Network Topologies and Dynamics Leading to Endotoxin Tolerance and Priming in Innate Immune Cells

The innate immune system, acting as the first line of host defense, senses and adapts to foreign challenges through complex intracellular and intercellular signaling networks. Endotoxin tolerance and priming elicited by macrophages are classic examples of the complex adaptation of innate immune cells. Upon repetitive exposures to different doses of bacterial endotoxin (lipopolysaccharide) or other stimulants, macrophages show either suppressed or augmented inflammatory responses compared to a single exposure to the stimulant. Endotoxin tolerance and priming are critically involved in both immune homeostasis and the pathogenesis of diverse inflammatory diseases. However, the underlying molecular mechanisms are not well understood. By means of a computational search through the parameter space of a coarse-grained three-node network with a two-stage Metropolis sampling approach, we enumerated all the network topologies that can generate priming or tolerance. We discovered three major mechanisms for priming (pathway synergy, suppressor deactivation, activator induction) and one for tolerance (inhibitor persistence). These results not only explain existing experimental observations, but also reveal intriguing test scenarios for future experimental studies to clarify mechanisms of endotoxin priming and tolerance.Comment: 15 pages, 8 figures, submitte

Point Fields of Last Passage Percolation and Coalescing Fractional Brownian Motions

We consider large-scale point fields which naturally appear in the context of the Kardar-Parisi-Zhang (KPZ) phenomenon. Such point fields are geometrical objects formed by points of mass concentration, and by shocks separating the sources of these points. We introduce similarly defined point fields for processes of coalescing fractional Brownian motions (cfBm). The case of the Hurst index 2/3 is of particular interest for us since, in this case, the power law of the density decay is the same as that in the KPZ phenomenon. In this paper, we present strong numerical evidence that statistical properties of points fields in these two different settings are very similar. We also discuss theoretical arguments in support of the conjecture that they are exactly the same in the large-time limit. This would indicate that two objects may, in fact, belong to the same universality class

Screening and bioinformatics analysis of a ceRNA network based on the circular RNAs, miRNAs, and mRNAs in pan‐cancer

Abstract Background The pan‐cancer analysis has recently brought us into a novel level of cancer research. Nowadays, the Circular RNAs (circRNAs) is becoming increasingly important in the occurrence and progression of tumors. Nevertheless, the specific expression patterns and functions of circRNAs in the pan‐cancer remains unclear. Here we aimed to explore the expression patterns and functions of circRNAs in pan‐cancer. Methods We combined our microarray with seven circRNA arrays from the Gene Expression Omnibus (GEO) database and transcriptome profiles were acquired from The Cancer Genome Atlas (TCGA) database. A circRNA‐miRNA‐mRNA network was created and analyzed using multiple bioinformatic approaches including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, Search Tool for the Retrieval of Interacting Genes (STRING) database, cytoHubba and MCODE app. Cell function assays including CCK‐8 analysis, colony formation, and transwell assay were used to explore pan‐circRNAs’ functions. Results A panel of 6 circRNAs, 11 miRNAs, and 318 mRNAs was found to be differentially expressed (DE) in pan‐cancer. A circRNA‐miRNA‐mRNA network was also constructed. Then, a circRNA‐miRNA‐hub gene network was created according to 5 pan‐circRNAs, 8 pan‐miRNAs, and 16 pan‐mRNAs. Enrichment analysis pointed out the possible association of DEmRNAs with pan‐cancer is transcriptional misregulation in cancer. Overexpression of hsa_circ_0004639 and silence of hsa_circ_0008310 can inhibit the malignant biological properties of cancer cells. Conclusions Six pan‐circRNAs were discovered and their regulating mechanisms were predicted. Those findings together will give a new insight into pan‐cancer research and present potential therapy targeting as well as promising biomarkers

The Study of a Novel Paeoniflorin-Converting Enzyme from Cunninghamella blakesleeana

Paeoniflorin is a glycoside compound found in Paeonia lactiflora Pall that is used in traditional herbal medicine and shows various protective effects on the cardio-cerebral vascular system. It has been reported that the pharmacological effects of paeoniflorin might be generated by its metabolites. However, the bioavailability of paeoniflorin by oral administration is low, which greatly limits its clinical application. In this paper, a paeoniflorin-converting enzyme gene (G6046, GenBank accession numbers: OP856858) from Cunninghamella blakesleeana (AS 3.970) was identified by comparative analysis between MS analysis and transcriptomics. The expression, purification, enzyme activity, and structure of the conversion products produced by this paeoniflorin-converting enzyme were studied. The optimal conditions for the enzymatic activity were found to be pH 9, 45 °C, resulting in a specific enzyme activity of 14.56 U/mg. The products were separated and purified by high-performance counter-current chromatography (HPCCC). Two main components were isolated and identified, 2-amino-2-p-hydroxymethyl-methyl alcohol-benzoate (tirs-benzoate) and 1-benzoyloxy-2,3-propanediol (1-benzoyloxypropane-2,3-diol), via UPLC-Q-TOF-MS and NMR. Additionally, paeoniflorin demonstrated the ability to metabolize into benzoic acid via G6046 enzyme, which might exert antidepressant effects through the blood–brain barrier into the brain

The Study of a Novel Paeoniflorin-Converting Enzyme from <i>Cunninghamella blakesleeana</i>

Paeoniflorin is a glycoside compound found in Paeonia lactiflora Pall that is used in traditional herbal medicine and shows various protective effects on the cardio-cerebral vascular system. It has been reported that the pharmacological effects of paeoniflorin might be generated by its metabolites. However, the bioavailability of paeoniflorin by oral administration is low, which greatly limits its clinical application. In this paper, a paeoniflorin-converting enzyme gene (G6046, GenBank accession numbers: OP856858) from Cunninghamella blakesleeana (AS 3.970) was identified by comparative analysis between MS analysis and transcriptomics. The expression, purification, enzyme activity, and structure of the conversion products produced by this paeoniflorin-converting enzyme were studied. The optimal conditions for the enzymatic activity were found to be pH 9, 45 °C, resulting in a specific enzyme activity of 14.56 U/mg. The products were separated and purified by high-performance counter-current chromatography (HPCCC). Two main components were isolated and identified, 2-amino-2-p-hydroxymethyl-methyl alcohol-benzoate (tirs-benzoate) and 1-benzoyloxy-2,3-propanediol (1-benzoyloxypropane-2,3-diol), via UPLC-Q-TOF-MS and NMR. Additionally, paeoniflorin demonstrated the ability to metabolize into benzoic acid via G6046 enzyme, which might exert antidepressant effects through the blood–brain barrier into the brain

Simultaneous removal of organic micropollutants and metals from water by a multifunctional β-cyclodextrin polymer-supported-polyaniline composite

The occurrence of diverse pollutants in water resources across the globe, including organic micropollutants and heavy metals, has challenged the efficacy of many existing water treatment processes. Various materials and media have been developed for removal of these compounds, but few have the capacity to remove multiple contaminants which are typically present in real water sources. Here we report on a novel sorbent (PANI@PCDP) for the simultaneous removal of organic micropollutants and heavy metals during a single process. Cr(VI) and bisphenol A (BPA) were selected as target pollutants due to their frequent occurrence in aquatic environments and the significant health risks they pose. PANI@PCDP exhibited a high level of performance for removal of BPA and total Cr at pH 6 for initial concentrations of 0.5–100 mg/L for Cr(VI) and 0.228–22.8 mg/L for BPA. Up to 98 % Cr was removed at pH 6 through the adsorption and reduction of Cr(VI), followed by the sequestration of the generated Cr(III). In addition, BPA could be captured by PANI@PCDP at an adsorption rate of 1.4 × 10-1 g mg−1 min−1 as a result of the fast formation of complexes with the media. When the PANI@PCDP media was tested on a wider variety of emerging organic micropollutants (including chlorinated aromatic compounds, simple aromatics, and pharmaceuticals) good removal was observed. Such performance benefits arise from the integration of porous β-cyclodextrin polymers with polyaniline, which provides the PANI@PCDP with multiple binding sites for contaminant removal. In addition, the PANI@PCDP can be regenerated at least five times without loss in performance using a facile procedure, providing evidence for its practical application in water treatment

Details of the three priming mechanisms.

<p>(A) Backbone motifs (topological features shared by most of the good parameter sets) of each priming mechanism (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002526#pcbi.1002526.s003" target="_blank">Figure S3</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002526#pcbi.1002526.s012" target="_blank">Text S1</a> for details). The width of a line is proportional to the mean value of the corresponding <i>ω_ji</i> among data sets under each priming mechanism. The “slow” and “fast” time scales reflect the values of γ<i>_j</i> in comparison to γ₃ = 1. (B–D) Typical time courses and corresponding phase space trajectories with or without LD pretreatment. Bistable results for AI and SD are shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002526#pcbi.1002526.s005" target="_blank">Figure S5</a>.</p

Example regulatory networks supporting the priming mechanisms.

<p>(A) The AI mechanism is consistent with observed intra- and inter-cellular molecular mechanisms for LPS priming, based on counterbalanced IL-10 and IL-12 signaling <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002526#pcbi.1002526-Shnyra1" target="_blank">[19]</a>. (B) The PS mechanism inspires this predicted intracellular molecular mechanism based on the selective activation of C/EBPδ by LD LPS. (C) IFN-γ self-priming and cross-priming to LPS follows the AI and PS mechanisms. Network details are retrieved from the database IPA (@Ingenuity) as well as the experimental literature listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002526#pcbi.1002526.s011" target="_blank">Table S3</a>. Dashed lines refer to indirect regulations involving autocrine signaling loops.</p