets, preprocess, normalize, and selects best performing features from multiple feature selection algorithms. The pipeline lets users apply various learning algorithms and generates multiple classification models and evaluation reports that distinguish cancer from normal samples, as well as different types and subtypes of cancer.Availability and ImplementationThe open source pipeline is freely available for download athttps://github.com/HelikarLab/CancerDiscover.Contactelikar2@unl.eduSupplementary InformationPlease refer to the CancerDiscover README (Supplementary File 1) for detailed instructions on installation and operation of the pipeline. For a list of available feature selection methods, see Supplementary File 2.
Hemodynamic forces tune the arrest, adhesion and extravasation of circulating tumor cells
Authors: Follain Gautier , Osmani Naël , Azevedo Sofia , Allio Guillaume , Mercier Luc , Karreman Matthia A. , Solecki Gergely , Garcia-Leon Maria Jesus , Lefebvre Olivier , Fekonja Nina , Hille Claudia , Chabannes Vincent , Dollé Guillaume , Metivet Thibaut , Der Hovsepian François , Prudhomme Christophe , Pichot Angélique , Paul Nicodème , Carapito Raphaël , Bahram Siamak , Ruthensteiner Bernhard , Kemmling André , Siemonsen Susanne , Schneider Tanja , Fiehler Jens , Glatzel Markus , Winkler Frank , Schwab Yannick , Pantel Klaus , Harlepp Sébastien , Goetz Jacky G. 
Published: September 2017

ABSTRACTMetastatic seeding is driven by cell-intrinsic and environmental cues, yet the contribution of biomechanics is poorly known. We aim to elucidate the impact of blood flow on the arrest and the extravasation of circulating tumor cells (CTCs)in vivo. Using the zebrafish embryo, we show that arrest of CTCs occurs in vessels with favorable flow profiles where flow forces control the adhesion efficacy of CTCs to the endothelium. We biophysically identified the threshold values of flow and adhesion forces allowing successful arrest of CTCs. In addition, flow forces fine-tune tumor cell extravasation by impairing the remodeling properties of the endothelium. Importantly, we also observe endothelial remodeling at arrest sites of CTCs in mouse brain capillaries. Finally, we observed that human supratentorial brain metastases preferably develop in areas with low perfusion. Altogether, these results demonstrate that hemodynamic profiles at metastatic sites regulate key steps of extravasation preceding metastatic outgrowth.
Recovering genomic clusters of secondary metabolites from lakes: a Metagenomics 2.0 approach
Authors: Cuadrat Rafael R. C. , Ionescu Danny , Davila Alberto M. R. , Grossart Hans-Peter 
Published: September 2017

AbstractBackgroundMetagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolism still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases.In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows.ResultsWith this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from the lake samples. A total of 18 NRPS, 19 PKS and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences.ConclusionsOur approach revealed a great potential to recover and study secondary metabolites genes from any aquatic ecosystem.
Timescales of influenza A/H3N2 antibody dynamics
Authors: Kucharski Adam J. , Lessler Justin , Cummings Derek A.T. , Riley Steven 
Published: September 2017

AbstractHuman immunity influences the evolution and impact of novel influenza strains. Because individuals are infected with multiple influenza strains during their lifetime and each virus can generate a cross-reactive antibody response, it is challenging to quantify the processes that shape observed immune responses, or to reliably detect recent infection from serological samples. Using a Bayesian model of antibody dynamics at multiple timescales, we explain complex cross-reactive antibody landscapes by inferring participants’ histories of infection with serological data from cross-sectional and longitudinal studies of influenza A/H3N2 in southern China and Vietnam. We show an individual’s influenza antibody profile can be explained by a short-lived, broadly cross-reactive response that decays within a year to leave a smaller long-term response acting against a narrower range of strains. We also demonstrate that accounting for dynamic immune responses can provide a more accurate alternative to traditional definitions seroconversion for the estimation of infection attack rates. Our work provides a general model for explaining mechanisms of influenza immunity acting at multiple timescales based on contemporary serological data, and suggests a two-armed immune response to influenza infection consistent with competitive dynamics between B cell populations. This approach to analysing multiple timescales for antigenic responses could also be applied to other multi-strain pathogens such as dengue and related flaviviruses.
Hsf1 and Hsp70 constitute a two-component feedback loop that regulates the yeast heat shock response
Authors: Krakowiak Joanna , Zheng Xu , Patel Nikit , Anandhakumar Jayamani , Valerius Kendra , Gross David S. , Khalil Ahmad S. , Pincus David 
Published: September 2017

ABSTRACTModels for regulation of the eukaryotic heat shock response typically invoke a negative feedback loop consisting of the transcriptional activator Hsf1 and a molecular chaperone encoded by an Hsf1 target gene. Previously, we identified Hsp70 as the chaperone responsible for Hsf1 repression inSaccharomyces cerevisiaeand constructed a mathematical model based on Hsp70-mediated negative feedback that recapitulated the dynamic activity of Hsf1 during heat shock. The model was based on two assumptions: dissociation of Hsp70 activates Hsf1, and transcriptional induction of Hsp70 deactivates Hsf1. Here we validated these assumptions. First, we severed the feedback loop by uncoupling Hsp70 expression from Hsf1 regulation. As predicted by the model, Hsf1 was unable to efficiently deactivate in the absence of Hsp70 transcriptional induction. Next we mapped a discrete Hsp70 binding site on Hsf1 to a motif in the C-terminal activation domain known as conserved element 2 (CE2). Removal of CE2 resulted in increased Hsf1 activity under non-heat shock conditions and delayed deactivation kinetics. In addition, we uncovered a role for the N-terminal domain of Hsf1 in negatively regulating DNA binding. These results reveal the quantitative control mechanisms underlying the feedback loop charged with maintaining cytosolic proteostasis.
Fitting mathematical models of biochemical pathways to steady state perturbation response data without simulating perturbation experiments
Authors: Santra Tapesh 
Published: September 2017

AbstractA common experimental approach for studying signal transduction networks (STNs) is to measure the steady state concentrations of their components following perturbations to individual components. Such data is frequently used to reconstruct topological models of STNs, but, are rarely used for calibrating kinetic models of these networks. This is because, existing calibration algorithms operate by assigning different sets of values to the parameters of the kinetic models, and for each set of values simulating all perturbations performed in the biochemical experiments. This process is highly computation intensive and may be infeasible when molecular level information of the perturbation experiments is unavailable. Here, I propose an algorithm which can calibrate ordinary differential equation (ODE) based kinetic models of STNs using steady-state perturbation responses (SSPRs) without simulating perturbation experiments. The proposed algorithm uses modular response analysis (MRA) to calculate the scaled Jacobian matrix of the ODE model of an STN using SSPR data. The model parameters are then calibrated to fit the scaled Jacobian matrix calculated in the above step. This procedure does not require simulating the perturbation experiments. Therefore, it is significantly less computation intensive than existing algorithms and can be implemented without molecular level knowledge of the mechanism of perturbations. It is also parallelizable, i.e. can explore multiple sets of parameter values simultaneously, and therefore is scalable. The capabilities and shortcomings of the proposed algorithm are demonstrated using both simulated and real perturbation responses of Mitogen Activated Protein Kinase (MAPK) STN.AvailabilityAll source codes and data needed to replicate the results in this manuscript are available fromhttps://github.com/SBIUCD/MRA_SMC_ABC1
Metabolite profile and mitochondrial energetics characterize poor early recovery of muscle mass following hind limb unloading in old mice
Authors: Zhang Xiaolei , Trevino Michelle B. , Wang Miao , Gardell Stephen J. , Ayala Julio E. , Han Xianlin , Kelly Daniel P. , Goodpaster Bret H. , Vega Rick B. , Coen Paul M. 
Published: September 2017

SUMMARYThe progression of age-related sarcopenia can be accelerated by impaired recovery of muscle mass following periods of disuse due to illness or immobilization. The molecular underpinnings of poor recovery of aging muscle following disuse remain largely unknown. However, recent evidence suggests that mitochondrial energetics may play an important role. Here, we report that 22-24 month old mice with low muscle mass and insulin resistance display poor early recovery of muscle mass following 10 days of hind limb unloading. We took an unbiased approach to identify changes in energy metabolism gene expression and metabolite pools and show for the first time that persistent mitochondrial dysfunction, dysregulated fatty acid β-oxidation and elevated H2O2emission underlie poor early recovery of muscle mass following a period of disuse in old mice. Importantly, this is linked to more severe whole-body insulin resistance. The findings suggest that muscle fuel metabolism and mitochondrial energetics should be a focus for mining therapeutic targets to improve recovery of muscle mass following periods of disuse in older animals.
Validation of RT-qPCR approaches to monitorPseudomonas syringaegene expression during infection and exposure to pattern-triggered immunity
Authors: Smith Amy , Lovelace Amelia H. , Kvitko Brian H. 
Published: September 2017

AbstractPseudomonas syringaepv. tomato DC3000 (DC3000) is an important model plant pathogen, with a fully annotated genome and multiple compatible plant hosts. Very few studies have examined the regulation of DC3000 gene expressionin vivo. We developed a RT-qPCR assay to monitor transcriptional changes in DC3000 inoculated intoArabidopsis thalianaleaves during disease and exposure to pattern-triggered immunity (PTI). In our approach, bacterial RNA concentrations in total tissue RNA are standardized usingP.syringae-specific16S ribosomal RNA primers. We validated multiple stable reference genes for normalization in calculating the relative expression of genes of interest. We used empirically derived rates of amplification efficiency to calculate relative expression of key marker genes for virulence-associated regulation. We demonstrated that exposure to PTI alters DC3000 expression of Type III secretion system, coronatine synthesis genes and flagellar marker genes.
Adeno-associated virus mediated gene delivery: Implications for scalablein vitroandin vivocardiac optogenetic models
Authors: Ambrosi Christina M. , Sadananda Gouri , Klimas Aleksandra , Entcheva Emilia 
Published: September 2017

ABSTRACTAimsAdeno-associated viruses (AAVs) provide advantages in long-term, cardiac-specific gene expression. However, AAV serotype specificity data is lacking in cardiac models relevant to optogenetics. We aimed to identify the optimal AAV serotype (1, 6, or 9) in pursuit of scalable rodent and human models for cardiac optogenetics and elucidate the mechanism of virus uptake.MethodsIn vitrosyncytia of primary neonatal rat ventricular cardiomyocytes (NRVMs) and human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) were infected with AAVs 1, 6, and 9 containing the transgene for eGFP or channelrhodopsin-2 (ChR2) fused to mCherry.In vivoadult rats were intravenously injected with AAV1 and 9 containing ChR2-mCherry.ResultsTransgene expression profiles of rat and human cellsin vitrorevealed that AAV1 and 6 significantly outperformed AAV9. In contrast, systemic delivery of AAV9 in adult rat hearts yielded significantly higher levels of ChR2-mCherry expression and optogenetic responsiveness. We tracked the mechanism of virus uptake to purported receptor-mediators for AAV 1/6 (cell surface sialic acid) and AAV9(37/67kDa laminin receptor, LamR).In vitrodesialylation of NRVMs and hiPSC-CMs with neuraminidase significantly decreased AAV1,6-mediated gene expression, but interestingly, desialylation of hiPSC-CMs increased AAV9-mediated expression. In fact, only very high viral doses of AAV9-ChR2-mCherry, combined with neuraminidase treatment yielded consistent optogenetic responsiveness in hiPSC-CMs. Differences between thein vitroandin vivoperformance of AAV9 could be correlated to robust LamR expression in the adult and neonatal rat hearts, but no expressionin vitroin cultured cells. The dynamic nature of LamR expression and its dependence on environmental factors was further corroborated in intact adult human ventricular tissue slices.ConclusionThe combined transgene expression and cell surface receptor data may explain the preferential efficiency of AAV1/6in vitroand AAV9in vivofor cardiac delivery and mechanistic knowledge of their action can help guide cardiac optogenetic efforts.
Transcriptomes of major renal collecting-duct cell types in mouse identified by single-cell RNA-Seq
Authors: Chen Lihe , Lee Jae Wook , Chou Chung-Lin , Nair Anilkumar , Battistone Maria Agustina , Paunescu Teodor , Mekulova Maria , Breton Sylvie , Verlander Jill W. , Wall Susan , Brown Dennis , Burg Maurice B. , Knepper Mark A. 
Published: September 2017

ABSTRACTPrior RNA sequencing (RNA-Seq) studies have identified complete transcriptomes for most renal epithelial cell types. The exceptions are the cell types that make up the renal collecting duct, namely intercalated cells (ICs) and principal cells (PCs), which account for only a small fraction of the kidney mass, but play critical physiological roles in the regulation of blood pressure, extracellular fluid volume and extracellular fluid composition. To enrich these cell types, we used fluorescence-activated cell sorting (FACS) that employed well established lectin cell surface markers for PCs and type B ICs, as well as a newly identified cell surface marker for type A ICs, viz. c-Kit. Single-cell RNA-Seq using the 1C- and PC-enriched populations as input enabled identification of complete transcriptomes of A-ICs, B-ICs and PCs. The data were used to create a freely-accessible online gene-expression database for collecting duct cells. This database allowed identification of genes that are selectively expressed in each cell type including cell-surface receptors, transcription factors, transporters and secreted proteins. The analysis also identified a small fraction of hybrid cells expressing both aquapor¡n-2 and either anion exchanger 1 or pendrin transcripts. In many cases, mRNAs for receptors and their ligands were identified in different cells (e.g.Notch2chiefly in PCs vsJag1chiefly in ICs) suggesting signaling crosstalk among the three cell types. The identified patterns of gene expression among the three types of collecting duct cells provide a foundation for understanding physiological regulation and pathophysiology in the renal collecting duct.SIGNIFICANCE STATEMENTA long-term goal in mammalian biology is to identify the genes expressed in every cell type of the body. In kidney, the expressed genes (“transcriptome”) of all epithelial cell types have already been identified with the exception of the cells that make up the renal collecting duct, responsible for regulation of blood pressure and body fluid composition. Here, a technique called "single-cell RNA-Seq" was used in mouse to identify transcriptomes for the major collecting-duct cell types: type A intercalated cells, type B intercalated cells and principal cells. The information was used to create a publicly-accessible online resource. The data allowed identification of genes that are selectively expressed in each cell type, informative for cell-level understanding of physiology and pathophysiology.