Distinct Mechanisms for Induction and Tolerance Regulate the Immediate Early Genes Encoding Interleukin 1β and Tumor Necrosis Factor α

Interleukin-1β and Tumor Necrosis Factor α play related, but distinct, roles in immunity and disease. Our study revealed major mechanistic distinctions in the Toll-like receptor (TLR) signaling-dependent induction for the rapidly expressed genes (IL1B and TNF) coding for these two cytokines. Prior to induction, TNF exhibited pre-bound TATA Binding Protein (TBP) and paused RNA Polymerase II (Pol II), hallmarks of poised immediate-early (IE) genes. In contrast, unstimulated IL1B displayed very low levels of both TBP and paused Pol II, requiring the lineage-specific Spi-1/PU.1 (Spi1) transcription factor as an anchor for induction-dependent interaction with two TLR-activated transcription factors, C/EBPβ and NF-κB. Activation and DNA binding of these two pre-expressed factors resulted in de novo recruitment of TBP and Pol II to IL1B in concert with a permissive state for elongation mediated by the recruitment of elongation factor P-TEFb. This Spi1-dependent mechanism for IL1B transcription, which is unique for a rapidly-induced/poised IE gene, was more dependent upon P-TEFb than was the case for the TNF gene. Furthermore, the dependence on phosphoinositide 3-kinase for P-TEFb recruitment to IL1B paralleled a greater sensitivity to the metabolic state of the cell and a lower sensitivity to the phenomenon of endotoxin tolerance than was evident for TNF. Such differences in induction mechanisms argue against the prevailing paradigm that all IE genes possess paused Pol II and may further delineate the specific roles played by each of these rapidly expressed immune modulators. © 2013 Adamik et al

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.Comment: 49 pages, 2 figures, 2 tables, 10 supplementary figures, 13 supplementary table

Volcano eruption algorithm for solving optimization problems

This is an accepted manuscript of an article published by Springer in Neural Computing and Applications on 30/06/2020, available online at https://doi.org/10.1007/s00521-020-05124-x The accepted version of the publication may differ from the final published version.Meta-heuristic algorithms have been proposed to solve several optimization problems in different research areas due to their unique attractive features. Traditionally, heuristic approaches are designed separately for discrete and continuous problems. This paper leverages the meta-heuristic algorithm for solving NP-hard problems in both continuous and discrete optimization fields, such as nonlinear and multi-level programming problems through extensive simulations of volcano eruption process. In particular, a new optimization solution named Volcano Eruption Algorithm (VEA) proposed in this paper, which is inspired from the nature of volcano eruption. The feasibility and efficiency of the algorithm are evaluated using numerical results obtained through several test problems reported in the state-of-theart literature. Based on the solutions and number of required iterations, we observed that the proposed meta-heuristic algorithm performs remarkably well to solve NP-hard problem. Furthermore, the proposed algorithm is applied to solve some large-size benchmarking LP and Internet of Vehicles (IoV) problems efficiently

Synthesis and Photoluminescence Property of Silicon Carbide Nanowires Via Carbothermic Reduction of Silica

Silicon carbide nanowires have been synthesized at 1400 °C by carbothermic reduction of silica with bamboo carbon under normal atmosphere pressure without metallic catalyst. X-ray diffraction, scanning electron microscopy, energy-dispersive spectroscopy, transmission electron microscopy and Fourier transformed infrared spectroscopy were used to characterize the silicon carbide nanowires. The results show that the silicon carbide nanowires have a core–shell structure and grow along <111> direction. The diameter of silicon carbide nanowires is about 50–200 nm and the length from tens to hundreds of micrometers. The vapor–solid mechanism is proposed to elucidate the growth process. The photoluminescence of the synthesized silicon carbide nanowires shows significant blueshifts, which is resulted from the existence of oxygen defects in amorphous layer and the special rough core–shell interface

Improvement of renal oxidative stress markers after ozone administration in diabetic nephropathy in rats

<p>Abstract</p> <p>Background</p> <p>Several complications of diabetes mellitus (DM) e.g. nephropathy (DN) have been linked to oxidative stress. Ozone, by means of oxidative preconditioning, may exert its protective effects on DN.</p> <p>Aim</p> <p>The aim of the present work is to study the possible role of ozone therapy in ameliorating oxidative stress and inducing renal antioxidant defence in streptozotocin (STZ)-induced diabetic rats.</p> <p>Methods</p> <p>Six groups (n = 10) of male Sprague Dawley rats were used as follows: Group C: Control group. Group O: Ozone group, in which animals received ozone intraperitoneally (i.p.) (1.1 mg/kg). Group D: Diabetic group, in which DM was induced by single i.p. injections of streptozotocin (STZ). Group DI: Similar to group D but animals also received subcutaneous (SC) insulin (0.75 IU/100 gm BW.). Group DO: In which diabetic rats received the same dose of ozone, 48 h after induction of diabetes. Group DIO, in which diabetic rats received the same doses of insulin and ozone, respectively. All animals received daily treatment for six weeks. At the end of the study period (6 weeks), blood pressure, blood glycosylated hemoglobin (HbA_1c), serum creatinine, blood urea nitrogen (BUN), kidney tissue levels of superoxide dismutase (SOD), catalase (CAT), glutathione peroxide (GPx), aldose reductase (AR) activities and malondialdehyde (MDA) concentration were measured.</p> <p>Results</p> <p>Induction of DM in rats significantly elevated blood pressure, HbA_1c, BUN, creatinine and renal tissue levels of MDA and AR while significantly reducing SOD, CAT and GPx activities. Either Insulin or ozone therapy significantly reversed the effects of DM on all parameters; in combination (DIO group), they caused significant improvements in all parameters in comparison to each alone.</p> <p>Conclusions</p> <p>Ozone administration in conjunction with insulin in DM rats reduces oxidative stress markers and improves renal antioxidant enzyme activity which highlights its potential uses in the regimen for treatment of diabetic patients.</p

High-Resolution Phenotypic Profiling Defines Genes Essential for Mycobacterial Growth and Cholesterol Catabolism

The pathways that comprise cellular metabolism are highly interconnected, and alterations in individual enzymes can have far-reaching effects. As a result, global profiling methods that measure gene expression are of limited value in predicting how the loss of an individual function will affect the cell. In this work, we employed a new method of global phenotypic profiling to directly define the genes required for the growth of Mycobacterium tuberculosis. A combination of high-density mutagenesis and deep-sequencing was used to characterize the composition of complex mutant libraries exposed to different conditions. This allowed the unambiguous identification of the genes that are essential for Mtb to grow in vitro, and proved to be a significant improvement over previous approaches. To further explore functions that are required for persistence in the host, we defined the pathways necessary for the utilization of cholesterol, a critical carbon source during infection. Few of the genes we identified had previously been implicated in this adaptation by transcriptional profiling, and only a fraction were encoded in the chromosomal region known to encode sterol catabolic functions. These genes comprise an unexpectedly large percentage of those previously shown to be required for bacterial growth in mouse tissue. Thus, this single nutritional change accounts for a significant fraction of the adaption to the host. This work provides the most comprehensive genetic characterization of a sterol catabolic pathway to date, suggests putative roles for uncharacterized virulence genes, and precisely maps genes encoding potential drug targets

Artificial intelligence in biological activity prediction

Artificial intelligence has become an indispensable resource in chemoinformatics. Numerous machine learning algorithms for activity prediction recently emerged, becoming an indispensable approach to mine chemical information from large compound datasets. These approaches enable the automation of compound discovery to find biologically active molecules with important properties. Here, we present a review of some of the main machine learning studies in biological activity prediction of compounds, in particular for sweetness prediction. We discuss some of the most used compound featurization techniques and the major databases of chemical compounds relevant to these tasks.This study was supported by the European Commission through project SHIKIFACTORY100 - Modular cell factories for the production of 100 compounds from the shikimate pathway (Reference 814408), and by the Portuguese FCT under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020.info:eu-repo/semantics/publishedVersio

Mutation in SUMO E3 ligase, SIZ1, Disrupts the Mature Female Gametophyte in Arabidopsis

Female gametophyte is the multicellular haploid structure that can produce embryo and endosperm after fertilization, which has become an attractive model system for investigating molecular mechanisms in nuclei migration, cell specification, cell-to-cell communication and many other processes. Previous reports found that the small ubiquitin-like modifier (SUMO) E3 ligase, SIZ1, participated in many processes depending on particular target substrates and suppression of salicylic acid (SA) accumulation. Here, we report that SIZ1 mediates the reproductive process. SIZ1 showed enhanced expression in female organs, but was not detected in the anther or pollen. A defect in the siz1-2 maternal source resulted in reduced seed-set regardless of high SA concentration within the plant. Moreover, aniline blue staining and scanning electron microscopy revealed that funicular and micropylar pollen tube guidance was arrested in siz1-2 plants. Some of the embryo sacs of ovules in siz1-2 were also disrupted quickly after stage FG7. There was no significant affects of the siz1-2 mutation on expression of genes involved in female gametophyte development- or pollen tube guidance in ovaries. Together, our results suggest that SIZ1 sustains the stability and normal function of the mature female gametophyte which is necessary for pollen tube guidance

Protective Coupling of Mitochondrial Function and Protein Synthesis via the eIF2α Kinase GCN-2

Cells respond to defects in mitochondrial function by activating signaling pathways that restore homeostasis. The mitochondrial peptide exporter HAF-1 and the bZip transcription factor ATFS-1 represent one stress response pathway that regulates the transcription of mitochondrial chaperone genes during mitochondrial dysfunction. Here, we report that GCN-2, an eIF2α kinase that modulates cytosolic protein synthesis, functions in a complementary pathway to that of HAF-1 and ATFS-1. During mitochondrial dysfunction, GCN-2–dependent eIF2α phosphorylation is required for development as well as the lifespan extension observed in Caenorhabditis elegans. Reactive oxygen species (ROS) generated from dysfunctional mitochondria are required for GCN-2–dependent eIF2α phosphorylation but not ATFS-1 activation. Simultaneous deletion of ATFS-1 and GCN-2 compounds the developmental defects associated with mitochondrial stress, while stressed animals lacking GCN-2 display a greater dependence on ATFS-1 and stronger induction of mitochondrial chaperone genes. These findings are consistent with translational control and stress-dependent chaperone induction acting in complementary arms of the UPRmt