Subtle changes in ligand-receptor interactions dramatically alter transcriptional outcomes of pregnane X receptor modulators
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Engineering topics
Publications and source records attributed to Wu, Jing.
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Nuclear receptors are ligand-activated transcription factors that can often be useful drug targets. Unfortunately, ligand promiscuity leads to two-thirds of receptors remaining clinically untargeted. PXR is a nuclear receptor that can be activated by diverse compounds to elevate metabolism, negatively impacting drug efficacy and safety. This presents a barrier to drug development because compounds designed to target other proteins must avoid PXR activation while retaining potency for the desired target. This problem could be avoided by using PXR antagonists, but these compounds are rare, and their molecular mechanisms remain unknown. Here, we report structurally related PXR-selective agonists and antagonists and their corresponding co-crystal structures to describe mechanisms of antagonism and selectivity. Structural and computational approaches show that antagonists induce PXR conformational changes incompatible with transcriptional coactivator recruitment. These results guide the design of compounds with predictable agonist/antagonist activities and bolster efforts to generate antagonists to prevent PXR activation interfering with other drugs.
Abstract Bromodomain and extraterminal (BET) proteins are extensively studied in multiple pathologies, including cancer. BET proteins modulate transcription of various genes, including those synonymous with cancer, such as MYC. Thus, BET inhibitors are a major area of drug development efforts. (+)-JQ1 (JQ1) is the prototype inhibitor and is a common tool to probe BET functions. While showing therapeutic promise, JQ1 is not clinically usable, partly due to metabolic instability. Here, we show that JQ1 and the BET-inactive (−)-JQ1 are agonists of pregnane X receptor (PXR), a nuclear receptor that transcriptionally regulates genes encoding drug-metabolizing enzymes such as CYP3A4, which was previously shown to oxidize JQ1. A PXR-JQ1 co-crystal structure identified JQ1′s tert-butyl moiety as a PXR anchor and explains binding by (−)-JQ1. Analogs differing at the tert-butyl lost PXR binding, validating our structural findings. Evaluation in liver cell models revealed both PXR-dependent and PXR-independent modulation of CYP3A4 expression by BET inhibitors. We have characterized a non-BET JQ1 target, a mechanism of physiological JQ1 instability, a biological function of (−)-JQ1, and BET-dependent transcriptional regulation of drug metabolism genes.
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Here, a novel nanoscale phase separation process has been discovered to promote the growth and segregation of single-crystal LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811). This process occurs directly during high-temperature calcination without significant agglomeration. The key lies in converting transition metal hydroxide (TM(OH) 2 ) precursors with well-controlled morphology into transition metal oxide (TMO) intermediates before reacting them with lithium salt. The nanoscale redistribution of Ni in TMO, resulting from the concurrent formation of spinel and rock salt phases, helps to deagglomerate the clusters of later-formed NMC811 crystals. The as-prepared single-crystal NMC811 is further validated in a 2Ah pouch cell, demonstrating 1,000 stable cycles. The fundamentally new reaction mechanism of single-crystal growth and segregation provides a new direction for large-scale synthesis of a broad range of single crystals for advanced energy storage.
Superconducting microwave circuits with Josephson junctions, the major platform for quantum computing, can only reach the full capability when connected. This requires an efficient protocol to distribute microwave entanglement. While quantum computers typically use discrete-variable (DV) methods for information encoding, the entire continuous-variable (CV) degree of freedom in electromagnetic fields must be utilized to achieve the highest entanglement distribution rate. Here, we propose a hybrid protocol to resolve the incompatibility between DV microwave quantum computers and CV quantum communications. CV microwave entanglement is distributed using optical swapping of optical-microwave entanglement pairs. To interface with DV microwave quantum computers, we further design a hybrid circuit to simultaneously convert and distill high-quality DV entanglement from noisy CV entanglement. The hybrid circuit is trained with machine-learning algorithms, ensuring high entanglement fidelity and generation rate. In conclusion, our work not only provides a practical method to realize efficient quantum links for superconducting microwave quantum computers, but also opens avenues to bridge the gap between DV and CV quantum systems.
Escherichia coli is considered an opportunistic pathogen and an indicator for antimicrobial resistance (AMR) monitoring. Despite many reports on its AMR monitoring, studies based on genome-based analysis of AMR genes are still insufficient. Here, 181 E. coli strains were isolated from anal swab samples collected from pigs and chickens of animal farms located in Eastern China and sequenced through the Illumina platform. The results showed that 87.85% (159/181) of the E. coli isolates were multidrug-resistant (MDR). Ampicillin (AMP)- spectinomycin (SPT)- tetracycline (TET)- florfenicol (FFC)- sulfisoxazole (SF)- trimethoprim/sulfamethoxazole (SXT) was the predominant AMR pattern. By whole-genome sequencing, we found that ST10 (10.49%, 19/181) and ST48 (7.18%, 13/181) were major sequence types. IncFIB and IncX1 were the most prevalent plasmid replicons. The AMR genes bla NDM-5 (1.10%, 2/181), mcr -1 (1.10%, 2/181), tet (X4) (1.10%, 2/181), and cfr (6.08%, 11/181) were also found in these isolates. In addition, among the 169 virulence genes detected, we identified ast A (37.02%, 67/181), hly A (1.66%, 3/181), hly B (1.66%, 3/181) and hly D (1.66%, 3/181), which were closely related to heat-stable enterotoxin 1 and α-hemolysin. In addition, there were 33 virulence genes associated with the iron uptake system, and 46 were adhesion-related genes. Our study highlighted the need for routine surveillance of AMR with advanced genomic approaches, providing up-to-date data on the prevalence of AMR for the development and execution of antimicrobial stewardship policy.
The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic studies, continued advancements in genome sequencing and bioinformatics have provided the opportunity to capitalize on whole-genome information. As new sequencing platforms can routinely provide high-quality sequencing data for sufficient genome coverage to genotype various breeding populations, a limitation comes in the time and cost of library construction when multiplexing a large number of samples. Here we describe a high-throughput whole-genome skim-sequencing (skim-seq) approach that can be utilized for a broad range of genotyping and genomic characterization. Using optimized low-volume Illumina Nextera chemistry, we developed a skim-seq method and combined up to 960 samples in one multiplex library using dual index barcoding. With the dual-index barcoding, the number of samples for multiplexing can be adjusted depending on the amount of data required, and could be extended to 3,072 samples or more. Panels of doubled haploid wheat lines ( Triticum aestivum , CDC Stanley x CDC Landmark), wheat-barley ( T . aestivum x Hordeum vulgare ) and wheat-wheatgrass ( Triticum durum x Thinopyrum intermedium ) introgression lines as well as known monosomic wheat stocks were genotyped using the skim-seq approach. Bioinformatics pipelines were developed for various applications where sequencing coverage ranged from 1 × down to 0.01 × per sample. Using reference genomes, we detected chromosome dosage, identified aneuploidy, and karyotyped introgression lines from the skim-seq data. Leveraging the recent advancements in genome sequencing, skim-seq provides an effective and low-cost tool for routine genotyping and genetic analysis, which can track and identify introgressions and genomic regions of interest in genetics research and applied breeding programs.
Neuromorphic computing provides a means for achieving faster and more energy efficient computations than conventional digital computers for artificial intelligence (AI). However, its current accuracy is generally less than the dominant software-based AI. The key to improving accuracy is to reduce the intrinsic randomness of memristive devices, emulating synapses in the brain for neuromorphic computing. Here using a planar device as a model system, the controlled formation of conduction channels is achieved with high oxygen vacancy concentrations through the design of sharp protrusions in the electrode gap, as observed by X-ray multimodal imaging of both oxygen stoichiometry and crystallinity. Classical molecular dynamics simulations confirm that the controlled formation of conduction channels arises from confinement of the electric field, yielding a reproducible spatial distribution of oxygen vacancies across switching cycles. Furthermore, this work demonstrates an effective route to control the otherwise random electroforming process by electrode design, facilitating the development of more accurate memristive devices for neuromorphic computing.
The 48 human nuclear receptors (NRs) form a superfamily of transcription factors that regulate major physiological and pathological processes. Emerging evidence suggests that NR crosstalk can fundamentally change our understanding of NR biology, but detailed molecular mechanisms of crosstalk are lacking. Here, we report the molecular basis of crosstalk between the pregnane X receptor (PXR) and constitutive androstane receptor (CAR), where they form a novel heterodimer, resulting in their mutual inhibition. PXR and CAR regulate drug metabolism and energy metabolism. Although they have been broadly perceived as functionally redundant, a growing number of reports suggests a mutual inhibitory relation, but their precise mode of coordinated action remains unknown. Using methods including RNA sequencing, small-angle X-ray scattering and crosslinking mass spectrometry we demonstrate that the mutual inhibition altered gene expression globally and is attributed to the novel PXR–CAR heterodimerization via the same interface used by each receptor to heterodimerize with its functional partner, retinoid X receptor (RXR). These findings establish an unexpected functional relation between PXR, CAR and RXR, change the perceived functional relation between PXR and CAR, open new perspectives on elucidating their role and designing approaches to regulate them, and highlight the importance to comprehensively investigate nuclear receptor crosstalk.
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The physics of flat band is novel and rich but difficult to access. In this regard, recently twisting of bilayer van der Waals (vdW)-bounded two-dimensional (2D) materials has attracted much attention, because the reduction of Brillouin zone will eventually lead to a diminishing kinetic energy. Alternatively, one may start with a 2D kagome lattice, which already possesses flat bands at the Fermi level, but unfortunately these bands connect quadratically to other (dispersive) bands, leading to undesirable effects. Here, we propose, by first-principles calculation and tight-binding modeling, that the same bilayer twisting approach can be used to isolate the kagome flat bands. As the starting kinetic energy is already vanishingly small, the interlayer vdW potential is always sufficiently large irrespective of the twisting angle. As such the electronic states in the (connected) flat bands become unstable against a spontaneous Wigner crystallization, which is expected to have interesting interplays with other flat-band phenomena such as novel superconductivity and anomalous quantum Hall effect.
The discovery of ferroelectricity in HfO 2 -based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO 2 learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO 2 with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO 2 to related material systems including dopants and defects.