Small-Molecule Allosteric Inhibitors of Human Aspartate Transcarbamoylase Suppress Proliferation of Bone Osteosarcoma Epithelial Cells.

Aspartate transcarbamoylase (ATC) is the first committed step in de novo pyrimidine biosynthesis in eukaryotes and plants. A potent transition state analog of human ATCase (PALA) has previously been assessed in clinical trials for the treatment of cancer, but was ultimately unsuccessful. Additionally, inhibition of this pathway has been proposed to be a target to suppress cell proliferation in E. coli, the malarial parasite and tuberculosis. In this manuscript we screened a 70-member library of ATC inhibitors developed against the malarial and tubercular ATCases for inhibitors of the human ATC. Four compounds showed low nanomolar inhibition (IC50 30-120 nM) in an in vitro activity assay. These compounds significantly outperform PALA, which has a triphasic inhibition response under identical conditions, in which significant activity remains at PALA concentrations above 10 µM. Evidence for a druggable allosteric pocket in human ATC is provided by both in vitro enzyme kinetic, homology modeling and in silico docking. These compounds also suppress the proliferation of U2OS osteoblastoma cells by promoting cell cycle arrest in G0/G1 phase. This report provides the first evidence for an allosteric pocket in human ATC, which greatly enhances its druggability and demonstrates the potential of this series in cancer therapy.

Nunchaku: optimally partitioning data into piece-wise contiguous segments.

MOTIVATION: When analyzing 1D time series, scientists are often interested in identifying regions where one variable depends linearly on the other. Typically, they use an ad hoc and therefore often subjective method to do so. RESULTS: Here, we develop a statistically rigorous, Bayesian approach to infer the optimal partitioning of a dataset not only into contiguous piece-wise linear segments, but also into contiguous segments described by linear combinations of arbitrary basis functions. We therefore present a general solution to the problem of identifying discontinuous change points. Focusing on microbial growth, we use the algorithm to find the range of optical density where this density is linearly proportional to the number of cells and to automatically find the regions of exponential growth for both Escherichia coli and Saccharomyces cerevisiae. For budding yeast, we consequently are able to infer the Monod constant for growth on fructose. Our algorithm lends itself to automation and high throughput studies, increases reproducibility, and should facilitate data analyses for a broad range of scientists. AVAILABILITY AND IMPLEMENTATION: The corresponding Python package, entitled Nunchaku, is available at PyPI: https://pypi.org/project/nunchaku.

nextPYP: a comprehensive and scalable platform for characterizing protein variability in situ using single-particle cryo-electron tomography.

Single-particle cryo-electron tomography is an emerging technique capable of determining the structure of proteins imaged within the native context of cells at molecular resolution. While high-throughput techniques for sample preparation and tilt-series acquisition are beginning to provide sufficient data to allow structural studies of proteins at physiological concentrations, the complex data analysis pipeline and the demanding storage and computational requirements pose major barriers for the development and broader adoption of this technology. Here, we present a scalable, end-to-end framework for single-particle cryo-electron tomography data analysis from on-the-fly pre-processing of tilt series to high-resolution refinement and classification, which allows efficient analysis and visualization of datasets with hundreds of tilt series and hundreds of thousands of particles. We validate our approach using in vitro and cellular datasets, demonstrating its effectiveness at achieving high-resolution and revealing conformational heterogeneity in situ. The framework is made available through an intuitive and easy-to-use computer application, nextPYP ( http://nextpyp.app ).

mRNA expression profile reveals differentially expressed genes in splenocytes of experimental autoimmune encephalomyelitis model.

Experimental autoimmune encephalomyelitis (EAE) is a mouse model that can be used to investigate aetiology, pathogenesis, and treatment approaches for multiple sclerosis (MS). A novel integrated bioinformatics approach was used to understand the involvement of differentially expressed genes (DEGs) in the spleen of EAE mice through data mining of existing microarray and RNA-seq datasets. We screened differentially expressed mRNAs using mRNA expression profile data of EAE spleens taken from Gene Expression Omnibus (GEO). Functional and pathway enrichment analyses of DEGs were performed by Database for Annotation, Visualization, and Integrated Discovery (DAVID). Subsequently, the DEGs-encoded protein-protein interaction (PPI) network was constructed. The 784 DEGs in GSE99300 A.SW PP-EAE mice spleen mRNA profiles, 859 DEGs in GSE151701 EAE mice spleen mRNA profiles, and 646 DEGs in GSE99300 SJL/J PP-EAE mice spleen mRNA profiles were explored. Functional enrichment of 55 common DEGs among 3 sub-datasets revealed several immune-related terms, such as neutrophil extravasation, leucocyte migration, antimicrobial humoral immune response mediated by an antimicrobial peptide, toll-like receptor 4 bindings, IL-17 signalling pathway, and TGF-beta signalling pathway. In the screening of 10 hub genes, including MPO, ELANE, CTSG, LTF, LCN2, SELP, CAMP, S100A9, ITGA2B, and PRTN3, and in choosing and validating the 5 DEGs, including ANK1, MBOAT2, SLC25A21, SLC43A1, and SOX6, the results showed that SLC43A1 and SOX6 were significantly decreased in EAE mice spleen. Thus this study offers a list of genes expressed in the spleen that might play a key role in the pathogenesis of EAE.

Inhibitors of Aspartate Transcarbamoylase Inhibit Mycobacterium tuberculosis Growth.

Aspartate transcarbamoylase (ATCase) plays a key role in the second step of de novo pyrimidine biosynthesis in eukaryotes and has been proposed to be a target to suppress cell proliferation in E. coli, human cells and the malarial parasite. We hypothesized that a library of ATCase inhibitors developed for malarial ATCase (PfATCase) may also contain inhibitors of the tubercular ATCase and provide a similar inhibition of cellular proliferation. Of the 70 compounds screened, 10 showed single-digit micromolar inhibition in an in vitro activity assay and were tested for their effect on M. tuberculosis cell growth in culture. The most promising compound demonstrated a MIC90 of 4 µM. A model of MtbATCase was generated using the experimental coordinates of PfATCase. In silico docking experiments showed this compound can occupy a similar allosteric pocket on MtbATCase to that seen on PfATCase, explaining the observed species selectivity seen for this compound series.

Decreased SIRT1 mRNA expression in peripheral blood mononuclear cells from patients with neuromyelitis optica spectrum disorders.

OBJECTIVE: Sirtuin (SIRT)1, as a molecular link between immunity and metabolic pathways, is a key immune response regulator. The significance of SIRT1 in peripheral blood mononuclear cells (PBMCs) of neuromyelitis optica spectrum disorder (NMOSD) has not been investigated. Here, we aimed to evaluate the SIRT1 mRNA level in PBMCs of patients with NMOSD and its clinical relevance and explore the potential mechanism of SIRT1 action. METHODS: A total of 65 patients with NMOSD and 60 normal controls from North China were enrolled. Using real-time fluorescence quantitative-polymerase chain reaction, mRNA levels were detected in PBMCs, and protein levels were detected using western blotting. RESULTS: Compared to the healthy controls and chronic-phase patients with NMOSD, SIRT1 mRNA and protein levels in PBMCs of NMOSD patients with acute attack were significantly downregulated (p < 0.0001). ∆EDSS scores (EDSS scores in the acute phase-EDSS scores before the recent attack) were higher in NMOSD patients with low SIRT1 mRNA level than in patients with high SIRT1 expression (p = 0.042). SIRT1 mRNA level in patients with acute-phase NMSOD was positively correlated with lymphocyte and monocyte counts and negatively correlated with neutrophil counts and the neutrophil-to-lymphocyte ratio. Furthermore, the transcription factor FOXP3 mRNA level was significantly positively correlated with the SIRT1 mRNA level in PBMCs of patients with acute-phase NMOSD. CONCLUSIONS: Our study indicated that SIRT1 mRNA expression was downregulated in the PBMCs of patients with acute-phase NMOSD, and its level was correlated with the clinical parameters of the patients, suggesting a potential role of SIRT1 in NMOSD.

Machine-learning-accelerated simulations to enable automatic surface reconstruction.

Understanding material surfaces and interfaces is vital in applications such as catalysis or electronics. By combining energies from electronic structure with statistical mechanics, ab initio simulations can, in principle, predict the structure of material surfaces as a function of thermodynamic variables. However, accurate energy simulations are prohibitive when coupled to the vast phase space that must be statistically sampled. Here we present a bi-faceted computational loop to predict surface phase diagrams of multicomponent materials that accelerates both the energy scoring and statistical sampling methods. Fast, scalable and data-efficient machine learning interatomic potentials are trained on high-throughput density-functional-theory calculations through closed-loop active learning. Markov chain Monte Carlo sampling in the semigrand canonical ensemble is enabled by using virtual surface sites. The predicted surfaces for GaN(0001), Si(111) and SrTiO3(001) are in agreement with past work and indicate that the proposed strategy can model complex material surfaces and discover previously unreported surface terminations.

Discovery of Small-Molecule Allosteric Inhibitors of PfATC as Antimalarials.

The discovery and development of new drugs against malaria remain urgent. Aspartate transcarbamoylase (ATC) has been suggested to be a promising target for antimalarial drug development. Here, we describe a series of small-molecule inhibitors of P. falciparum ATC with low nanomolar binding affinities that selectively bind to a previously unreported allosteric pocket, thereby inhibiting ATC activation. We demonstrate that the buried allosteric pocket is located close to the traditional ATC active site and that reported compounds maintain the active site of PfATC in its low substrate affinity/low activity conformation. These compounds inhibit parasite growth in blood stage cultures at single digit micromolar concentrations, whereas limited effects were seen against human normal lymphocytes. To our knowledge, this series represent the first PfATC-specific allosteric inhibitors.

Multicomponent Macrocyclic IL-17a Modifier.

IL-17a is a major inflammation target, with several approved antibodies in clinical use. Small-molecule IL-17a antagonists are an emerging hot topic, with the recent advancement of three compounds into clinical trials. Here, we describe the design, discovery, synthesis, and screening of macrocyclic compounds that bind to IL-17a. We found that all currently described IL-17a modifiers belong to the same pharmacophore model, likely resulting in a similar receptor binding mode on IL-17a. A pipeline of pharmacophore analysis, virtual screening, resynthesis, and protein biophysics resulted in a potent IL-17a macrocyclic modifier.

Novel Highlight in Malarial Drug Discovery: Aspartate Transcarbamoylase.

Malaria remains one of the most prominent and dangerous tropical diseases. While artemisinin and analogs have been used as first-line drugs for the past decades, due to the high mutational rate and rapid adaptation to the environment of the parasite, it remains urgent to develop new antimalarials. The pyrimidine biosynthesis pathway plays an important role in cell growth and proliferation. Unlike human host cells, the malarial parasite lacks a functional pyrimidine salvage pathway, meaning that RNA and DNA synthesis is highly dependent on the de novo synthesis pathway. Thus, direct or indirect blockage of the pyrimidine biosynthesis pathway can be lethal to the parasite. Aspartate transcarbamoylase (ATCase), catalyzes the second step of the pyrimidine biosynthesis pathway, the condensation of L-aspartate and carbamoyl phosphate to form N-carbamoyl aspartate and inorganic phosphate, and has been demonstrated to be a promising target both for anti-malaria and anti-cancer drug development. This is highlighted by the discovery that at least one of the targets of Torin2 - a potent, yet unselective, antimalarial - is the activity of the parasite transcarbamoylase. Additionally, the recent discovery of an allosteric pocket of the human homology raises the intriguing possibility of species selective ATCase inhibitors. We recently exploited the available crystal structures of the malarial aspartate transcarbamoylase to perform a fragment-based screening to identify hits. In this review, we summarize studies on the structure of Plasmodium falciparum ATCase by focusing on an allosteric pocket that supports the catalytic mechanisms.

Lipoic Acid Metabolism as a Potential Chemotherapeutic Target Against Plasmodium falciparum and Staphylococcus aureus.

Lipoic acid (LA) is an organic compound that plays a key role in cellular metabolism. It participates in a posttranslational modification (PTM) named lipoylation, an event that is highly conserved and that occurs in multimeric metabolic enzymes of very distinct microorganisms such as Plasmodium sp. and Staphylococcus aureus, including pyruvate dehydrogenase (PDH) and α-ketoglutarate dehydrogenase (KDH). In this mini review, we revisit the recent literature regarding LA metabolism in Plasmodium sp. and Staphylococcus aureus, by covering the lipoate ligase proteins in both microorganisms, the role of lipoate ligase proteins and insights for possible inhibitors of lipoate ligases.

The effects of low-intensity resistance training with or without blood flow restriction on serum BDNF, VEGF and perception in patients with post-stroke depression.

BACKGROUND: Post-stroke depression (PSD) has a significant effect on patients' quality of life and is often accompanied by a decrease in serum brain-derived neurotrophic factor (BDNF) and vascular endothelial growth factor (VEGF) levels. Although exercise is an effective way to improve the body's endocrine environment, traditional high-intensity resistance exercise is not yet readily accepted. PURPOSE: To compare the acute effects of high and low resistance training with or without blood flow restriction on perception, BDNF, and VEGF levels in patients with PSD. METHOD: A total of 24 patients with PSD participated in 2 40% 1- Repetition Maximum (RM) low-intensity resistance training sessions (the low-intensity resistance training group (LOW group) had no blood flow restriction belt; the low-intensity blood flow restriction group (L-BFR group) was required to wear a 120-160 mmHg pressure cuff at the proximal end of the limb) and 1 80% 1-RM high-intensity resistance training session (HIGH group). Elbow venous blood was collected before and after exercise to test for ratings of perceived exertion (RPE), serum blood lactic acid (BLA), BDNF, and VEGF levels. RESULT AND CONCLUSION: There were no statistical differences between the RPE, BLA, BDNF, and VEGF levels of each group before exercise. After exercise, the RPE, BLA, and BDNF levels of the LOW group increased significantly (P < 0.05); the change in VEGF level of the LOW group was not significantly different from that before exercise (P > 0.05), and the indexes of the L-BFR group and the HIGH group were significant after the increase in exercise (P < 0.05). Analysis between groups showed that the changes in BLA, BDNF, and VEGF levels in the L-BFR group and HIGH group were higher than those in the LOW group, and the statistical difference was significant (P < 0.05); there was no change between the statistical difference of the L-BFR group and HIGH group (P > 0.05). The difference in RPE before and after exercise in the HIGH group was significantly higher than that in the L-BFR group (P < 0.05) and the difference in RPE before and after exercise in the L-BFR group was significantly higher than that in the LOW group (P < 0.05). Blood flow restriction resistance exercise may increase the serum BNDF and VEGF levels of PSD patients by increasing the body's BLA concentration. Although its effect is similar to that of traditional high-intensity resistance exercise, subjective physical strength is lower during blood flow restriction resistance exercise.

Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography.

Tomographic reconstruction of cryopreserved specimens imaged in an electron microscope followed by extraction and averaging of sub-volumes has been successfully used to derive atomic models of macromolecules in their biological environment. Eliminating biochemical isolation steps required by other techniques, this method opens up the cell to in-situ structural studies. However, the need to compensate for errors in targeting introduced during mechanical navigation of the specimen significantly slows down tomographic data collection thus limiting its practical value. Here, we introduce protocols for tilt-series acquisition and processing that accelerate data collection speed by up to an order of magnitude and improve map resolution compared to existing approaches. We achieve this by using beam-image shift to multiply the number of areas imaged at each stage position, by integrating geometrical constraints during imaging to achieve high precision targeting, and by performing per-tilt astigmatic CTF estimation and data-driven exposure weighting to improve final map resolution. We validated our beam image-shift electron cryo-tomography (BISECT) approach by determining the structure of a low molecular weight target (~300 kDa) at 3.6 Å resolution where density for individual side chains is clearly resolved.

MicroRNAs and extracellular vesicles in the gut: new host modulators of the microbiome?

The gut microbiota plays an integral role in human health and its dysbiosis is associated with many chronic diseases. There are still large gaps in understanding the host and environmental factors that directly regulate the gut microbiota, and few effective strategies exist to modulate the microbiota in therapeutic applications. Recent reports suggest that certain microRNAs (miRNAs) released by mammalian cells can regulate bacterial gene expression to influence the microbiome composition and propose extracellular vesicles as one natural mechanism for miRNA transport in the gut. These new findings interface with a burgeoning body of data showing that miRNAs are present in a stable form in extracellular environments and can mediate cell-to-cell communication in mammals. Here, we review the literature on RNA-mediated modulation of the microbiome to bring cross-disciplinary perspective to this new type of interaction and its potential implications in biology and medicine.

Correlation between Charge Transport and Base Excision Repair in the MutY-DNA Glycosylase.

Experimental evidence suggests that DNA-mediated redox signaling between high-potential [Fe4S4] proteins is relevant to DNA replication and repair processes, and protein-mediated charge transfer (CT) between [Fe4S4] clusters and nucleic acids is a fundamental process of the signaling and repair mechanisms. We analyzed the dominant CT pathways in the base excision repair glycosylase MutY using molecular dynamics simulations and hole hopping pathway analysis. We find that the adenine nucleobase of the mismatched A·oxoG DNA base pair facilitates [Fe4S4]-DNA CT prior to adenine excision by MutY. We also find that the R153L mutation in MutY (linked to colorectal adenomatous polyposis) influences the dominant [Fe4S4]-DNA CT pathways and appreciably decreases their effective CT rates.

[Inversion of Water Quality Parameters Based on UAV Multispectral Images and the OPT-MPP Algorithm].

Unmanned aerial vehicle (UAV) multispectral remote sensing can be used to monitor multiple water quality parameters, such as suspended solids, turbidity, total phosphorus, and chlorophyll. Establishing a stable and accurate water quality parameter inversion model is a prerequisite for this work. The matching pixel-by-pixel (MPP) algorithm is an inversion algorithm for high resolution features of UAV images; however, it is associated with problems of excessive computation and over-fitting. To overcome these problems, the optimize-MPP (OPT-MPP) algorithm is proposed. In this study, Qingshan Lake in Hangzhou City, Zhejiang Province, was used as the research area. Forty-five samples were collected to construct the OPT-MPP algorithm inversion model for two water quality parameters:the suspended sediments concentration (SS) and turbidity (TU). The results showed that the optimal suspended sediment concentration inversion model had a determination coefficient (R2) of 0.7870 and a comprehensive error of 0.1308. The optimal turbidity inversion model had a R2 of 0.8043 and a comprehensive error of 0.1503. Hence, the inversion of the spatial distribution information for water quality parameters in each experimental area of QingShan Lake was realized by using the optimal models of the two established parameters.

sB7H3 in Children with Acute Appendicitis: Its Diagnostic Value and Association with Histological Findings.

BACKGROUND: Several efforts have been made to find out a valuable marker to assist the diagnosis and differentiation of gangrenous/perforated appendicitis. We aimed to determine the diagnostic capacity of soluble B7H3 (sB7H3) in acute appendicitis (AA) and its accuracy as a predictor of the severity of appendicitis. METHODS: 182 children were allocated into four groups as follows: control group (CG, 90), simple appendicitis (SA, 12), purulent appendicitis (PA, 49), and gangrenous appendicitis (GA, 31). Prior to appendectomy, blood was collected and sent for analysis of routine examination and cytokines (sB7H3 and TNF-α). We compared values of all measured parameters according to histological findings. Furthermore, we assigned AA patients into the nonperforated appendicitis group and the perforated appendicitis group. The diagnostic effects of significant markers were assessed by ROC curves. RESULTS: Only the levels of CRP, FIB, and sB7H3 had a remarkable rising trend in AA-based groups, while differences in the levels of CRP and FIB between simple appendicitis and purulent appendicitis were not statistically significant. In addition, sB7H3 was found as the only marker in children with AA, which was markedly associated with the degree of histological findings of the appendix. Furthermore, sB7H3 had a high diagnostic value in predicting AA and complex appendicitis (PA+GA) in children. However, the diagnostic performance of sB7H3 for distinguishing PA from GA was not remarkable. Additionally, only the levels of CRP and sB7H3 were statistically different between the nonperforated appendicitis group and the perforated appendicitis group. The diagnostic performance of CRP and sB7H3 could not merely predict perforation of AA in children; however, the diagnostic performance was improved after combination. CONCLUSIONS: sB7H3 could be used as a valuable marker to predict the presence of AA and complex AA in children. However, the diagnostic value of sB7H3 to predict gangrenous/perforated appendicitis was not found to be remarkable. The combination of sB7H3 and CRP might improve the prediction of perforated appendicitis.

Prevention and Control of Pathogens Based on Big-Data Mining and Visualization Analysis.

Morbidity and mortality caused by infectious diseases rank first among all human illnesses. Many pathogenic mechanisms remain unclear, while misuse of antibiotics has led to the emergence of drug-resistant strains. Infectious diseases spread rapidly and pathogens mutate quickly, posing new threats to human health. However, with the increasing use of high-throughput screening of pathogen genomes, research based on big data mining and visualization analysis has gradually become a hot topic for studies of infectious disease prevention and control. In this paper, the framework was performed on four infectious pathogens (Fusobacterium, Streptococcus, Neisseria, and Streptococcus salivarius) through five functions: 1) genome annotation, 2) phylogeny analysis based on core genome, 3) analysis of structure differences between genomes, 4) prediction of virulence genes/factors with their pathogenic mechanisms, and 5) prediction of resistance genes/factors with their signaling pathways. The experiments were carried out from three angles: phylogeny (macro perspective), structure differences of genomes (micro perspective), and virulence and drug-resistance characteristics (prediction perspective). Therefore, the framework can not only provide evidence to support the rapid identification of new or unknown pathogens and thus plays a role in the prevention and control of infectious diseases, but also help to recommend the most appropriate strains for clinical and scientific research. This paper presented a new genome information visualization analysis process framework based on big data mining technology with the accommodation of the depth and breadth of pathogens in molecular level research.

Metabolic Labeling of Peptidoglycan with NIR-II Dye Enables In Vivo Imaging of Gut Microbiota.

Deepening our understanding of mammalian gut microbiota has been greatly hampered by the lack of a facile, real-time, and in vivo bacterial imaging method. To address this unmet need in microbial visualization, we herein report the development of a second near-infrared (NIR-II)-based method for in vivo imaging of gut bacteria. Using d-propargylglycine in gavage and then click reaction with an azide-containing NIR-II dye, gut microbiota of a donor mouse was strongly labeled with NIR-II fluorescence on their peptidoglycan. The bacteria could be readily visualized in recipient mouse gut with high spatial resolution and deep tissue penetration under NIR irradiation. The NIR-II-based metabolic labeling strategy reported herein, provides, to the best of our knowledge, the first protocol for facile in vivo visualization of gut microbiota within deep tissues, and offers an instrumental tool for deciphering the complex biology of these gut "dark matters".

[Value of three scoring systems in evaluating the prognosis of children with severe sepsis].

OBJECTIVE: To study the predictive value of Pediatric Age-adapted Sequential Organ Failure Assessment Score (pSOFA), Pediatric Risk of Mortality Score III (PRISM III), and Pediatric Critical Illness Score (PCIS) in children with severe sepsis. METHODS: A retrospective analysis was performed for the clinical data of 193 hospitalized children with severe sepsis. According to the final outcome, these children were divided into a survival group with 151 children and a death group with 42 children. The scores of pSOFA, PRISM III, and PCIS were determined according to the worst values of each index within 24 hours after admission. The receiver operating characteristic (ROC) curve was used to analyze the efficiency of each scoring system in predicting the risk of death due to sepsis. Smooth curve fitting was used to analyze the correlation between the three scoring systems and the threshold effect of each scoring system. Decision curve analysis (DCA) was used to evaluate the application value of each scoring system. RESULTS: The ROC analysis showed that PCIS and pSOFA had a similar predictive value (P=0.182) and that PRISM III and pSOFA had a similar predictive value (P=0.210), while PRISM III had a better predictive value than PCIS (P=0.045). PRISM III had the highest degree of fitting with prognosis, followed by pSOFA and PCIS. The DCA analysis showed that when the risk of death was 0.4 and 0.6 in children with severe sepsis and the three scoring systems were used as the basis for emergency intervention decision-making, pSOFA achieved the highest standardized net benefit, followed by PRISM III and PCIS. CONCLUSIONS: All three scoring systems have a certain value in predicting the prognosis of children with severe sepsis, and pSOFA has a better value than PRISM III and PCIS.