Cheong-sang-bang-pung-san alleviated hepatic lipid accumulation by regulating lipid metabolism in vitro and in vivo.

Introduction: The occurrence of fatty liver disease, resulting from the accumulation of excessive fat within the liver, has been showing a significant and rapid increase. This study aimed to evaluate the therapeutic effects of Cheong-sang-bang-pung-san extract (CB) on fatty liver disease, and to elucidate the underlying mechanisms. Methods: We used a high-fat diet (HFD)-fed fatty liver mice and free fatty acid (FFA) induced HepG2 cell lipid accumulation model. The levels of serum, hepatic, and intracellular lipid content were assessed. Histopathological staining was used to evaluate the extent of hepatic lipid accumulation. Real-time polymerase chain reaction and Western blotting were conducted to examine the expression of factors associated with lipid metabolism. Results: We demonstrated that treatment with CB dramatically reduced body weight, liver weight, and fat mass, and improved the serum and hepatic lipid profiles in HFD-induced fatty liver mice. Additionally, CB alleviated lipid accumulation in HFD-fed mice by controlling lipid metabolism, including fatty acid uptake, triglyceride and cholesterol synthesis, and fatty acid oxidation, at the mRNA as well as protein levels. In free fatty acid-treated HepG2 cells, CB significantly reduced intracellular lipid accumulation by regulating lipid metabolism via the activation of AMP-activated protein kinase. Conclusion: These findings provide insights into the mechanisms underlying CB's effects on liver steatosis and position of CB as a potential therapeutic candidate for managing lipid metabolic disorders.

Anti-Neuroinflammatory Effects of the Human Milk Oligosaccharide, 2'-Fucosyllactose, Exerted via Modulation of M2 Microglial Activation in a Mouse Model of Ischemia-Reperfusion Injury.

Cerebral ischemic stroke is one of the leading causes of death and disability worldwide. 2'-fucosyllactose (2'-FL), a human milk oligosaccharide, exerts anti-inflammatory effects and plays a protective role in arterial thrombosis; however, its role in ischemic stroke remains unclear. This study aimed to investigate the neuroprotective effects of 2'-FL and its potential mechanisms in a mouse model of ischemic stroke. Neurological score and behavior tests revealed that 2'-FL promoted the recovery of neurological deficits and motor function in middle cerebral artery occlusion (MCAO) mice, and that 2'FL led to a reduction in the size of cerebral infarct. Biochemical studies showed that administration of 2'-FL led to a reduction of reactive oxygen species (ROS)-related products in the brain of MCAO mice. 2'-FL upregulated IL-10 and downregulated TNF-α level. In addition, 2'-FL enhanced M2-type microglial polarization and upregulated CD206 expression at 7 days after MCAO. At 3 days after MCAO, 2'-FL increased IL-4 levels and activated STAT6. Our data show that 2'-FL reduced the neurological symptoms of ischemic stroke and ROS accumulation in the brain through IL-4/STAT6-dependent M2-type microglial polarization in MCAO mice. These results demonstrate that 2'-FL is a potentially effective therapeutic agent for ischemic stroke.

2'-Fucosyllactose and 3-Fucosyllactose Alleviates Interleukin-6-Induced Barrier Dysfunction and Dextran Sodium Sulfate-Induced Colitis by Improving Intestinal Barrier Function and Modulating the Intestinal Microbiome.

Ulcerative colitis is an inflammatory bowel disease (IBD) with relapsing and remitting patterns, and it is caused by varied factors, such as the intestinal inflammation extent and duration. We examined the preventative effects of human milk oligosaccharides (HMOs) on epithelial barrier integrity and intestinal inflammation in an interleukin (IL)-6-induced cell model and dextran sodium sulfate (DSS)-induced acute mouse colitis model. HMOs including 2'-fucosyllactose (FL) and 3-FL and positive controls including fructooligosaccharide (FOS) and 5-acetylsalicylic acid (5-ASA) were orally administrated once per day to C57BL/6J mice with colitis induced by 5% DSS in the administered drinking water. 2'-FL and 3-FL did not affect the cell viability in Caco-2 cells. Meanwhile, these agents reversed IL-6-reduced intestinal barrier function in Caco-2 cells. Furthermore, 2'-FL and 3-FL reversed the body weight loss and the remarkably short colon lengths in DSS-induced acute colitis mice. Moreover, 2'-FL and 3-FL obviously protected the decreasing expression of zonula occluden-1 and occludin in colon tissue relative to the findings in the DSS-treated control group. 2'-FL and 3-FL significantly reduced IL-6 and tumor necrosis factor-α levels in serum relative to the control findings. The summary of these results shows that HMOs prevent colitis mainly by enhancing intestinal barrier function and advancing anti-inflammatory responses. Therefore, HMOs might suppress inflammatory responses and represent candidate treatments for IBD that protect intestinal integrity.

A Genome-Scale Co-Functional Network of Xanthomonas Genes Can Accurately Reconstruct Regulatory Circuits Controlled by Two-Component Signaling Systems.

Bacterial species in the genus Xanthomonas infect virtually all crop plants. Although many genes involved in Xanthomonas virulence have been identified through molecular and cellular studies, the elucidation of virulence-associated regulatory circuits is still far from complete. Functional gene networks have proven useful in generating hypotheses for genetic factors of biological processes in various species. Here, we present a genome-scale co-functional network of Xanthomonas oryze pv. oryzae (Xoo) genes, XooNet (www.inetbio.org/xoonet/), constructed by integrating heterogeneous types of genomics data derived from Xoo and other bacterial species. XooNet contains 106,000 functional links, which cover approximately 83% of the coding genome. XooNet is highly predictive for diverse biological processes in Xoo and can accurately reconstruct cellular pathways regulated by two-component signaling transduction systems (TCS). XooNet will be a useful in silico research platform for genetic dissection of virulence pathways in Xoo.

Network-assisted investigation of virulence and antibiotic-resistance systems in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a Gram-negative bacterium of clinical significance. Although the genome of PAO1, a prototype strain of P. aeruginosa, has been extensively studied, approximately one-third of the functional genome remains unknown. With the emergence of antibiotic-resistant strains of P. aeruginosa, there is an urgent need to develop novel antibiotic and anti-virulence strategies, which may be facilitated by an approach that explores P. aeruginosa gene function in systems-level models. Here, we present a genome-wide functional network of P. aeruginosa genes, PseudomonasNet, which covers 98% of the coding genome, and a companion web server to generate functional hypotheses using various network-search algorithms. We demonstrate that PseudomonasNet-assisted predictions can effectively identify novel genes involved in virulence and antibiotic resistance. Moreover, an antibiotic-resistance network based on PseudomonasNet reveals that P. aeruginosa has common modular genetic organisations that confer increased or decreased resistance to diverse antibiotics, which accounts for the pervasiveness of cross-resistance across multiple drugs. The same network also suggests that P. aeruginosa has developed mechanism of trade-off in resistance across drugs by altering genetic interactions. Taken together, these results clearly demonstrate the usefulness of a genome-scale functional network to investigate pathogenic systems in P. aeruginosa.

TRRUST: a reference database of human transcriptional regulatory interactions.

The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.grnpedia.org/trrust), which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.

Network-assisted genetic dissection of pathogenicity and drug resistance in the opportunistic human pathogenic fungus Cryptococcus neoformans.

Cryptococcus neoformans is an opportunistic human pathogenic fungus that causes meningoencephalitis. Due to the increasing global risk of cryptococcosis and the emergence of drug-resistant strains, the development of predictive genetics platforms for the rapid identification of novel genes governing pathogenicity and drug resistance of C. neoformans is imperative. The analysis of functional genomics data and genome-scale mutant libraries may facilitate the genetic dissection of such complex phenotypes but with limited efficiency. Here, we present a genome-scale co-functional network for C. neoformans, CryptoNet, which covers ~81% of the coding genome and provides an efficient intermediary between functional genomics data and reverse-genetics resources for the genetic dissection of C. neoformans phenotypes. CryptoNet is the first genome-scale co-functional network for any fungal pathogen. CryptoNet effectively identified novel genes for pathogenicity and drug resistance using guilt-by-association and context-associated hub algorithms. CryptoNet is also the first genome-scale co-functional network for fungi in the basidiomycota phylum, as Saccharomyces cerevisiae belongs to the ascomycota phylum. CryptoNet may therefore provide insights into pathway evolution between two distinct phyla of the fungal kingdom. The CryptoNet web server (www.inetbio.org/cryptonet) is a public resource that provides an interactive environment of network-assisted predictive genetics for C. neoformans.

EcoliNet: a database of cofunctional gene network for Escherichia coli.

During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research now focuses on more complex model organisms, E. coli still remains important in metabolic engineering and synthetic biology. Despite its long history as a subject of molecular investigation, more than one-third of the E. coli genome has no pathway annotation supported by either experimental evidence or manual curation. Recently, a network-assisted genetics approach to the efficient identification of novel gene functions has increased in popularity. To accelerate the speed of pathway annotation for the remaining uncharacterized part of the E. coli genome, we have constructed a database of cofunctional gene network with near-complete genome coverage of the organism, dubbed EcoliNet. We find that EcoliNet is highly predictive for diverse bacterial phenotypes, including antibiotic response, indicating that it will be useful in prioritizing novel candidate genes for a wide spectrum of bacterial phenotypes. We have implemented a web server where biologists can easily run network algorithms over EcoliNet to predict novel genes involved in a pathway or novel functions for a gene. All integrated cofunctional associations can be downloaded, enabling orthology-based reconstruction of gene networks for other bacterial species as well. Database URL: http://www.inetbio.org/ecolinet.

WormNet v3: a network-assisted hypothesis-generating server for Caenorhabditis elegans.

High-throughput experimental technologies gradually shift the paradigm of biological research from hypothesis-validation toward hypothesis-generation science. Translating diverse types of large-scale experimental data into testable hypotheses, however, remains a daunting task. We previously demonstrated that heterogeneous genomics data can be integrated into a single genome-scale gene network with high prediction power for ribonucleic acid interference (RNAi) phenotypes in Caenorhabditis elegans, a popular metazoan model in the study of developmental biology, neurobiology and genetics. Here, we present WormNet version 3 (v3), which is a new network-assisted hypothesis-generating server for C. elegans. WormNet v3 includes major updates to the base gene network, which substantially improved predictions of RNAi phenotypes. The server generates various gene network-based hypotheses using three complementary network methods: (i) a phenotype-centric approach to 'find new members for a pathway'; (ii) a gene-centric approach to 'infer functions from network neighbors' and (iii) a context-centric approach to 'find context-associated hub genes', which is a new method to identify key genes that mediate physiology within a specific context. For example, we demonstrated that the context-centric approach can be used to identify potential molecular targets of toxic chemicals. WormNet v3 is freely accessible at http://www.inetbio.org/wormnet.

Complementarity between distance- and probability-based methods of gene neighbourhood identification for pathway reconstruction.

Identifying gene neighbourhoods using either distance- or probability-based measures has proven effective in retrieving co-functional links. We report that these two approaches are highly complementary, with differential sensitivity for the core pathway links. We demonstrate that integrating these measures improves prediction of both pathways and phenotypes.

YeastNet v3: a public database of data-specific and integrated functional gene networks for Saccharomyces cerevisiae.

Saccharomyces cerevisiae, i.e. baker's yeast, is a widely studied model organism in eukaryote genetics because of its simple protocols for genetic manipulation and phenotype profiling. The high abundance of publicly available data that has been generated through diverse 'omics' approaches has led to the use of yeast for many systems biology studies, including large-scale gene network modeling to better understand the molecular basis of the cellular phenotype. We have previously developed a genome-scale gene network for yeast, YeastNet v2, which has been used for various genetics and systems biology studies. Here, we present an updated version, YeastNet v3 (available at http://www.inetbio.org/yeastnet/), that significantly improves the prediction of gene-phenotype associations. The extended genome in YeastNet v3 covers up to 5818 genes (∼99% of the coding genome) wired by 362 512 functional links. YeastNet v3 provides a new web interface to run the tools for network-guided hypothesis generations. YeastNet v3 also provides edge information for all data-specific networks (∼2 million functional links) as well as the integrated networks. Therefore, users can construct alternative versions of the integrated network by applying their own data integration algorithm to the same data-specific links.

JiffyNet: a web-based instant protein network modeler for newly sequenced species.

Revolutionary DNA sequencing technology has enabled affordable genome sequencing for numerous species. Thousands of species already have completely decoded genomes, and tens of thousands more are in progress. Naturally, parallel expansion of the functional parts list library is anticipated, yet genome-level understanding of function also requires maps of functional relationships, such as functional protein networks. Such networks have been constructed for many sequenced species including common model organisms. Nevertheless, the majority of species with sequenced genomes still have no protein network models available. Moreover, biologists might want to obtain protein networks for their species of interest on completion of the genome projects. Therefore, there is high demand for accessible means to automatically construct genome-scale protein networks based on sequence information from genome projects only. Here, we present a public web server, JiffyNet, specifically designed to instantly construct genome-scale protein networks based on associalogs (functional associations transferred from a template network by orthology) for a query species with only protein sequences provided. Assessment of the networks by JiffyNet demonstrated generally high predictive ability for pathway annotations. Furthermore, JiffyNet provides network visualization and analysis pages for wide variety of molecular concepts to facilitate network-guided hypothesis generation. JiffyNet is freely accessible at http://www.jiffynet.org.

[Relationship of socioeconomic factors with medical utilization for lower urinary tract symptoms and benign prostatic hyperplasia in a South Korean community].

OBJECTIVES: We wanted to evaluate the medical underutilization for benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS) among Korean elderly men and we wanted to determine their associated factors. METHODS: This study was conducted on 239 men with LUTS and 116 men with BPH who were compatible with the diagnostic criteria from a total of 641 participants. These participants were over 50 years old and they were randomly chosen in a community-based study for estimating the prevalence of BPH. Using a self-reported questionnaire, we surveyed the sociodemographics, health status, quality of life, lower urinary tract symptoms, medical utilization and reasons for not seeking treatment. RESULTS: Only 27.6% of the men with LUTS and 31.0% of the men with BPH reported having visited a doctor for urinary symptoms. The reasons for not visiting a doctor were, in order of responses from the group with LUTS: 'considered the symptoms as a part of the normal ageing process', 'not enough time to visit a doctor', 'financial difficulty' and 'the symptoms were not severe or bothersome'. Regarding BPH, the responses were the same as those of the group with LUTS however, 'financial difficulty' placed second. Among the men with experience of visiting a doctor for urinary symptoms, 33.3% of those with LUTS and 28.1% of those with BPH were not treated. The most common reason in both groups was 'the symptoms were not severe to be treated'. On a multiple logistic regression analysis, the larger size household (odds ratio (OR) 3.03, 95% confidence interval (Cl) = 1.40-6.54) and an unsatisfactory quality of life related with urinary symptoms (OR 2.98, 95% CI = 1.23-7.21) were associated with medical utilization in the group of LUTS. For BPH, the current employment status was related with the medical utilization (OR 2.80, 95% CI = 1.10-7.11), in addition to the larger size household (OR 3.24, 95% CI = 1.14-9.21). CONCLUSIONS: Many men with urinary symptoms do not visit a doctor. This medical underutilization for people with LUTS and BPH may be associated with economic status in Korea.