The alleviating effect of ellagic acid on DSS-induced colitis via regulating gut microbiomes and gene expression of colonic epithelial cells.

The anti-inflammatory effect of ellagic acid (EA) and its possible underlying mechanism in dextran sulfate sodium (DSS)-induced mouse chronic colonic inflammation were studied. It was observed that EA administration significantly alleviated the colonic inflammation phenotypes, including decreasing the disease activity index (DAI), enhancing the body weight loss, and improving the shortened length of the colon and pathological damage of colon tissue. Additionally, EA reshaped the constitution of the gut microbiota by elevating the ratio of Bacteroidetes along with Bacteroides and Muribaculaceae, while decreasing the proportion of Firmicutes. The Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt2) revealed that the metabolic function of the gut microbiota was also changed. Furthermore, mouse colon transcriptome analysis showed that the tight junction and peroxisome proliferator-activated receptor (PPAR) signaling pathways were activated and the expressions of related genes were upregulated after EA intervention. These results showed that EA could remodel the gut bacterial composition, change the intestinal epithelial cell gene expressions in mice, and consequently improve the colonic inflammatory symptoms.

Compressible viscoelasticity of cell membranes determined by gigahertz-frequency acoustic vibrations.

Membrane viscosity is an important property of cell biology, which determines cellular function, development and disease progression. Various experimental and computational methods have been developed to investigate the mechanics of cells. However, there have been no experimental measurements of the membrane viscosity at high-frequencies in live cells. High frequency measurements are important because they can probe viscoelastic effects. Here, we investigate the membrane viscosity at gigahertz-frequencies through the damping of the acoustic vibrations of gold nanoplates. The experiments are modeled using a continuum mechanics theory which reveals that the membranes display viscoelasticity, with an estimated relaxation time of ca. 5.7 + 2.4 / - 2.7 ps. We further demonstrate that membrane viscoelasticity can be used to differentiate a cancerous cell line (the human glioblastoma cells LN-18) from a normal cell line (the mouse brain microvascular endothelial cells bEnd.3). The viscosity of cancerous cells LN-18 is lower than that of healthy cells bEnd.3 by a factor of three. The results indicate promising applications of characterizing membrane viscoelasticity at gigahertz-frequency in cell diagnosis.

Dextran-Sulfate-Sodium-Induced Colitis-Ameliorating Effect of Aqueous Phyllanthus emblica L. Extract through Regulating Colonic Cell Gene Expression and Gut Microbiomes.

The anti-inflammation effect of aqueous Phyllanthus emblica L. extract (APE) and its possible underlying mechanism in dextran sulfate sodium (DSS)-induced mice chronic colonic inflammation were studied. APE treatment significantly improved the colitic symptoms, including ameliorating the shortening of the colon, increasing the DSS-induced body weight loss, reducing the disease activity index, and reversing the condition of colon tissue damage of mucus lost and goblet cell reduction. Overproduction of serum pro-inflammatory cytokines were suppressed by the treatment of APE. Gut microbiome analysis showed that APE remodeled the structure of gut bacteria in phylum and genus levels, upregulating the abundance of phylum Bacteroidetes, family Muribaculaceae, and genus Bacteroides and downregulating the abundance of phylum Firmicutes. The reshaped gut microbiome caused metabolic functions and pathway change with enhanced queuosine biosynthesis and reduced polyamine synthesis pathway. Colon tissue transcriptome analysis further elucidated APE-inhibited mitogen-activated protein kinase (MAPK), cytokine-cytokine receptor interaction, and tumor necrosis factor (TNF) signaling pathways and the expressions of the genes that promote the progress of colorectal cancer. It turned out that APE reshaped the gut microbiome and inhibited MAPK, cytokine-cytokine receptor interaction, and TNF signaling pathways as well as the colorectal-cancer-related genes to exert its colitis protective effect.

Data-driven method based on deep learning algorithm for detecting fat, oil, and grease (FOG) of sewer networks in urban commercial areas.

The content of fat, oil and grease (FOG) in the sewer network sediments is the key indicator for diagnosing sewer blockage and overflow. However, the traditional FOG detection is time-consuming and costly, and the establishment of mathematical models based on statistical methods to predict the content of FOG fail to provide satisfactory accuracy. Herein, a deep learning algorithm used a data-driven FOG content prediction model is proposed to achieve a more accurate prediction of FOG content. Meanwhile, global sensitivity analysis (GSA) is exploited to evaluate the contribution of input indicators to the output indicator (FOG) in the model, so that some input indicators that have less impact on the prediction performance can be screened out, the best combination of input indicators can be determined, and the operation cost of the model can be reduced. To evaluate the effectiveness of the proposed model, a case study was conducted in a city in southern China. The experimental results indicate that the prediction model obtains good FOG estimations and performs well from a single site to multiple sites with a mean R2 of 0.922, showing a good generalization performance. Through GSA, the key input indicators in the model were identified as pH, water temperature (T), relative humidity (RH), sewage flow (Flow), drinking water supply (DWS), velocity (V) and conductivity (σ), and the input indicators such as air pressure (AP), population (Pop.), and liquid level (LV) can be reduced without affecting the prediction accuracy of the model.

Metagenome-wide association study of gut microbiome revealed potential microbial marker set for diagnosis of pediatric myasthenia gravis.

BACKGROUND: Myasthenia gravis (MG) is an acquired immune-mediated disorder of the neuromuscular junction that causes fluctuating skeletal muscle weakness and fatigue. Pediatric MG and adult MG have many different characteristics, and current MG diagnostic methods for children are not quite fit. Previous studies indicate that alterations in the gut microbiota may be associated with adult MG. However, it has not been determined whether the gut microbiota are altered in pediatric MG patients. METHODS: Our study recruited 53 pediatric MG patients and 46 age- and gender-matched healthy controls (HC). We sequenced the fecal samples of recruited individuals using whole-genome shotgun sequencing and analyzed the data with in-house bioinformatics pipeline. RESULTS: We built an MG disease classifier based on the abundance of five species, Fusobacterium mortiferum, Prevotella stercorea, Prevotella copri, Megamonas funiformis, and Megamonas hypermegale. The classifier obtained 94% area under the curve (AUC) in cross-validation and 84% AUC in the independent validation cohort. Gut microbiome analysis revealed the presence of human adenovirus F/D in 10 MG patients. Significantly different pathways and gene families between MG patients and HC belonged to P. copri, Clostridium bartlettii, and Bacteroides massiliensis. Based on functional annotation, we found that the gut microbiome affects the production of short-chain fatty acids (SCFAs), and we confirmed the decrease in SCFA levels in pediatric MG patients via serum tests. CONCLUSIONS: The study indicated that altered fecal microbiota might play vital roles in pediatric MG's pathogenesis by reducing SCFAs. The microbial markers might serve as novel diagnostic methods for pediatric MG.

PStrain: an iterative microbial strains profiling algorithm for shotgun metagenomic sequencing data.

MOTIVATION: The microbial community plays an essential role in human diseases and physiological activities. The functions of microbes can differ due to strain-level differences in the genome sequences. Shotgun metagenomic sequencing allows us to profile the strains in microbial communities practically. However, current methods are underdeveloped due to the highly similar sequences among strains. We observe that strains genotypes at the same single nucleotide variant (SNV) locus can be speculated by the genotype frequencies. Also, the variants in different loci covered by the same reads can provide evidence that they reside on the same strain. RESULTS: These insights inspire us to design PStrain, an optimization method that utilizes genotype frequencies and the reads which cover multiple SNV loci to profile strains iteratively based on SNVs in a set of MetaPhlAn2 marker genes. Compared to the state-of-art methods, PStrain, on average, improved the performance of inferring strains abundances and genotypes by 87.75% and 59.45%, respectively. We have applied the PStrain package to the dataset with two cohorts of colorectal cancer (CRC) and found that the sequences of Bacteroides coprocola strains are significantly different between CRC and control samples, which is the first time to report the potential role of B.coprocola in the gut microbiota of CRC. AVAILABILITYAND IMPLEMENTATION: https://github.com/wshuai294/PStrain. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gas diffusion electrodes for H2O2 production and their applications for electrochemical degradation of organic pollutants in water: A review.

Nowadays, it is a great challenge to minimize the negative impact of hazardous organic compounds in the environment. Highly efficient hydrogen peroxide (H2O2) production through electrochemical methods with gas diffusion electrodes (GDEs) is greatly demand for degradation of organic pollutants that present in drinking water and industrial wastewater. The GDEs as cathodic electrocatalyst manifest more cost-effective, lower energy consumption and higher oxygen utilization efficiency for H2O2 production as compared to other carbonaceous cathodes due to its worthy chemical and physical characteristics. In recent years, the crucial research and practical application of GDE for degradation of organic pollutants have been well developed. In this review, we focus on the novel design, fundamental aspects, influence factors, and electrochemical properties of GDEs. Furthermore, we investigate the generation of H2O2 through electrocatalytic processes and degradation mechanisms of refractory organic pollutants on GDEs. We describe the advanced methodologies towards electrochemical kinetics, which include the enhancement of GDEs electrochemical catalytic activity and mass transfer process. More importantly, we also highlight the other technologies assisted electrochemical process with GDEs to enlarge the practical application for water treatment. In addition, the developmental prospective and the existing research challenges of GDE-based electrocatalytic materials for real applications in H2O2 production and wastewater treatment are forecasted. According to our best knowledge, only few review articles have discussed GDEs in detail for H2O2 production and their applications for degradation of organic pollutants in water.

Establishing high-accuracy biomarkers for colorectal cancer by comparing fecal microbiomes in patients with healthy families.

Colorectal cancer (CRC) causes high morbidity and mortality worldwide, and noninvasive gut microbiome (GM) biomarkers are promising for early CRC diagnosis. However, the GM varies significantly based on ethnicity, diet and living environment, suggesting varied GM biomarker performance in different regions. We performed a metagenomic association analysis on stools from 52 patients and 55 corresponding healthy family members who lived together to identify GM biomarkers for CRC in Chongqing, China. The GM of patients differed significantly from that of healthy controls. A total of 22 microbial genes were included as screening biomarkers with high accuracy in additional 46 cases and 40 randomly selected healthy adults in Chongqing (area under the receive-operation curve (AUC) = 0.905, 95% CI 0.832-0.977). The classifier based on the identified 22 biomarkers also performed well in the cohort from Hong Kong (AUC = 0.811, 95% CI 0.715-0.907) and French (AUC = 0.859, 95% CI 0.773-0.944) populations. Quantitative PCR was applied for measuring three selected biomarkers in the classification of CRC patients in independent Chongqing population containing 30 cases and 30 controls and the best biomarker from Coprobacillus performed well with high AUC (0.930, 95% CI 0.904-0.955). This study revealed increased sensitivity and applicability of our GM biomarkers compared with previous biomarkers significantly promoting the early diagnosis of CRC.

Semi-rationally engineered variants of S-adenosylmethionine synthetase from Escherichia coli with reduced product inhibition and improved catalytic activity.

S-adenosylmethionine synthetase (MAT) catalyzes the synthesis of S-adenosylmethionine (SAM) from ATP and L-methionine. SAM is the major methyl donor for more than 100 transmethylation reactions. It is also a common cosubstrate involved in transsulfuration and aminopropylation. However, product inhibition largely restrains the activity of MAT and limits the enzymatic synthesis of SAM. In this research, the product inhibition of MAT from Escherichia coli was reduced via semi-rational modification. A triple variant (Variant III, I303 V/I65 V/L186 V) showed a 42-fold increase in Ki,ATP and a 2.08-fold increase in specific activity when compared to wild-type MAT. Its Ki,ATP was 0.42 mM and specific acitivity was 3.78 ±0.19 U/mg. Increased Ki,ATP means reduced product inhibition which enhances SAM accumulation. The SAM produced by Variant III could reach to 3.27 mM while SAM produced by wild-type MAT was 1.62 mM in the presence of 10 mM substrates. When the residue in 104th of Variant III was further optimized by site-saturated mutagenesis, the specific activity of Variant IV (I303 V/I65 V/L186 V/N104 K) reached to 6.02 ±0.22 U/mg at 37 °C, though the SAM concentration decreased to 2.68 mM with 10 mM substrates. Analysis of protein 3D structure suggests that changes in hydrogen bonds or other ligand interactions around active site may account for the variety of product inhibition and enzyme activity. The Variant III and Variant IV with reduced inhibition and improved enzyme activity in the study would be more suitable candidates for SAM production in the future.

The differential profiles of long non-coding RNAs between rheumatoid arthritis and gouty arthritis.

OBJECTIVE: This study was designed to determine the differential profiles of long non-coding RNAs (lncRNAs) between rheumatoid arthritis (RA) and gouty arthritis (GA), which may lead to the discovery of specific biomarkers for RA diagnosis and treatment in the future. METHODS: The profiles of lncRNAs were determined by Agilent microarray. Bioinformatics analyses, including Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, of the large dataset obtained from microarray experiments were performed. RESULTS: A total of 765 lncRNAs and 2,808 mRNAs were significantly and differentially expressed in RA samples as compared to GA samples. Moreover, of 2,808 differentially expressed mRNAs, 178 upregulated mRNAs and 21 downregulated mRNAs were identified to be strongly correlated with lncRNAs examined in this study. Bioinformatics analyses revealed the tumor-like phenotype of synovial cells in RA and the involvement of immune system process in GA. In addition, this study demonstrated the significantly different molecular origins of two Chinese Medicine syndrome patterns of RA patients -- blood stasis and non-blood stasis. CONCLUSIONS: Our study showed for the first time the differentially expressed lncRNA profiles in synovial tissues between RA and GA and between two clinical phenotypes of RA patients differentiated by Chinese Medicine. This study helps achieving personalized medicine in RA. Larger-scale studies are required to validate the data presented.

Integrated analysis of microRNA regulatory network in nasopharyngeal carcinoma with deep sequencing.

BACKGROUND: MicroRNAs (miRNAs) have been shown to play a critical role in the development and progression of nasopharyngeal carcinoma (NPC). Although accumulating studies have been performed on the molecular mechanisms of NPC, the miRNA regulatory networks in cancer progression remain largely unknown. Laser capture microdissection (LCM) and deep sequencing are powerful tools that can help us to detect the integrated view of miRNA-target network. METHODS: Illumina Hiseq2000 deep sequencing was used to screen differentially expressed miRNAs in laser-microdessected biopsies between 12 NPC and 8 chronic nasopharyngitis patients. The result was validated by real-time PCR on 201 NPC and 25 chronic nasopharyngitis patients. The potential candidate target genes of the miRNAs were predicted using published target prediction softwares (RNAhybrid, TargetScan, Miranda, PITA), and the overlay part was analyzed in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological process. The miRNA regulatory network analysis was performed using the Ingenuity Pathway Analysis (IPA) software. RESULTS: Eight differentially expressed miRNAs were identified between NPC and chronic nasopharyngitis patients by deep sequencing. Further qRT-PCR assays confirmed 3 down-regulated miRNAs (miR-34c-5p, miR-375 and miR-449c-5p), 4 up-regulated miRNAs (miR-205-5p, miR-92a-3p, miR-193b-3p and miR-27a-5p). Additionally, the low level of miR-34c-5p (miR-34c) was significantly correlated with advanced TNM stage. GO and KEGG enrichment analyses showed that 914 target genes were involved in cell cycle, cytokine secretion and tumor immunology, and so on. IPA revealed that cancer was the top disease associated with those dysregulated miRNAs, and the genes regulated by miR-34c were in the center of miRNA-mRNA regulatory network, including TP53, CCND1, CDK6, MET and BCL2, and the PI3K/AKT/ mTOR signaling was regarded as a significant function pathway in this network. CONCLUSION: Our study presents the current knowledge of miRNA regulatory network in NPC with combination of bioinformatics analysis and literature research. The hypothesis of miR-34c regulatory pathway may be beneficial in guiding further studies on the molecular mechanism of NPC tumorigenesis.