Rapid assembly of customized TALENs into multiple

Transcriptional activator-like effector nucleases (TALENs) have become a powerful tool for genome editing. Here we present an efficient TALEN assembly approach in which TALENs are assembled by direct Golden Gate ligation into Gateway® Entry vectors from a repeat variable di-residue (RVD) plasmid array. We constructed TALEN pairs targeted to mouse Ddx3 subfamily genes, and demonstrated that our modified TALEN assembly approach efficiently generates accurate TALEN moieties that effectively introduce mutations into target genes. We generated "user friendly" TALEN Entry vectors containing TALEN expression cassettes with fluorescent reporter genes that can be efficiently transferred via Gateway (LR) recombination into different delivery systems. We demonstrated that the TALEN Entry vectors can be easily transferred to an adenoviral delivery system to expand application to cells that are difficult to transfect. Since TALENs work in pairs, we also generated a TALEN Entry vector set that combines a TALEN pair into one PiggyBac transposon-based destination vector. The approach described here can also be modified for construction of TALE transcriptional activators, repressors or other functional domains. © 2013 Zhang et al

Analysis of the transcriptional activity of endogenous NFAT5 in primary cells using transgenic NFAT-luciferase reporter mice

<p>Abstract</p> <p>Background</p> <p>The transcription factor NFAT5/TonEBP regulates the response of mammalian cells to hypertonicity. However, little is known about the physiopathologic tonicity thresholds that trigger its transcriptional activity in primary cells. Wilkins et al. recently developed a transgenic mouse carrying a luciferase reporter (9xNFAT-Luc) driven by a cluster of NFAT sites, that was activated by calcineurin-dependent NFATc proteins. Since the NFAT site of this reporter was very similar to an optimal NFAT5 site, we tested whether this reporter could detect the activation of NFAT5 in transgenic cells.</p> <p>Results</p> <p>The 9xNFAT-Luc reporter was activated by hypertonicity in an NFAT5-dependent manner in different types of non-transformed transgenic cells: lymphocytes, macrophages and fibroblasts. Activation of this reporter by the phorbol ester PMA plus ionomycin was independent of NFAT5 and mediated by NFATc proteins. Transcriptional activation of NFAT5 in T lymphocytes was detected at hypertonic conditions of 360–380 mOsm/kg (isotonic conditions being 300 mOsm/kg) and strongly induced at 400 mOsm/kg. Such levels have been recorded in plasma in patients with osmoregulatory disorders and in mice deficient in aquaporins and vasopressin receptor. The hypertonicity threshold required to activate NFAT5 was higher in bone marrow-derived macrophages (430 mOsm/kg) and embryonic fibroblasts (480 mOsm/kg). Activation of the 9xNFAT-Luc reporter by hypertonicity in lymphocytes was insensitive to the ERK inhibitor PD98059, partially inhibited by the PI3-kinase inhibitor wortmannin (0.5 μM) and the PKA inhibitor H89, and substantially downregulated by p38 inhibitors (SB203580 and SB202190) and by inhibition of PI3-kinase-related kinases with 25 μM LY294002. Sensitivity of the reporter to FK506 varied among cell types and was greater in primary T cells than in fibroblasts and macrophages.</p> <p>Conclusion</p> <p>Our results indicate that NFAT5 is a sensitive responder to pathologic increases in extracellular tonicity in T lymphocytes. Activation of NFAT5 by hypertonicity in lymphocytes was mediated by a combination of signaling pathways that differed from those required in other cell types. We propose that the 9xNFAT-Luc transgenic mouse model might be useful to study the physiopathological regulation of both NFAT5 and NFATc factors in primary cells.</p

Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models

<p>Abstract</p> <p>Background</p> <p>In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used.</p> <p>Methods</p> <p>We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels.</p> <p>Results</p> <p>The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, <it>R</it>₀, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes.</p> <p>Conclusions</p> <p>The good agreement between the two modeling approaches is very important for defining the tradeoff between data availability and the information provided by the models. The results we present define the possibility of hybrid models combining the agent-based and the metapopulation approaches according to the available data and computational resources.</p

Tbx2 and Tbx3 induce atrioventricular myocardial development and endocardial cushion formation

A key step in heart development is the coordinated development of the atrioventricular canal (AVC), the constriction between the atria and ventricles that electrically and physically separates the chambers, and the development of the atrioventricular valves that ensure unidirectional blood flow. Using knock-out and inducible overexpression mouse models, we provide evidence that the developmentally important T-box factors Tbx2 and Tbx3, in a functionally redundant manner, maintain the AVC myocardium phenotype during the process of chamber differentiation. Expression profiling and ChIP-sequencing analysis of Tbx3 revealed that it directly interacts with and represses chamber myocardial genes, and induces the atrioventricular pacemaker-like phenotype by activating relevant genes. Moreover, mutant mice lacking 3 or 4 functional alleles of Tbx2 and Tbx3 failed to form atrioventricular cushions, precursors of the valves and septa. Tbx2 and Tbx3 trigger development of the cushions through a regulatory feed-forward loop with Bmp2, thus providing a mechanism for the co-localization and coordination of these important processes in heart development

The “conscious pilot”—dendritic synchrony moves through the brain to mediate consciousness

Cognitive brain functions including sensory processing and control of behavior are understood as “neurocomputation” in axonal–dendritic synaptic networks of “integrate-and-fire” neurons. Cognitive neurocomputation with consciousness is accompanied by 30- to 90-Hz gamma synchrony electroencephalography (EEG), and non-conscious neurocomputation is not. Gamma synchrony EEG derives largely from neuronal groups linked by dendritic–dendritic gap junctions, forming transient syncytia (“dendritic webs”) in input/integration layers oriented sideways to axonal–dendritic neurocomputational flow. As gap junctions open and close, a gamma-synchronized dendritic web can rapidly change topology and move through the brain as a spatiotemporal envelope performing collective integration and volitional choices correlating with consciousness. The “conscious pilot” is a metaphorical description for a mobile gamma-synchronized dendritic web as vehicle for a conscious agent/pilot which experiences and assumes control of otherwise non-conscious auto-pilot neurocomputation

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at √s = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and Otq(8), where the limits on the latter are the most stringent to date. [Figure not available: see fulltext.]

Two-particle azimuthal correlations in photonuclear ultraperipheral Pb plus Pb collisions at 5.02 TeV with ATLAS

Two-particle long-range azimuthal correlations are measured in photonuclear collisions using 1.7 nb − 1 of 5.02 TeV Pb + Pb collision data collected by the ATLAS experiment at the CERN Large Hadron Collider. Candidate events are selected using a dedicated high-multiplicity photonuclear event trigger, a combination of information from the zero-degree calorimeters and forward calorimeters, and from pseudorapidity gaps constructed using calorimeter energy clusters and charged-particle tracks. Distributions of event properties are compared between data and Monte Carlo simulations of photonuclear processes. Two-particle correlation functions are formed using charged-particle tracks in the selected events, and a template-fitting method is employed to subtract the nonflow contribution to the correlation. Significant nonzero values of the second- and third-order flow coefficients are observed and presented as a function of charged-particle multiplicity and transverse momentum. The results are compared with flow coefficients obtained in proton-proton and proton-lead collisions in similar multiplicity ranges, and with theoretical expectations. The unique initial conditions present in this measurement provide a new way to probe the origin of the collective signatures previously observed only in hadronic collision

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Non-ionizing energy loss causes bulk damage to the silicon sensors of the ATLAS pixel and strip detectors. This damage has important implications for data-taking operations, charged-particle track reconstruction, detector simulations, and physics analysis. This paper presents simulations and measurements of the leakage current in the ATLAS pixel detector and semiconductor tracker as a function of location in the detector and time, using data collected in Run 1 (2010–2012) and Run 2 (2015–2018) of the Large Hadron Collider. The extracted fluence shows a much stronger |z|-dependence in the innermost layers than is seen in simulation. Furthermore, the overall fluence on the second innermost layer is significantly higher than in simulation, with better agreement in layers at higher radii. These measurements are important for validating the simulation models and can be used in part to justify safety factors for future detector designs and interventions.publishedVersio

Improving topological cluster reconstruction using calorimeter cell timing in ATLAS

Clusters of topologically connected calorimeter cells around cells with large absolute signal-to-noise ratio (topo-clusters) are the basis for calorimeter signal reconstruction in the ATLAS experiment. Topological cell clustering has proven performant in LHC Runs 1 and 2. It is, however, susceptible to out-of-time pile-up of signals from soft collisions outside the 25 ns proton-bunch-crossing window associated with the event’s hard collision. To reduce this effect, a calorimeter-cell timing criterion was added to the signal-to-noise ratio requirement in the clustering algorithm. Multiple versions of this criterion were tested by reconstructing hadronic signals in simulated events and Run 2 ATLAS data. The preferred version is found to reduce the out-of-time pile-up jet multiplicity by ∼50% for jet pT ∼ 20 GeV and by ∼80% for jet pT 50 GeV, while not disrupting the reconstruction of hadronic signals of interest, and improving the jet energy resolution by up to 5% for 20 < pT < 30 GeV. Pile-up is also suppressed for other physics objects based on topo-clusters (electrons, photons, τ -leptons), reducing the overall event size on disk by about 6% in early Run 3 pileup conditions. Offline reconstruction for Run 3 includes the timing requirement

Software Performance of the ATLAS Track Reconstruction for LHC Run 3

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two