Fine-tuning activation specificity of G-protein-coupled receptors via automated path searching.

Physics-based simulation methods can grant atomistic insights into the molecular origin of the function of biomolecules. However, the potential of such approaches has been hindered by their low efficiency, including in the design of selective agonists where simulations of myriad protein-ligand combinations are necessary. Here, we describe an automated input-free path searching protocol that offers (within 14 d using Graphics Processing Unit servers) a minimum free energy path (MFEP) defined in high-dimension configurational space for activating sphingosine-1-phosphate receptors (S1PRs) by arbitrary ligands. The free energy distributions along the MFEP for four distinct ligands and three S1PRs reached a remarkable agreement with Bioluminescence Resonance Energy Transfer (BRET) measurements of G-protein dissociation. In particular, the revealed transition state structures pointed out toward two S1PR3 residues F263/I284, that dictate the preference of existing agonists CBP307 and BAF312 on S1PR1/5. Swapping these residues between S1PR1 and S1PR3 reversed their response to the two agonists in BRET assays. These results inspired us to design improved agonists with both strong polar head and bulky hydrophobic tail for higher selectivity on S1PR1. Through merely three in silico iterations, our tool predicted a unique compound scaffold. BRET assays confirmed that both chiral forms activate S1PR1 at nanomolar concentration, 1 to 2 orders of magnitude less than those for S1PR3/5. Collectively, these results signify the promise of our approach in fine agonist design for G-protein-coupled receptors.

Mechanism of agonist-induced activation of the human itch receptor MRGPRX1.

Mas-related G-protein-coupled receptors X1-X4 (MRGPRX1-X4) are 4 primate-specific receptors that are recently reported to be responsible for many biological processes, including itch sensation, pain transmission, and inflammatory reactions. MRGPRX1 is the first identified human MRGPR, and its expression is restricted to primary sensory neurons. Due to its dual roles in itch and pain signaling pathways, MRGPRX1 has been regarded as a promising target for itch remission and pain inhibition. Here, we reported a cryo-electron microscopy (cryo-EM) structure of Gq-coupled MRGPRX1 in complex with a synthetic agonist compound 16 in an active conformation at an overall resolution of 3.0 Å via a NanoBiT tethering strategy. Compound 16 is a new pain-relieving compound with high potency and selectivity to MRGPRX1 over other MRGPRXs and opioid receptor. MRGPRX1 was revealed to share common structural features of the Gq-mediated receptor activation mechanism of MRGPRX family members, but the variable residues in orthosteric pocket of MRGPRX1 exhibit the unique agonist recognition pattern, potentially facilitating to design MRGPRX1-specific modulators. Together with receptor activation and itch behavior evaluation assays, our study provides a structural snapshot to modify therapeutic molecules for itch relieving and analgesia targeting MRGPRX1.

An LC-MS-based workflow measures the export activity of S1P transporters.

Sphingosine-1-phosphate (S1P) is an active signaling metabolite synthesized by blood cells, exported into blood stream, and can trigger many downstream signaling pathways with disease implications. Understanding how S1P is transported is of great values for dissecting the function of S1P, but most existing methods for measuring S1P transporter activity use radioactive substrates or involve multiple workup steps, hindering their broader uses. In this study, we develop a workflow combining sensitive LC-MS measurement and a cell-based transporter protein system to measure the export activity of S1P transporter proteins. Our workflow demonstrated good applications in studying different S1P transporters SPNS2 and MFSD2B, WT and mutated protein, and different protein substrates. In summary, we provide a simple yet versatile workflow for measuring the export activity of S1P transporters, facilitating future studies of S1P transport mechanism and drug development.

Integration of multi-omics data reveals cis-regulatory variants that are associated with phenotypic differentiation of eastern from western pigs.

BACKGROUND: The genetic mechanisms that underlie phenotypic differentiation in breeding animals have important implications in evolutionary biology and agriculture. However, the contribution of cis-regulatory variants to pig phenotypes is poorly understood. Therefore, our aim was to elucidate the molecular mechanisms by which non-coding variants cause phenotypic differences in pigs by combining evolutionary biology analyses and functional genomics. RESULTS: We obtained a high-resolution phased chromosome-scale reference genome with a contig N50 of 18.03 Mb for the Luchuan pig breed (a representative eastern breed) and profiled potential selective sweeps in eastern and western pigs by resequencing the genomes of 234 pigs. Multi-tissue transcriptome and chromatin accessibility analyses of these regions suggest that tissue-specific selection pressure is mediated by promoters and distal cis-regulatory elements. Promoter variants that are associated with increased expression of the lysozyme (LYZ) gene in the small intestine might enhance the immunity of the gastrointestinal tract and roughage tolerance in pigs. In skeletal muscle, an enhancer-modulating single-nucleotide polymorphism that is associated with up-regulation of the expression of the troponin C1, slow skeletal and cardiac type (TNNC1) gene might increase the proportion of slow muscle fibers and affect meat quality. CONCLUSIONS: Our work sheds light on the molecular mechanisms by which non-coding variants shape phenotypic differences in pigs and provides valuable resources and novel perspectives to dissect the role of gene regulatory evolution in animal domestication and breeding.

Bearing Fault Diagnosis Based on an Enhanced Image Representation Method of Vibration Signal and Conditional Super Token Transformer.

Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) is an advanced deconvolution method, which can effectively inhibit the interference of background noise and distinguish the fault period by calculating the multipoint kurtosis values. However, multipoint kurtosis (MKurt) could lead to misjudgment since it is sensitive to spurious noise spikes. Considering that L-kurtosis has good robustness with noise, this paper proposes a multipoint envelope L-kurtosis (MELkurt) method for establishing the temporal features. Then, an enhanced image representation method of vibration signals is proposed by employing the Gramian Angular Difference Field (GADF) method to convert the MELkurt series into images. Furthermore, to effectively learn and extract the features of GADF images, this paper develops a deep learning method named Conditional Super Token Transformer (CSTT) by incorporating the Super Token Transformer block, Super Token Mixer module, and Conditional Positional Encoding mechanism into Vision Transformer appropriately. Transfer learning is introduced to enhance the diagnostic accuracy and generalization capability of the designed CSTT. Consequently, a novel bearing fault diagnosis framework is established based on the presented enhanced image representation and CSTT. The proposed method is compared with Vision Transformer and some CNN-based models to verify the recognition effect by two experimental datasets. The results show that MELkurt significantly improves the fault feature enhancement ability with superior noise robustness to kurtosis, and the proposed CSTT achieves the highest diagnostic accuracy and stability.

Comparative transcriptome and DNA methylation analysis in temperature-sensitive genic male sterile wheat BS366.

BACKGROUND: Known as the prerequisite component for the heterosis breeding system, the male sterile line determines the hybrid yield and seed purity. Therefore, a deep understanding of the mechanism and gene network that leads to male sterility is crucial. BS366, a temperature-sensitive genic male sterile (TGMS) line, is male sterile under cold conditions (12 °C with 12 h of daylight) but fertile under normal temperature (20 °C with 12 h of daylight). RESULTS: During meiosis, BS366 was defective in forming tetrads and dyads due to the abnormal cell plate. During pollen development, unusual vacuolated pollen that could not accumulate starch grains at the binucleate stage was also observed. Transcriptome analysis revealed that genes involved in the meiotic process, such as sister chromatid segregation and microtubule-based movement, were repressed, while genes involved in DNA and histone methylation were induced in BS366 under cold conditions. MethylRAD was used for reduced DNA methylation sequencing of BS366 spikes under both cold and control conditions. The differentially methylated sites (DMSs) located in the gene region were mainly involved in carbohydrate and fatty acid metabolism, lipid metabolism, and transport. Differentially expressed and methylated genes were mainly involved in cell division. CONCLUSIONS: These results indicated that the methylation of genes involved in carbon metabolism or fatty acid metabolism might contribute to male sterility in BS366 spikes, providing novel insight into the molecular mechanism of wheat male sterility.

Genome-wide identification and transcriptional characterization of DNA methyltransferases conferring temperature-sensitive male sterility in wheat.

BACKGROUND: DNA methyltransferase (DMT) genes contribute to plant stress responses and development by de novo establishment and subsequent maintenance of DNA methylation during replication. The photoperiod and/or temperature-sensitive genic male sterile (P/TGMS) lines play an important role in hybrid seed production of wheat. However, only a few studies have reported on the effect of DMT genes on temperature-sensitive male sterility of wheat. Although DMT genes have been investigated in some plant species, the identification and analysis of DMT genes in wheat (Triticum aestivum L.) based on genome-wide levels have not been reported. RESULTS: In this study, a detailed overview of phylogeny of 52 wheat DMT (TaDMT) genes was presented. Homoeolog retention for TaDMT genes was significantly above the average retention rate for whole-wheat genes, indicating the functional importance of many DMT homoeologs. We found that the strikingly high number of TaDMT genes resulted mainly from the significant expansion of the TaDRM subfamily. Intriguingly, all 5 paralogs belonged to the wheat DRM subfamily, and we speculated that tandem duplications might play a crucial role in the TaDRM subfamily expansion. Through the transcriptional analysis of TaDMT genes in a TGMS line BS366 and its hybrids with the other six fertile lines under sterile and fertile conditions, we concluded that TaCMT-D2, TaMET1-B1, and TaDRM-U6 might be involved in male sterility in BS366. Furthermore, a correlation analysis showed that TaMET1-B1 might negatively regulate the expression of TaRAFTIN1A, an important gene for pollen development, so we speculated regarding an epigenetic regulatory mechanism underlying the male sterility of BS366 via the interaction between TaMET1-B1 and TaRAFTIN1A. CONCLUSIONS: Our findings presented a detailed phylogenic overview of the DMT genes and could provide novel insights into the effects of DMT genes on TGMS wheat.

Gearbox Fault Diagnosis Based on Hierarchical Instantaneous Energy Density Dispersion Entropy and Dynamic Time Warping.

The accurate fault diagnosis of gearboxes is of great significance for ensuring safe and efficient operation of rotating machinery. This paper develops a novel fault diagnosis method based on hierarchical instantaneous energy density dispersion entropy (HIEDDE) and dynamic time warping (DTW). Specifically, the instantaneous energy density (IED) analysis based on singular spectrum decomposition (SSD) and Hilbert transform (HT) is first applied to the vibration signal of gearbox to acquire the IED signal, which is designed to reinforce the fault feature of the signal. Then, the hierarchical dispersion entropy (HDE) algorithm developed in this paper is used to quantify the complexity of the IED signal to obtain the HIEDDE as fault features. Finally, the DTW algorithm is employed to recognize the fault types automatically. The validity of the two parts that make up the HIEDDE algorithm, i.e., the IED analysis for fault features enhancement and the HDE algorithm for quantifying the information of signals, is numerically verified. The proposed method recognizes the fault patterns of the experimental data of gearbox accurately and exhibits advantages over the existing methods such as multi-scale dispersion entropy (MDE) and refined composite MDE (RCMDE).

Rolling Bearing Fault Diagnosis Based on an Improved HTT Transform.

When rolling bearing failure occurs, vibration signals generally contain different signal components, such as impulsive fault feature signals, background noise and harmonic interference signals. One of the most challenging aspects of rolling bearing fault diagnosis is how to inhibit noise and harmonic interference signals, while enhancing impulsive fault feature signals. This paper presents a novel bearing fault diagnosis method, namely an improved Hilbert time-time (IHTT) transform, by combining a Hilbert time-time (HTT) transform with principal component analysis (PCA). Firstly, the HTT transform was performed on vibration signals to derive a HTT transform matrix. Then, PCA was employed to de-noise the HTT transform matrix in order to improve the robustness of the HTT transform. Finally, the diagonal time series of the de-noised HTT transform matrix was extracted as the enhanced impulsive fault feature signal and the contained fault characteristic information was identified through further analyses of amplitude and envelope spectrums. Both simulated and experimental analyses validated the superiority of the presented method for detecting bearing failures.

Rolling Bearing Fault Diagnosis Based on Optimal Notch Filter and Enhanced Singular Value Decomposition.

The impulsive fault feature signal of rolling bearings at the early failure stage is easily contaminated by the fundamental frequency (i.e., the rotation frequency of the shaft) signal and background noise. To address this problem, this paper puts forward a rolling bearing weak fault diagnosis method with the combination of optimal notch filter and enhanced singular value decomposition. Firstly, in order to eliminate the interference of the fundamental frequency signal, the original signal was processed by the notch filter with the fundamental frequency as the center frequency and with a varying bandwidth to get a series of corresponding notch filter signals. Secondly, the Teager energy entropy index was adopted to adaptively determine the optimal bandwidth to complete the optimal notch filter analysis on the raw vibration signal and obtain the corresponding optimal notch filter signal. Thirdly, an enhanced singular value decomposition de-nosing method was employed to de-noise the optimal notch filter signal. Finally, the envelope spectrum analysis was conducted on the de-noised signal to extract the fault characteristic frequencies. The effectiveness of the presented method was demonstrated via simulation and experiment verifications. In addition, the minimum entropy deconvolution, Kurtogram and Infogram methods were employed for comparisons to show the advantages of the presented method.

Rotor Fault Diagnosis Based on Characteristic Frequency Band Energy Entropy and Support Vector Machine.

Rotor is a widely used and easily defected mechanical component. Thus, it is significant to develop effective techniques for rotor fault diagnosis. Fault signature extraction and state classification of the extracted signatures are two key steps for diagnosing rotor faults. To complete the accurate recognition of rotor states, a novel evaluation index named characteristic frequency band energy entropy (CFBEE) was proposed to extract the defective features of rotors, and support vector machine (SVM) was employed to automatically identify the rotor fault types. Specifically, the raw vibration signal of rotor was first analyzed by a joint time-frequency method based on improved singular spectrum decomposition (ISSD) and Hilbert transform (HT) to derive its time-frequency spectrum (TFS), which is named ISSD-HT TFS in this paper. Then, the CFBEE of the ISSD-HT TFS was calculated as the fault feature vector. Finally, SVM was used to complete the automatic identification of rotor faults. Simulated processing results indicate that ISSD improves the end effects of singular spectrum decomposition (SSD) and is superior to empirical mode decomposition (EMD) in extracting the sub-components of rotor vibration signal. The ISSD-HT TFS can more accurately reflect the time-frequency information compared to the EMD-HT TFS. Experimental verification demonstrates that the proposed method can accurately identify rotor defect types and outperform some other methods.

PBSword: a web server for searching similar protein-protein binding sites.

PBSword is a web server designed for efficient and accurate comparisons and searches of geometrically similar protein-protein binding sites from a large-scale database. The basic idea of PBSword is that each protein binding site is first represented by a high-dimensional vector of 'visual words', which characterizes both the global and local shape features of the binding site. It then uses a scalable indexing technique to search for those binding sites whose visual words representations are similar to that of the query binding site. Our system is able to return ranked results of binding sites in short time from a database of 194 322 domain-domain binding sites. PBSword supports query by protein ID and by new structures uploaded by users. PBSword is a useful tool to investigate functional connections among proteins based on the local structures of binding site and has potential applications to protein-protein docking and drug discovery. The system is hosted at http://pbs.rnet.missouri.edu.

DOMMINO: a database of macromolecular interactions.

With the growing number of experimentally resolved structures of macromolecular complexes, it becomes clear that the interactions that involve protein structures are mediated not only by the protein domains, but also by various non-structured regions, such as interdomain linkers, or terminal sequences. Here, we present DOMMINO (http://dommino.org), a comprehensive database of macromolecular interactions that includes the interactions between protein domains, interdomain linkers, N- and C-terminal regions and protein peptides. The database complements SCOP domain annotations with domain predictions by SUPERFAMILY and is automatically updated every week. The database interface is designed to provide the user with a three-stage pipeline to study macromolecular interactions: (i) a flexible search that can include a PDB ID, type of interaction, SCOP family of interacting proteins, organism name, interaction keyword and a minimal threshold on the number of contact pairs; (ii) visualization of subunit interaction network, where the user can investigate the types of interactions within a macromolecular assembly; and (iii) visualization of an interface structure between any pair of the interacting subunits, where the user can highlight several different types of residues within the interfaces as well as study the structure of the corresponding binary complex of subunits.

Research Note: Relationships between texture and water property measurements in raw intact broiler breast fillets with the wooden breast condition.

Relationships between texture measurements and meat water properties were investigated in raw intact broiler breast fillets with the wooden breast (WB) condition. Texture measurements included subjective WB scores and blunt Meullenet-Owens Razor Shear (BMORS). Water properties were determined with low-field nuclear magnetic resonance (LF-NMR). Spearman correlation was used to estimate relationships between WB scores and water properties, while Pearson correlation was used for relationships between BMORS force and water properties. LF-NMR measurements exhibited 3 water components: protein-associated or hydration water T2b, intra-myofibrillar water or immobilized water T21, and extra-myofibrillar water or free water T22 in chicken breast meat. Significant and strong Spearman correlations were found between the WB scores and T21 time constant, the abundance (normalized areas) of T22, and the proportion of T21 and T22 (rs > 0.60, P < 0.001). Strong Pearson correlations (r = 0.72) were noted only between the T21 time constant and BMORS force. These results demonstrate that water may contribute to the specific texture characteristics measured with subjective WB scoring (palpable hardness and rigidity) and BMORS (hardness and share force) in raw broiler breast fillets with the WB condition.

Combined Relaxation Spectra for the Prediction of Meat Quality: A Case Study on Broiler Breast Fillets with the Wooden Breast Condition.

This study evaluated the potential of using combined relaxation (CRelax) spectra within time-domain nuclear magnetic resonance (TD-NMR) measurements to predict meat quality. Broiler fillets affected by different severities of the wooden breast (WB) conditions were used as case-study samples because of the broader ranges of meat-quality variations. Partial least squares regression (PLSR) models were established to predict water-holding capacity (WHC) and meat texture, demonstrating superior CRelax capabilities for predicting meat quality. Additionally, a partial least squares discriminant analysis (PLS-DA) model was developed to predict WB severity based on CRelax spectra. The models exhibited high accuracy in distinguishing normal fillets from those affected by the WB condition and demonstrated competitive performance in classifying WB severity. This research contributes innovative insights into advanced spectroscopic techniques for comprehensive meat-quality evaluation, with implications for enhancing precision in meat applications.

Structural insights into the activation and inhibition of CXC chemokine receptor 3.

The chemotaxis of CD4+ type 1 helper cells and CD8+ cytotoxic lymphocytes, guided by interferon-inducible CXC chemokine 9-11 (CXCL9-11) and CXC chemokine receptor 3 (CXCR3), plays a critical role in type 1 immunity. Here we determined the structures of human CXCR3-DNGi complexes activated by chemokine CXCL11, peptidomimetic agonist PS372424 and biaryl-type agonist VUF11222, and the structure of inactive CXCR3 bound to noncompetitive antagonist SCH546738. Structural analysis revealed that PS372424 shares a similar orthosteric binding pocket to the N terminus of CXCL11, while VUF11222 buries deeper and activates the receptor in a distinct manner. We showed an allosteric binding site between TM5 and TM6, accommodating SCH546738 in the inactive CXCR3. SCH546738 may restrain the receptor at an inactive state by preventing the repacking of TM5 and TM6. By revealing the binding patterns and the pharmacological properties of the four modulators, we present the activation mechanisms of CXCR3 and provide insights for future drug development.

Fast protein binding site comparisons using visual words representation.

MOTIVATION: Finding geometrically similar protein binding sites is crucial for understanding protein functions and can provide valuable information for protein-protein docking and drug discovery. As the number of known protein-protein interaction structures has dramatically increased, a high-throughput and accurate protein binding site comparison method is essential. Traditional alignment-based methods can provide accurate correspondence between the binding sites but are computationally expensive. RESULTS: In this article, we present a novel method for the comparisons of protein binding sites using a 'visual words' representation (PBSword). We first extract geometric features of binding site surfaces and build a vocabulary of visual words by clustering a large set of feature descriptors. We then describe a binding site surface with a high-dimensional vector that encodes the frequency of visual words, enhanced by the spatial relationships among them. Finally, we measure the similarity of binding sites by utilizing metric space operations, which provide speedy comparisons between protein binding sites. Our experimental results show that PBSword achieves a comparable classification accuracy to an alignment-based method and improves accuracy of a feature-based method by 36% on a non-redundant dataset. PBSword also exhibits a significant efficiency improvement over an alignment-based method.

A high-throughput KASP assay provides insights into the evolution of multiple resistant mutations in populations of the two-spotted spider mite Tetranychus urticae across China.

BACKGROUND: The two-spotted spider mite (TSSM), Tetranychus urticae (Acari: Tetranychidae), is a cosmopolitan phytophagous pest in agriculture and horticulture. It has developed resistance to many acaricides by target-site mutations. Understanding the status and evolution of resistant mutations in the field is essential for resistance management. Here, we applied a high-throughput Kompetitive allele-specific polymerase chain reaction (KASP) method for detecting six mutations conferring resistance to four acaricides of the TSSM. We genotyped 3274 female adults of TSSM from 43 populations collected across China in 2017, 2020, and 2021. RESULTS: The KASP genotyping of 24 testing individuals showed 99% agreement with Sanger sequencing results. KASP assays showed that most populations had a high frequency of mutations conferring avermectin (G314D and G326E) and pyridaben (H92R) resistance. The frequency of mutation conferring bifenazate (A269V and G126S) and etoxazole (I1017F) resistance was relatively low. Multiple mutations were common in the TSSM, with 70.2% and 24.6% of individuals having 2-6 and 7-10 of 10 possible resistant alleles, respectively. No loci were linked in most populations among the six mutations, indicating the development of multiple resistance is mainly by independent selection. However, G314D and I1017F on the nuclear genome deviated from Hardy-Weinberg equilibrium in most populations, indicating significant selective pressure on TSSM populations by acaricides or fitness cost of the mutations in the absence of acaricide selection. CONCLUSION: Our study revealed that the high frequency of TSSMs evolved multiple resistant mutations in population and individual levels by independent selection across China, alarming for managing multiple-acaricides resistance. © 2023 Society of Chemical Industry.

KASP genotyping and semi-quantitation of G275E mutation in the α6 subunit of Thrips palmi nAChR gene conferring spinetoram resistance.

BACKGROUND: Pesticide resistance is a long-standing and growing problem in the chemical control of invertebrate pests. Molecular diagnostic methods can facilitate pesticide resistance management by accurately and efficiently detecting resistant mutations and their frequency. In this study, the kompetitive allele specific PCR (KASP) approach, a technology for high-throughput single nucleotide polymorphism (SNP) genotyping, is validated as a useful method for characterizing genotypes at a pesticide-resistance locus for the first time. We focus on the spinetoram resistance mutation of G275E in the nicotinic acetylcholine receptor alpha 6 (nAChR α6) subunit gene of Thrips palmi. RESULTS: Of the 341 individuals of Thrips palmi tested, 98.24% were successfully genotyped, with 100% concordance with Sanger sequencing results. We then quantitatively mixed genomic DNA of known genotypes to establish 21 DNA mixtures with a resistant allele frequency ranging from 0 to 100% at steps of 5%. The linear discriminant analysis (LDA) showed that 75.8% of original grouped cases were correctly classified; six groups had no overlap in membership (resistant allele frequency: 0%, 5%, 10-75%, 80-85%, 90-95%, and 100%). When we chose 11 pooled samples with 10% steps for LDA, 84.4% of original grouped cases were correctly classified; seven groups had no overlap in membership (0%, 10%, 20-30%, 40-70%, 80%, 90%, 100%). The results indicated that KASP applied to pooled samples may provide a semi-quantitative estimate of resistance. CONCLUSIONS: Our study points to the suitability of KASP for high-throughput genotyping of genotypes affecting pesticide resistance and semi-quantitative assessments of resistance allele frequencies in populations. © 2023 Society of Chemical Industry.