Natural products modulate NLRP3 in ulcerative colitis.

Ulcerative colitis (UC) is a clinically common, progressive, devastating, chronic inflammatory disease of the intestine that is recurrent and difficult to treat. Nod-like receptor protein 3 (NLRP3) is a protein complex composed of multiple proteins whose formation activates cysteine aspartate protease-1 (caspase-1) to induce the maturation and secretion of inflammatory mediators such as interleukin (IL)-1ß and IL-18, promoting the development of inflammatory responses. Recent studies have shown that NLRP3 is associated with UC susceptibility, and that it maintains a stable intestinal environment by responding to a wide range of pathogenic microorganisms. The mainstay of treatment for UC is to control inflammation and relieve symptoms. Despite a certain curative effect, there are problems such as easy recurrence after drug withdrawal and many side effects associated with long-term medication. NLRP3 serves as a core link in the inflammatory response. If the relationship between NLRP3 and gut microbes and inflammation-associated factors can be analyzed concerning its related inflammatory signaling pathways, its expression status as well as specific mechanism in the course of IBD can be elucidated and further considered for clinical diagnosis and treatment of IBD, it is expected that the development of lead compounds targeting the NLRP3 inflammasome can be developed for the treatment of IBD. Research into the prevention and treatment of UC, which has become a hotbed of research in recent years, has shown that natural products are rich in therapeutic means, and multi-targets, with fewer adverse effects. Natural products have shown promise in treating UC in numerous basic and clinical trials over the past few years. This paper describes the regulatory role of the NLRP3 inflammasome in UC and the mechanism of recent natural products targeting NLRP3 against UC, which provides a reference for the clinical treatment of this disease.

The gut microbes in inflammatory bowel disease: Future novel target option for pharmacotherapy.

Gut microbes constitute the main microbiota in the human body, which can regulate biological processes such as immunity, cell proliferation, and differentiation, hence playing a specific function in intestinal diseases. In recent years, gut microbes have become a research hotspot in the pharmaceutical field. Because of their enormous number, diversity, and functional complexity, gut microbes have essential functions in the development of many digestive diseases. Inflammatory bowel disease (IBD) is a chronic non-specific inflammatory disease with a complex etiology, the exact cause and pathogenesis are unclear. There are no medicines that can cure IBD, and more research on therapeutic drugs is urgently needed. It has been reported that gut microbes play a critical role in pathogenesis, and there is a tight and complex association between gut microbes and IBD. The dysregulation of gut microbes may be a predisposing factor for IBD, and at the same time, IBD may exacerbate gut microbes' disorders, but the mechanism of interaction between the two is still not well defined. The study of the relationship between gut microbes and IBD is not only important to elucidate the pathogenesis but also has a positive effect on the treatment based on the regimen of regulating gut microbes. This review describes the latest research progress on the functions of gut microbes and their relationship with IBD, which can provide reference and assistance for further research. It may provide a theoretical basis for the application of probiotics, fecal microbiota transplantation, and other therapeutic methods to regulate gut microbes in IBD.

Study of an Ultrasensitive Label-Free Electrochemiluminescent Immunosensor Fabricated with a Composite Electrode for Detecting the Glutamate Decarboxylase Antibody.

Antibody testing for the glutamic acid decarboxylase 65 antibody (GADA) is widely used as a golden standard for autoimmune diabetes diagnosis, while current methods for antibody testing are not sensitive enough for clinical usage. Here, a label-free electrochemiluminescent (ECL) immunosensor for detecting GADA in autoimmune diabetes is fabricated and investigated. In the designed immunosensor, a composite film including the multiwalled carbon nanotubes (MWCNTs), zinc oxide (ZnO), and Au nanoparticles (AuNPs) was prepared through nanofabrication processes to improve the performance of sensor. The MWCNTs, which can provide a larger specific surface area, ZnO as a good photocatalytic material, and AuNPs that can enhance the ECL signal of luminol and immobilize the GAD65 antigen were applied to prefunctionalize indium tin oxide (ITO) glass based on a nanofabrication process. The GADA concentration was detected using the ECL immunosensor after incubating with GAD65 antigen-coated prefunctionalized ITO glass. After a direct immunoreaction, it is found that the degree of decreased ECL intensity has a good linear regression toward the logarithm of the GADA concentration in the range of 0.01 to 50 ng mL-1 with a detection limit down to 10 pg mL-1. Human serum samples positive or negative for GADA all nicely fell in the expected area. The fabricated immunosensor with excellent sensitivity, specificity, and stability has potential capability for clinical usage in GADA detection.

GmSYP24, a putative syntaxin gene, confers osmotic/drought, salt stress tolerances and ABA signal pathway.

As major environment factors, drought or high salinity affect crop growth, development and yield. Transgenic approach is an effective way to improve abiotic stress tolerance of crops. In this study, we comparatively analyzed gene structures, genome location, and the evolution of syntaxin proteins containing late embryogenesis abundant (LEA2) domain. GmSYP24 was identified as a dehydration-responsive gene. Our study showed that the GmSYP24 protein was located on the cell membrane. The overexpression of GmSYP24 (GmSYP24ox) in soybean and heteroexpression of GmSYP24 (GmSYP24hx) in Arabidopsis exhibited insensitivity to osmotic/drought and high salinity. However, wild type soybean, Arabidopsis, and the mutant of GmSYP24 homologous gene of Arabidopsis were sensitive to the stresses. Under the abiotic stresses, transgenic soybean plants had greater water content and higher activities of POD, SOD compared with non-transgenic controls. And the leaf stomatal density and opening were reduced in transgenic Arabidopsis. The sensitivity to ABA was decreased during seed germination of GmSYP24ox and GmSYP24hx. GmSYP24hx induced up-regulation of ABA-responsive genes. GmSYP24ox alters the expression of some aquaporins under osmotic/drought, salt, or ABA treatment. These results demonstrated that GmSYP24 played an important role in osmotic/drought or salt tolerance in ABA signal pathway.

Differential Coexpression Network Analysis for Gene Expression Data.

Gene expression profiling by microarray has been used to uncover molecular variations in many areas. The traditional analysis method to gene expression profiling just focuses on the individual genes, and the interactions among genes are ignored, while genes play their roles not by isolations but by interactions with each other. Consequently, gene-to-gene coexpression analysis emerged as a powerful approach to solve the above problems. Then complementary to the conventional differential expression analysis, the differential coexpression analysis can identify gene markers from the systematic level. There are three aspects for differential coexpression network analysis including the network global topological comparison, differential coexpression module identification, and differential coexpression genes and gene pairs identification. To date, the coexpression network and differential coexpression analysis are widely used in a variety of areas in response to environmental stresses, genetic differences, or disease changes. In this chapter, we reviewed the existing methods for differential coexpression network analysis and discussed the applications to cancer research.

Identification of Transcriptional Modules and Key Genes in Chickens Infected with Salmonella enterica Serovar Pullorum Using Integrated Coexpression Analyses.

Salmonella enterica Pullorum is one of the leading causes of mortality in poultry. Understanding the molecular response in chickens in response to the infection by S. enterica is important in revealing the mechanisms of pathogenesis and disease progress. There have been studies on identifying genes associated with Salmonella infection by differential expression analysis, but the relationships among regulated genes have not been investigated. In this study, we employed weighted gene coexpression network analysis (WGCNA) and differential coexpression analysis (DCEA) to identify coexpression modules by exploring microarray data derived from chicken splenic tissues in response to the S. enterica infection. A total of 19 modules from 13,538 genes were associated with the Jak-STAT signaling pathway, the extracellular matrix, cytoskeleton organization, the regulation of the actin cytoskeleton, G-protein coupled receptor activity, Toll-like receptor signaling pathways, and immune system processes; among them, 14 differentially coexpressed modules (DCMs) and 2,856 differentially coexpressed genes (DCGs) were identified. The global expression of module genes between infected and uninfected chickens showed slight differences but considerable changes for global coexpression. Furthermore, DCGs were consistently linked to the hubs of the modules. These results will help prioritize candidate genes for future studies of Salmonella infection.

Electrochemistry-mass spectrometry for mechanism study of oxygen reduction at water/oil interface.

Electrochemistry methods have been widely employed in the development of renewable energy, and involved in various processes, e.g. water splitting and oxygen reduction. Remarkable progress notwithstanding, there are still many challenges in further optimization of catalysts to achieve high performance. For this purpose, an in-depth understanding of reaction mechanism is needed. In this study, an electrochemistry-mass spectrometry method based on a Y-shaped dual-channel microchip as electrochemical cell and ionization device was demonstrated. Combined solutions of aqueous phase and oil phase were introduced into mass spectrometer directly when electrochemical reactions were happening to study the reduction of oxygen by decamethylferrocene or tetrathiafulvalene under the catalysis of a metal-free porphyrin, tetraphenylporphyrin, at water/1,2-dichloroethane interfaces. Monoprotonated and diprotonated tetraphenylporphyrin were detected by mass spectrometer, confirming the previously proposed mechanism of the oxygen reduction reaction. This work offers a new approach to study electrochemical reactions at liquid-liquid interface.

A 41-gene signature derived from breast cancer stem cells as a predictor of survival.

PURPOSE: The aim of this study was to evaluate the ability of a 41-gene signature derived from breast cancer stem cells (BCSCs) to estimate the risk of metastasis and survival in breast cancer patients. METHODS: The centroid expression of the 41-gene signature derived from BCSCs was applied as the threshold to classify patients into two separate groups--patients with high expression (high-EL) of the prognostic signature and patients with low expression (low-EL). The predictive ability of the 41-gene signature was evaluated by Cox regression model and was compared against other popular tests, such as Oncotype and MammaPrint. RESULTS: Our results showed that the 41-gene prognostic signature was significantly associated with age (P = .0351) and ER status (P = .0095). The analysis indicated that patients in the high-EL group had a worse prognosis than those in the low-EL group in terms of both overall survival (OS: HR, 2.05, P = .009) and distant metastasis-free survival (DMFS: HR, 2.24, P = .002). Additionally, the 41-gene signature was an independent risk factor and separates patients based on estrogen receptor status. While comparable to Oncotype, the analysis demonstrated that the 41-gene signature had a better prognostic value in predicting DMFS and OS than AOL, NPI, St. Gallen, Veridex, and MammaPrint. CONCLUSIONS: This study confirms the utility of the 41-gene signature and adds to the growing evidence that gene expression signatures of BCSCs have clinical potential to predict patient outcome and aid in treatment choice.

DCGL v2.0: an R package for unveiling differential regulation from differential co-expression.

MOTIVATION: Differential co-expression analysis (DCEA) has emerged in recent years as a novel, systematic investigation into gene expression data. While most DCEA studies or tools focus on the co-expression relationships among genes, some are developing a potentially more promising research domain, differential regulation analysis (DRA). In our previously proposed R package DCGL v1.0, we provided functions to facilitate basic differential co-expression analyses; however, the output from DCGL v1.0 could not be translated into differential regulation mechanisms in a straightforward manner. RESULTS: To advance from DCEA to DRA, we upgraded the DCGL package from v1.0 to v2.0. A new module named "Differential Regulation Analysis" (DRA) was designed, which consists of three major functions: DRsort, DRplot, and DRrank. DRsort selects differentially regulated genes (DRGs) and differentially regulated links (DRLs) according to the transcription factor (TF)-to-target information. DRrank prioritizes the TFs in terms of their potential relevance to the phenotype of interest. DRplot graphically visualizes differentially co-expressed links (DCLs) and/or TF-to-target links in a network context. In addition to these new modules, we streamlined the codes from v1.0. The evaluation results proved that our differential regulation analysis is able to capture the regulators relevant to the biological subject. CONCLUSIONS: With ample functions to facilitate differential regulation analysis, DCGL v2.0 was upgraded from a DCEA tool to a DRA tool, which may unveil the underlying differential regulation from the observed differential co-expression. DCGL v2.0 can be applied to a wide range of gene expression data in order to systematically identify novel regulators that have not yet been documented as critical. AVAILABILITY: DCGL v2.0 package is available at http://cran.r-project.org/web/packages/DCGL/index.html or at our project home page http://lifecenter.sgst.cn/main/en/dcgl.jsp.

Systems perspectives on erythromycin biosynthesis by comparative genomic and transcriptomic analyses of S. erythraea E3 and NRRL23338 strains.

BACKGROUND: S. erythraea is a Gram-positive filamentous bacterium used for the industrial-scale production of erythromycin A which is of high clinical importance. In this work, we sequenced the whole genome of a high-producing strain (E3) obtained by random mutagenesis and screening from the wild-type strain NRRL23338, and examined time-series expression profiles of both E3 and NRRL23338. Based on the genomic data and transcriptpmic data of these two strains, we carried out comparative analysis of high-producing strain and wild-type strain at both the genomic level and the transcriptomic level. RESULTS: We observed a large number of genetic variants including 60 insertions, 46 deletions and 584 single nucleotide variations (SNV) in E3 in comparison with NRRL23338, and the analysis of time series transcriptomic data indicated that the genes involved in erythromycin biosynthesis and feeder pathways were significantly up-regulated during the 60 hours time-course. According to our data, BldD, a previously identified ery cluster regulator, did not show any positive correlations with the expression of ery cluster, suggesting the existence of alternative regulation mechanisms of erythromycin synthesis in S. erythraea. Several potential regulators were then proposed by integration analysis of genomic and transcriptomic data. CONCLUSION: This is a demonstration of the functional comparative genomics between an industrial S. erythraea strain and the wild-type strain. These findings help to understand the global regulation mechanisms of erythromycin biosynthesis in S. erythraea, providing useful clues for genetic and metabolic engineering in the future.

A new thermostable ß-glucosidase mined from Dictyoglomus thermophilum: properties and performance in octyl glucoside synthesis at high temperatures.

A new ß-glucosidase (DtGH) representing 40% identity with an apple seed glycosidase (ASG) was cloned from Dictyoglomus thermophilum. DtGH showed extremely high thermostability in aqueous solution, with half-lives of 533, 44, and 5 h measured at 70, 80 and 90 °C, respectively. Therefore it was used for direct glycosylation of n-octanol at 70 °C instead of 50 °C as usually. As a result, the glucose based conversion was increased by 27%, but the time spent to reach equilibrium was decreased from 7 d to 3 d. This enzyme also exhibited excellent stability under the reaction environment, retaining 70-80% of its initial activity after 7 d of incubation at 70 °C in either 1.7 M glucose solution or octanol-aqueous (85:15, v/v) system. It could retain part of synthetic activity even in boiling water. Owing to the strong glucose-tolerance and extremely high thermostability, DtGH should be promising for various glucosides synthesis.

Link-based quantitative methods to identify differentially coexpressed genes and gene pairs.

BACKGROUND: Differential coexpression analysis (DCEA) is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. RESULTS: We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links). Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D) expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. CONCLUSIONS: This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

Periodic mesoporous organosilicas with controlled pore symmetries for peptides enrichment.

Periodic mesoporous organosilicas (PMOs) with controlled structures have been synthesized by using cetyltrimethylammonium bromide (CTAB) and sodium perfluorooctanoate (PFONa) as co-templates, 1,2-bis (triethoxysilyl)ethane (BTEE) as an organosilica precursor. By increasing the weight ratio of PFONa/CTAB, a structure transformation from a cubic (Pm-3n) to a two-dimensional hexagonal (p6m) mesostructure and then to multilamellar vesicles can be observed. The cubic and hexagonal samples have similar particle size (200-750 nm), pore size (2.6 and 2.8 nm, respectively), total pore volume (approximately 0.7 cm3/g), and surface area (approximately 900 m2/g), providing ideal candidates to study the peptide enrichment performance influenced simply by pore symmetries. Matrix-assisted laser desorption ionization time-of-flight mass spectroscopy (MALDI-TOF MS) analysis indicates that PMO with a cubic (Pm-3n) structure is more effective in small molecular weight peptides enrichment compared with PMO with a hexagonal structure, showing the importance of mesostructural control for targeted applications. The phenomena can be attributed to the cage-type structure of the Pm-3n symmetry, which possesses cages with a relatively larger pore size and connectivity with a relatively smaller size. It is suggested that the pore entrances with small size are responsible for entrapping small molecular weight peptides. Our study may shed light on the designed synthesis of functional porous materials with controlled structures and enhanced performance in peptides enrichment.

Analyses of copy number variation of GK rat reveal new putative type 2 diabetes susceptibility loci.

Large efforts have been taken to search for genes responsible for type 2 diabetes (T2D), but have resulted in only about 20 in humans due to its complexity and heterogeneity. The GK rat, a spontanous T2D model, offers us a superior opportunity to search for more diabetic genes. Utilizing array comparative genome hybridization (aCGH) technology, we identifed 137 non-redundant copy number variation (CNV) regions from the GK rats when using normal Wistar rats as control. These CNV regions (CNVRs) covered approximately 36 Mb nucleotides, accounting for about 1% of the whole genome. By integrating information from gene annotations and disease knowledge, we investigated the CNVRs comprehensively for mining new T2D genes. As a result, we prioritized 16 putative protein-coding genes and two microRNA genes (rno-mir-30b and rno-mir-30d) as good candidates. The catalogue of CNVRs between GK and Wistar rats identified in this work served as a repository for mining genes that might play roles in the pathogenesis of T2D. Moreover, our efforts in utilizing bioinformatics methods to prioritize good candidate genes provided a more specific set of putative candidates. These findings would contribute to the research into the genetic basis of T2D, and thus shed light on its pathogenesis.

DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data.

SUMMARY: Gene coexpression analysis was developed to explore gene interconnection at the expression level from a systems perspective, and differential coexpression analysis (DCEA), which examines the change in gene expression correlation between two conditions, was accordingly designed as a complementary technique to traditional differential expression analysis (DEA). Since there is a shortage of DCEA tools, we implemented in an R package 'DCGL' five DCEA methods for identification of differentially coexpressed genes and differentially coexpressed links, including three currently popular methods and two novel algorithms described in a companion paper. DCGL can serve as an easy-to-use tool to facilitate differential coexpression analyses. CONTACT: yyli@scbit.org and yxli@scbit.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Time-resolved transcriptome analysis of Bacillus subtilis responding to valine, glutamate, and glutamine.

Microorganisms can restructure their transcriptional output to adapt to environmental conditions by sensing endogenous metabolite pools. In this paper, an Agilent customized microarray representing 4,106 genes was used to study temporal transcript profiles of Bacillus subtilis in response to valine, glutamate and glutamine pulses over 24 h. A total of 673, 835, and 1135 amino-acid-regulated genes were identified having significantly changed expression at one or more time points in response to valine, glutamate, and glutamine, respectively, including genes involved in cell wall, cellular import, metabolism of amino-acids and nucleotides, transcriptional regulation, flagellar motility, chemotaxis, phage proteins, sporulation, and many genes of unknown function. Different amino acid treatments were compared in terms of both the global temporal profiles and the 5-minute quick regulations, and between-experiment differential genes were identified. The highlighted genes were analyzed based on diverse sources of gene functions using a variety of computational tools, including T-profiler analysis, and hierarchical clustering. The results revealed the common and distinct modes of action of these three amino acids, and should help to elucidate the specific signaling mechanism of each amino acid as an effector.