Back in time to the Gly-rich prototype of the phosphate binding elementary function.

Binding of nucleotides and their derivatives is one of the most ancient elementary functions dating back to the Origin of Life. We review here the works considering one of the key elements in binding of (di)nucleotide-containing ligands - phosphate binding. We start from a brief discussion of major participants, conditions, and events in prebiotic evolution that resulted in the Origin of Life. Tracing back to the basic functions, including metal and phosphate binding, and, potentially, formation of primitive protein-protein interactions, we focus here on the phosphate binding. Critically assessing works on the structural, functional, and evolutionary aspects of phosphate binding, we perform a simple computational experiment reconstructing its most ancient and generic sequence prototype. The profiles of the phosphate binding signatures have been derived in form of position-specific scoring matrices (PSSMs), their peculiarities depending on the type of the ligands have been analyzed, and evolutionary connections between them have been delineated. Then, the apparent prototype that gave rise to all relevant phosphate-binding signatures had also been reconstructed. We show that two major signatures of the phosphate binding that discriminate between the binding of dinucleotide- and nucleotide-containing ligands are GxGxxG and GxxGxG, respectively. It appears that the signature archetypal for dinucleotide-containing ligands is more generic, and it can frequently bind phosphate groups in nucleotide-containing ligands as well. The reconstructed prototype's key signature GxGGxG underlies the role of glycine residues in providing flexibility and interactions necessary for binding the phosphate groups. The prototype also contains other ancient amino acids, valine, and alanine, showing versatility towards evolutionary design and functional diversification.

Potential mechanism of ginseng in the treatment of periodontitis based on network pharmacology and molecular docking.

OBJECTIVES: To explore the mechanism of ginseng in the treatment of periodontitis based on network pharmacology and molecular docking technology. METHODS: Potential targets of ginseng and periodontitis were obtained through various databases. The intersection targets of ginseng and periodontitis were obtained by using VENNY, the protein-protein interaction network relationship diagram was formed on the STRING platform, the core target diagram was formed by Cytoscape software, and the ginseng-active ingredient-target network diagram was constructed. The selected targets were screened for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. The core targets of ginseng's active ingredients in treating periodontitis were analyzed by molecular docking technique. RESULTS: The 22 ginseng's active ingredients, 591 potential targets of ginseng's active ingredients, 2 249 periodontitis gene targets, and 145 ginseng-periodontitis intersection targets were analyzed. Ginseng had strong binding activity on core targets such as vascular endothelial growth factor A and epidermal growth factor receptor, as well as hypoxia induced-factor 1 (HIF-1) signaling pathway and phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling pathway. CONCLUSIONS: Ginseng and its active components can regulate several signaling pathways such as HIF-1 and PI3K-Akt, thereby indicating that ginseng may play a role in treating periodontitis through multiple pathways.

The application of mesenchymal stem cells in the treatment of traumatic brain injury: mechanisms, results, and problems.

Mesenchymal stem cells (MSCs) are multipotent stromal cells that can be derived from a wide variety of human tissues and organs. They can differentiate into a variety of cell types, including osteoblasts, adipocytes, and chondrocytes, and thus show great potential in regenerative medicine. Traumatic brain injury (TBI) is an organic injury to brain tissue with a high rate of disability and death caused by an external impact or concussive force acting directly or indirectly on the head. The current treatment of TBI mainly includes symptomatic, pharmacological, and rehabilitation treatment. Although some efficacy has been achieved, the definitive recovery effect on neural tissue is still limited. Recent studies have shown that MSC therapies are more effective than traditional treatment strategies due to their strong multi-directional differentiation potential, self-renewal capacity, and low immunogenicity and homing properties, thus MSCs are considered to play an important role and are an ideal cell for the treatment of injurious diseases, including TBI. In this paper, we systematically reviewed the role and mechanisms of MSCs and MSC-derived exosomes in the treatment of TBI, thereby providing new insights into the clinical applications of MSCs and MSC-derived exosomes in the treatment of central nervous system disorders.

Advances in combined application of dental stem cells and small-molecule drugs in regenerative medicine.

Teeth are a kind of masticatory organs of special histological origin, unique to vertebrates, playing an important role in chewing, esthetics, and auxiliary pronunciation. In the past decades, with the development of tissue engineering and regenerative medicine, the studies of mesenchymal stem cells (MSCs) gradually attracted the interest of researchers. Accordingly, several types of MSCs have been successively isolated in teeth or teeth-related tissues, including dental pulp stem cells, periodontal ligament stem cells, stem cells from human exfoliated deciduous teeth, dental follicle stem cells, stem cells from apical papilla and gingival mesenchymal stem cells. These dental stem cells (DSCs) are easily accessible, possess excellent stem cell characteristics, such as high proliferation rates and profound immunomodulatory properties. Small-molecule drugs are widely used and show great advantages in clinical practice. As research progressed, small-molecule drugs are found to have various complex effects on the characteristics of DSCs, especially the enhancement of biological characteristics of DSCs, which has gradually become a hot issue in the field of DSCs research. This review summarizes the background, current status, existing problems, future research directions, and prospects of the combination of DSCs with three common small-molecule drugs: aspirin, metformin, and berberine.

TGF-ß1 promotes human breast cancer angiogenesis and malignant behavior by regulating endothelial-mesenchymal transition.

Background: Endothelial-mesenchymal transition (EndMT) is an important process of angiogenesis, which plays a significant role in in tumor invasion and metastasis, while its regulatory mechanisms in breast cancer remain to be fully elucidated. We previously demonstrated that tumor-associated macrophages (TAMs) can induce EndMT in endothelial cells by secreting CCL18 through the activation of the TGF-ß and Notch signaling pathways in breast cancer. This study was designed to study the role of EndMT in breast cancer angiogenesis and progression in order to explore the underlying mechanism. Methods: Immunohistochemistry (IHC) was used to evaluate the expression of microvascular density (MVD) and EndMT markers in breast cancer. TGF-ß1 was used to induce EndMT models of differentiated-endothelial breast cancer stem-like cells (BCSLCs). In vitro cell migration, proliferation and matrigel tube-formation assays, as well as in vivo nude mouse tumor-bearing model and nude mouse dorsal skinfold window chamber (DSWC) model, were utilized to investigate the effects in order to explore the mechanism of EndMT induced by TGF-ß1 on breast cancer progression. Results: In this study, we demonstrated that the EndMT markers were positively associated with MVD indicating unfavorable prognosis of invasive ductal carcinoma (IDC) patients. Functionally, TGF-ß1 promoted migration, proliferation and angiogenesis of differentiated-endothelial BCSLCs by inducing EndMT in vitro and promoted tumor growth and angiogenesis in vivo. Mechanically, we revealed TGF-ß1 induced EndMT by activation of TGF-ß and Notch signaling pathways with increase of p-Smad2/3 and Notch1 expression. Moreover, we found Snail and Slug were key factors of TGF-ß and Notch signaling pathways. Conclusion: Our findings elucidated the mechanism of TGF-ß1 in the promotion of angiogenesis and progression by EndMT in breast cancer.

Construction of the Six-lncRNA Prognosis Signature as a Novel Biomarker in Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a common malignant gastrointestinal tumor threatening global human health. For patients diagnosed with ESCC, determining the prognosis is a huge challenge. Due to their important role in tumor progression, long non-coding RNAs (lncRNAs) may be putative molecular candidates in the survival prediction of ESCC patients. Here, we obtained three datasets of ESCC lncRNA expression profiles (GSE53624, GSE53622, and GSE53625) from the Gene Expression Omnibus (GEO) database. The method of statistics and machine learning including survival analysis and LASSO regression analysis were applied. We identified a six-lncRNA signature composed of AL445524.1, AC109439.2, LINC01273, AC015922.3, LINC00547, and PSPC1-AS2. Kaplan-Meier and Cox analyses were conducted, and the prognostic ability and predictive independence of the lncRNA signature were found in three ESCC datasets. In the entire set, time-dependent ROC curve analysis showed that the prediction accuracy of the lncRNA signature was remarkably greater than that of TNM stage. ROC and stratified analysis indicated that the combination of six-lncRNA signature with the TNM stage has the highest accuracy in subgrouping ESCC patients. Furthermore, experiments subsequently confirmed that one of the lncRNAs LINC01273 may play an oncogenic role in ESCC. This study suggested the six-lncRNA signature could be a valuable survival predictor for patients with ESCC and have potential to be an auxiliary biomarker of TNM stage to subdivide ESCC patients more accurately, which has important clinical significance.

Corrigendum: TGF-ß1 promotes human breast cancer angiogenesis and malignant behavior by regulating endothelial-mesenchymal transition.

[This corrects the article DOI: 10.3389/fonc.2022.1051148.].

Displacement Identification by Computer Vision for Condition Monitoring of Rail Vehicle Bearings.

Bearings of rail vehicles bear various dynamic forces. Any fault of the bearing seriously threatens running safety. For fault diagnosis, vibration and temperature measured from the bogie and acoustic signals measured from trackside are often used. However, installing additional sensing devices on the bogie increases manufacturing cost while trackside monitoring is susceptible to ambient noise. For other application, structural displacement based on computer vision is widely applied for deflection measurement and damage identification of bridges. This article proposes to monitor the health condition of the rail vehicle bearings by detecting the displacement of bolts on the end cap of the bearing box. This study is performed based on an experimental platform of bearing systems. The displacement is monitored by computer vision, which can image real-time displacement of the bolts. The health condition of bearings is reflected by the amplitude of the detected displacement by phase correlation method which is separately studied by simulation. To improve the calculation rate, the computer vision only locally focuses on three bolts rather than the whole image. The displacement amplitudes of the bearing system in the vertical direction are derived by comparing the correlations of the image's gray-level co-occurrence matrix (GLCM). For verification, the measured displacement is checked against the measurement from laser displacement sensors, which shows that the displacement accuracy is 0.05 mm while improving calculation rate by 68%. This study also found that the displacement of the bearing system increases with the increase in rotational speed while decreasing with static load.

A Fault Diagnosis Method of Bogie Axle Box Bearing Based on Spectrum Whitening Demodulation.

The axle box bearing of bogie is one of the key components of the rail transit train, which can ensure the rotary motion of wheelsets and make the wheelsets adapt to the conditions of uneven railways. At the same time, the axle box bearing also exposes most of the load of the car body. Long-time high-speed rotation and heavy load make the axle box bearing prone to failure. If the bearing failure occurs, it will greatly affect the safety of the train. Therefore, it is extremely important to monitor the health status of the axle box bearing. At present, the health status of the axle box bearing is mainly monitored by vibration information and temperature information. Compared with the temperature data, the vibration data can more easily detect the early fault of the bearing, and early warning of the bearing state can avoid the occurrence of serious fault in time. Therefore, this paper is based on the vibration data of the axle box bearing to carry out adaptive fault diagnosis of bearing. First, the AR model predictive filter is used to denoise the vibration signal of the bearing, and then the signal is whitened in the frequency domain. Finally, the characteristic value of vibration data is extracted by energy operator demodulation, and the fault type is determined by comparing with the theoretical value. Through the analysis of the constructed simulation signal data, the characteristic parameters of the data can be effectively extracted. The experimental data collected from the bearing testbed of high-speed train are analyzed and verified, which further proves the effectiveness of the feature extraction method proposed in this paper. Compared with other axle box bearing fault diagnosis methods, the innovation of the proposed method is that the signal is denoised twice by using AR filter and spectrum whitening, and the adaptive extraction of fault features is realized by using energy operator. At the same time, the steps of setting parameters in the process of feature extraction are avoided in other feature extraction methods, which improves the diagnostic efficiency and is conducive to use in online monitoring system.

A Real-Time Fault Early Warning Method for a High-Speed EMU Axle Box Bearing.

An axle box bearing is one of the most important components of high-speed EMUs (electric multiple units), which runs at a very fast speed, suffers a heavy load, and operates under various complex working conditions. Once a bearing fault occurs, it not only has an enormous impact on the railway system, but also poses a threat to personal safety. Therefore, there is significant value in studying a real-time fault early warning of a high-speed EMU axle box bearing. However, to our best knowledge, there are three obvious defects in the existing fault early warning methods used for high-speed EMU axle box bearings: (1) these methods based on vibration are extremely mature, but there are no vibration sensors installed in high-speed EMU axle box because it will greatly increase the manufacturing cost; (2) a TADS (trackside acoustic device system) can effectively detect early failures, but only a portion of railways are equipped with such a facility; and (3) an EMU-ODS (electric multiple unit onboard detection system) has reported numerous untimely warnings, along with warnings of frequent occurrence being missed. Whereupon, a method is proposed to realize the fault early warning of an axle box bearing without installing a vibration sensor on the high-speed EMU in service, namely a MLSTM-iForest (multilayer long short-term memory-isolation forest). First, the time-series data of the temperature-related variables of the axle box bearing is used as the input of MLSTM to predict the axle box bearing temperature in the future. Then, the deviation index of the predicted axle box bearing temperature is calculated. Finally, the deviation index is input into an iForest algorithm for unsupervised classification to realize the fault early warning of an axle box bearing. Experimental results on high-speed EMU operation data sets demonstrated the availability and feasibility of the presented method toward achieving early fault warnings of a high-speed EMU axle box bearing.

Three-Dimensional Structures of Nanoporous NiO/ZnO Nanoarray Films for Enhanced Electrochromic Performance.

An electrochromic device with the as-obtained nanoporous NiO /ZnO nanoarray as a working electrode was constructed and assembled. The nanoporous NiO/ZnO nanoarray film with a three-dimensional structure was prepared on indium tin oxide (ITO) glass substrate through a two-step route that combined chemical bath deposition method with a hydrothermal method. The nanoporous NiO/ZnO nanoarray electrode reveals a noticeable improvement in electrochromism compared with that of nanoporous NiO alone, including higher optical modulation (81 %), higher coloration efficiency (78.5 cm2 C-1 ), faster response times (2.6 and 9.7 s for coloring and bleaching, respectively), and favorable durability performance. Such enhancements are mainly attributed to the three-dimensional structures of nanoporous NiO coated on ZnO nanoarray, namely, 1) the uniform hexagonal ZnO nanoarray loads more nanoporous NiO, 2) nanoporous NiO cross-linked with ZnO nanorods provides a loose interspace morphology, 3) stronger adhesion between ZnO nanorods and ITO covered with ZnO seed, 4) core-shell and cross-linked structures promote electrolyte infiltration, and 5) appropriate band gaps improve charge transfer.

AlloSigMA: allosteric signaling and mutation analysis server.

MOTIVATION: Allostery is an omnipresent mechanism of the function modulation in proteins via either effector binding or mutations in the exosites. Despite the growing number of online servers and databases devoted to prediction/classification of allosteric sites and their characteristics, there is a lack of resources for an efficient and quick estimation of the causality and energetics of allosteric communication. RESULTS: The AlloSigMA server implements a unique approach on the basis of the recently introduced structure-based statistical mechanical models of allosteric signaling. It provides an interactive framework for estimating the allosteric free energy as a result of the ligand(s) binding, mutation(s) and their combinations. Latent regulatory exosites and allosteric effect of mutations can be detected and explored, facilitating the research efforts in protein engineering and allosteric drug design. AVAILABILITY AND IMPLEMENTATION: The AlloSigMA server is freely available at http://allosigma.bii.a-star.edu.sg/home/. CONTACT: igorb@bii.a-star.edu.sg.

Protein function machinery: from basic structural units to modulation of activity.

Contemporary protein structure is a result of the trade off between the laws of physics and the evolutionary selection. The polymer nature of proteins played a decisive role in establishing the basic structural and functional units of soluble proteins. We discuss how these elementary building blocks work in the hierarchy of protein domain structure, co-translational folding, as well as in enzymatic activity and molecular interactions. Next, we consider modulators of the protein function, such as intermolecular interactions, disorder-to-order transitions, and allosteric signaling, acting via interference with the protein's structural dynamics. We also discuss the post-translational modifications, which is a complementary intricate mechanism evolved for regulation of protein functions and interactions. In conclusion, we assess an anticipated contribution of discussed topics to the future advancements in the field.

Basic units of protein structure, folding, and function.

Study of the hierarchy of domain structure with alternative sets of domains and analysis of discontinuous domains, consisting of remote segments of the polypeptide chain, raised a question about the minimal structural unit of the protein domain. The hypothesis on the decisive role of the polypeptide backbone in determining the elementary units of globular proteins have led to the discovery of closed loops. It is reviewed here how closed loops form the loop-n-lock structure of proteins, providing the foundation for stability and designability of protein folds/domain and underlying their co-translational folding. Simplified protein sequences are considered here with the aim to explore the basic principles that presumably dominated the folding and stability of proteins in the early stages of structural evolution. Elementary functional loops (EFLs), closed loops with one or few catalytic residues, are, in turn, units of the protein function. They are apparent descendants of the prebiotic ring-like peptides, which gave rise to the first functional folds/domains being fused in the beginning of the evolution of protein structure. It is also shown how evolutionary relations between protein functional superfamilies and folds delineated with the help of EFLs can contribute to establishing the rules for design of desired enzymatic functions. Generalized descriptors of the elementary functions are proposed to be used as basic units in the future computational design.

Nucleotide binding database NBDB--a collection of sequence motifs with specific protein-ligand interactions.

NBDB database describes protein motifs, elementary functional loops (EFLs) that are involved in binding of nucleotide-containing ligands and other biologically relevant cofactors/coenzymes, including ATP, AMP, ATP, GMP, GDP, GTP, CTP, PAP, PPS, FMN, FAD(H), NAD(H), NADP, cAMP, cGMP, c-di-AMP and c-di-GMP, ThPP, THD, F-420, ACO, CoA, PLP and SAM. The database is freely available online at http://nbdb.bii.a-star.edu.sg. In total, NBDB contains data on 249 motifs that work in interactions with 24 ligands. Sequence profiles of EFL motifs were derived de novo from nonredundant Uniprot proteome sequences. Conserved amino acid residues in the profiles interact specifically with distinct chemical parts of nucleotide-containing ligands, such as nitrogenous bases, phosphate groups, ribose, nicotinamide, and flavin moieties. Each EFL profile in the database is characterized by a pattern of corresponding ligand-protein interactions found in crystallized ligand-protein complexes. NBDB database helps to explore the determinants of nucleotide and cofactor binding in different protein folds and families. NBDB can also detect fragments that match to profiles of particular EFLs in the protein sequence provided by user. Comprehensive information on sequence, structures, and interactions of EFLs with ligands provides a foundation for experimental and computational efforts on design of required protein functions.

A computational method for studying the relation between alternative splicing and DNA methylation.

Alternative splicing is an important mechanism in eukaryotes that expands the transcriptome and proteome significantly. It plays an important role in a number of biological processes. Understanding its regulation is hence an important challenge. Recently, increasing evidence has been collected that supports an involvement of intragenic DNA methylation in the regulation of alternative splicing. The exact mechanisms of regulation, however, are largely unknown, and speculated to be complex: different methylation profiles might exist, each of which could be associated with a different regulation mechanism. We present a computational technique that is able to determine such stable methylation patterns and allows to correlate these patterns with inclusion propensity of exons. Pattern detection is based on dynamic time warping (DTW) of methylation profiles, a sophisticated similarity measure for signals that can be non-trivially transformed. We design a flexible self-organizing map approach to pattern grouping. Exemplary application on available data sets indicates that stable patterns which correlate non-trivially with exon inclusion do indeed exist. To improve the reliability of these predictions, further studies on larger data sets will be required. We have thus taken great care that our software runs efficiently on modern hardware, so that it can support future studies on large-scale data sets.

Efficient and Accurate OTU Clustering with GPU-Based Sequence Alignment and Dynamic Dendrogram Cutting.

De novo clustering is a popular technique to perform taxonomic profiling of a microbial community by grouping 16S rRNA amplicon reads into operational taxonomic units (OTUs). In this work, we introduce a new dendrogram-based OTU clustering pipeline called CRiSPy. The key idea used in CRiSPy to improve clustering accuracy is the application of an anomaly detection technique to obtain a dynamic distance cutoff instead of using the de facto value of 97 percent sequence similarity as in most existing OTU clustering pipelines. This technique works by detecting an abrupt change in the merging heights of a dendrogram. To produce the output dendrograms, CRiSPy employs the OTU hierarchical clustering approach that is computed on a genetic distance matrix derived from an all-against-all read comparison by pairwise sequence alignment. However, most existing dendrogram-based tools have difficulty processing datasets larger than 10,000 unique reads due to high computational complexity. We address this difficulty by developing two efficient algorithms for CRiSPy: a compute-efficient GPU-accelerated parallel algorithm for pairwise distance matrix computation and a memory-efficient hierarchical clustering algorithm. Our experiments on various datasets with distinct attributes show that CRiSPy is able to produce more accurate OTU groupings than most OTU clustering applications.

Organization of the multiaminoacyl-tRNA synthetase complex and the cotranslational protein folding.

Aminoacyl-tRNA synthetases (ARSs) play an essential role in the protein synthesis by catalyzing an attachment of their cognate amino acids to tRNAs. Unlike their prokaryotic counterparts, ARSs in higher eukaryotes form a multiaminoacyl-tRNA synthetase complex (MARS), consisting of the subset of ARS polypeptides and three auxiliary proteins. The intriguing feature of MARS complex is the presence of only nine out of twenty ARSs, specific for Arg, Asp, Gln, Glu, Ile, Leu, Lys, Met, and Pro, regardless of the organism, cell, or tissue types. Although existence of MARSs complex in higher eukaryotes has been already known for more than four decades, its functional significance remains elusive. We found that seven of the nine corresponding amino acids (Arg, Gln, Glu, Ile, Leu, Lys, and Met) together with Ala form a predictor of the protein α-helicity. Remarkably, all amino acids (besides Ala) in the predictor have the highest possible number of side-chain rotamers. Therefore, compositional bias of a typical α-helix can contribute to the helix's stability by increasing the entropy of the folded state. It also appears that position-specific α-helical propensity, specifically periodic alternation of charged and hydrophobic residues in the helices, may well be provided by the structural organization of the complex. Considering characteristics of MARS complex from the perspective of the α-helicity, we hypothesize that specific composition and structure of the complex represents a functional mechanism for coordination of translation with the fast and correct folding of amphiphilic α-helices.

Global DNA hypermethylation in down syndrome placenta.

Down syndrome (DS), commonly caused by an extra copy of chromosome 21 (chr21), occurs in approximately one out of 700 live births. Precisely how an extra chr21 causes over 80 clinically defined phenotypes is not yet clear. Reduced representation bisulfite sequencing (RRBS) analysis at single base resolution revealed DNA hypermethylation in all autosomes in DS samples. We hypothesize that such global hypermethylation may be mediated by down-regulation of TET family genes involved in DNA demethylation, and down-regulation of REST/NRSF involved in transcriptional and epigenetic regulation. Genes located on chr21 were up-regulated by an average of 53% in DS compared to normal villi, while genes with promoter hypermethylation were modestly down-regulated. DNA methylation perturbation was conserved in DS placenta villi and in adult DS peripheral blood leukocytes, and enriched for genes known to be causally associated with DS phenotypes. Our data suggest that global epigenetic changes may occur early in development and contribute to DS phenotypes.

DySC: software for greedy clustering of 16S rRNA reads.

UNLABELLED: Pyrosequencing technologies are frequently used for sequencing the 16S ribosomal RNA marker gene for profiling microbial communities. Clustering of the produced reads is an important but time-consuming task. We present Dynamic Seed-based Clustering (DySC), a new tool based on the greedy clustering approach that uses a dynamic seeding strategy. Evaluations based on the normalized mutual information (NMI) criterion show that DySC produces higher quality clusters than UCLUST and CD-HIT at a comparable runtime. AVAILABILITY AND IMPLEMENTATION: DySC, implemented in C, is available at http://code.google.com/p/dysc/ under GNU GPL license.