Impact of the lipase inhibitor orlistat on the human gut microbiota.

Orlistat, an anti-obesity agent, inhibits the metabolism and absorption of dietary fat by inactivating pancreatic lipase in the gut. The effect of orlistat on the gut microbiota of Japanese individuals with obesity is unknown. This study aimed to explore the effects of orlistat on the gut microbiota and fatty acid metabolism of Japanese individuals with obesity. Fourteen subjects with visceral fat obesity (waist circumference ≥85 cm) took orlistat orally at a dose of 60 mg, 3 times a day for 8 weeks. Body weight; waist circumference; visceral fat area; levels of short-chain fatty acids, gut microbiota, fatty acid metabolites in the feces, and gastrointestinal hormones; and adverse events were evaluated. Body weight, waist circumference, and blood leptin concentrations were significantly lower after orlistat treatment (mean ± standard deviation, 77.8 ± 9.1 kg; 91.9 ± 8.7 cm; and 4546 ± 3211 pg/mL, respectively) compared with before treatment (79.4 ± 9.0 kg; 94.4 ± 8.0 cm; and 5881 ± 3526 pg/mL, respectively). Significant increases in fecal levels of fatty acid metabolites (10-hydroxy-cis-12-octadecenoic acid, 10-oxo-cis-12-octadecenoic acid, and 10-oxo-trans-11-octadecenoic acid) were detected. Meanwhile, no significant changes were found in abdominal computed tomography parameters, blood marker levels, or short-chain fatty acid levels in the feces. Gut microbiota analysis revealed that some study subjects had decreased abundance of Firmicutes, increased abundance of Bacteroidetes, and increased α-diversity indices (Chao1 and ACE) after 8 weeks of treatment. The levels of Lactobacillus genus and Lactobacillus gasseri were significantly higher after 8 weeks of treatment. None of the subjects discontinued treatment or experienced severe adverse events. This study suggested that orlistat might alter gut microbiota composition and affect the body through fatty acid metabolites produced by the modified gut bacteria.

FGF23 modulates the effects of erythropoietin on gene expression in renal epithelial cells.

BACKGROUND: FGF23 plays an important role in calcium-phosphorus metabolism. Other roles of FGF23 have recently been reported, such as commitment to myocardium enlargement and immunological roles in the spleen. In this study, we aimed to identify the roles of FGF23 in the kidneys other than calcium-phosphorus metabolism. METHODS: DNA microarrays and bioinformatics tools were used to analyze gene expression in mIMCD3 mouse renal tubule cells following treatment with FGF23, erythropoietin and/or an inhibitor of ERK. RESULTS: Three protein-coding genes were upregulated and 12 were downregulated in response to FGF23. Following bioinformatics analysis of these genes, PPARγ and STAT3 were identified as candidate transcript factors for mediating their upregulation, and STAT1 as a candidate for mediating their downregulation. Because STAT1 and STAT3 also mediate erythropoietin signaling, we investigated whether FGF23 and erythropoietin might show interactive effects in these cells. Of the 15 genes regulated by FGF23, 11 were upregulated by erythropoietin; 10 of these were downregulated following cotreatment with FGF23. Inhibition of ERK, an intracellular mediator of FGF23, reversed the effects of FGF23. However, FGF23 did not influence STAT1 phosphorylation, suggesting that it impinges on erythropoietin signaling through other mechanisms. CONCLUSION: Our results suggest cross talk between erythropoietin and FGF23 signaling in the regulation of renal epithelial cells.

Identification of baseline gene expression signatures predicting therapeutic responses to three biologic agents in rheumatoid arthritis: a retrospective observational study.

BACKGROUND: According to EULAR recommendations, biologic DMARDs (bDMARDs) such as tumor necrosis factor inhibitor, tocilizumab (TCZ), and abatacept (ABT) are in parallel when prescribing to rheumatoid arthritis (RA) patients who have shown insufficient response to conventional synthetic DMARDs. However, most prediction studies of therapeutic response to bDMARDs using gene expression profiles were focused on a single bDMARD, and consideration of the results from the perspective of RA pathophysiology was insufficient. The aim of this study was to identify the specific molecular biological features predicting the therapeutic outcomes of three bDMARDs (infliximab [IFX], TCZ, and ABT) by studying blood gene expression signatures of patients before biologic treatment in a unified test platform. METHODS: RA patients who responded inadequately to methotrexate and were later commenced on any one of IFX (n = 140), TCZ (n = 38), or ABT (n = 31) as their first biologic between May 2007 and November 2011 were enrolled. Whole-blood gene expression data were obtained before biologic administration. Patients were categorized into remission (REM) and nonremission (NON-REM) groups according to CDAI at 6 months of biologic therapy. We employed Gene Set Enrichment Analysis (GSEA) to identify functional gene sets differentially expressed between these two groups for each biologic. Then, we compiled "signature scores" for these gene sets, and the prediction performances were assessed. RESULTS: GSEA showed that inflammasome genes were significantly upregulated with IFX in the NON-REM group compared with the REM group. With TCZ in the REM group, B-cell-specifically expressed genes were upregulated. RNA elongation, apoptosis-related, and NK-cell-specifically expressed genes were upregulated with ABT in the NON-REM group. Logistic regression analyses showed that "signature scores" of inflammasomes, B-cell-specifically expressed, and NK-cell-specifically expressed genes were significant, independently predictive factors for treatment outcome with IFX, TCZ, and ABT, respectively. The AUCs of ROC curves of these signature scores were 0.637, 0.796, and 0.768 for IFX, TCZ, and ABT, respectively. CONCLUSIONS: We have identified original gene expression predictive signatures uniquely underlying the therapeutic effects of IFX, TCZ, and ABT. This is, to our knowledge, the first attempt to predict therapeutic effects of three drugs concomitantly using a unified gene expression test platform.

A set of external reference controls/probes that enable quality assurance between different microarray platforms.

RNA external standards, although important to ensure equivalence across many microarray platforms, have yet to be fully implemented in the research community. In this article, a set of unique RNA external standards (or RNA standards) and probe pairs that were added to total RNA in the samples before amplification and labeling are described. Concentration-response curves of RNA external standards were used across multiple commercial DNA microarray platforms and/or quantitative real-time polymerase chain reaction (RT-PCR) and next-generation sequencing to identify problematic assays and potential sources of variation in the analytical process. A variety of standards can be added in a range of concentrations spanning high and low abundances, thereby enabling the evaluation of assay performance across the expected range of concentrations found in a clinical sample. Using this approach, we show that we are able to confirm the dynamic range and the limit of detection for each DNA microarray platform, RT-PCR protocol, and next-generation sequencer. In addition, the combination of a series of standards and their probes was investigated on each platform, demonstrating that multiplatform calibration and validation is possible.

Evaluation of toxicity of the mycotoxin citrinin using yeast ORF DNA microarray and Oligo DNA microarray.

BACKGROUND: Mycotoxins are fungal secondary metabolites commonly present in feed and food, and are widely regarded as hazardous contaminants. Citrinin, one of the very well known mycotoxins that was first isolated from Penicillium citrinum, is produced by more than 10 kinds of fungi, and is possibly spread all over the world. However, the information on the action mechanism of the toxin is limited. Thus, we investigated the citrinin-induced genomic response for evaluating its toxicity. RESULTS: Citrinin inhibited growth of yeast cells at a concentration higher than 100 ppm. We monitored the citrinin-induced mRNA expression profiles in yeast using the ORF DNA microarray and Oligo DNA microarray, and the expression profiles were compared with those of the other stress-inducing agents. Results obtained from both microarray experiments clustered together, but were different from those of the mycotoxin patulin. The oxidative stress response genes--AADs, FLR1, OYE3, GRE2, and MET17--were significantly induced. In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated. In the category of "metabolism", genes involved in the glutathione synthesis pathway were activated, and in the category of "cell rescue, defense and virulence", the ABC transporter genes were induced. To alleviate the induced stress, these cells might pump out the citrinin after modification with glutathione. While, the citrinin treatment did not induce the genes involved in the DNA repair. CONCLUSION: Results from both microarray studies suggest that citrinin treatment induced oxidative stress in yeast cells. The genotoxicity was less severe than the patulin, suggesting that citrinin is less toxic than patulin. The reproducibility of the expression profiles was much better with the Oligo DNA microarray. However, the Oligo DNA microarray did not completely overcome cross hybridization.

Xenopus death-domain-containing proteins FADD and RIP1 synergistically activate JNK and NF-kappaB.

BACKGROUND INFORMATION: Death receptors (DRs) induce intracellular signalling upon engagement of their cognate ligands, leading to apoptosis, cell survival or pro-inflammatory responses. In mammals, DR signalling is mediated by the recruitment of several DD (death domain)-containing molecules, such as FADD (Fas-associated DD) and RIP1 (receptor-interacting protein 1). RESULTS: To elucidate the molecular mechanisms of intracellular DR signalling in Xenopus, we have isolated cDNAs encoding xFADD (Xenopus FADD), and xRIP1 and its short isoform xRIP1beta, which is produced by alternative splicing of the xRIP1 gene. These DD-containing proteins interacted with Xenopus DR members xDR-M1 and xDR-M2 through their DDs in co-transfected HEK-293T cells. Overexpression of xFADD activated not only xCaspase 8, but also AP-1 (activator protein 1), which reflects activation of JNK (c-Jun N-terminal kinase) and NF-kappaB (nuclear factor kappaB). A comparative analysis of xRIP1, a kinase-dead mutant of xRIP1 and xRIP1beta indicated that the kinase activity of xRIP1 was required for the activation of AP-1 and NF-kappaB. Interestingly, xFADD and xRIP1 interacted with each other via their DDs, and the expression of a mutant xRIP1 containing only the DD (xRIP1-DD) repressed the xFADD-induced activation of NF-kappaB and AP-1. xFADD and xRIP1 synergistically induced the activation of AP-1 and NF-kappaB, both of which were partially mediated by TRAF2 (tumour-necrosis-factor-receptor-associated factor 2) and TAK1 (transforming-growth-factor-beta-activated kinase 1). We also found that the activation pathways of NF-kappaB induced by xDR-M2 were inhibited by xRIP1-DD. CONCLUSIONS: Xenopus FADD, RIP1 and its splice variant RIP1beta have been characterized. Interaction of xFADD and xRIP1 induced synergistic activation of JNK and NF-kappaB. In addition, the NF-kappaB activation induced by xDR-M2 was partially mediated by xRIP1.

Xenopus death receptor-M1 and -M2, new members of the tumor necrosis factor receptor superfamily, trigger apoptotic signaling by differential mechanisms.

Signaling through the tumor necrosis factor receptor (TNFR) superfamily can lead to apoptosis or promote cell survival, proliferation, and differentiation. A subset of this family, including TNFR1 and Fas, signals cell death via an intracellular death domain and therefore is termed the death receptor (DR) family. In this study, we identified new members of the DR family, designated xDR-M1 and xDR-M2, in Xenopus laevis. The two proteins, which show high homology (71.7% identity), have characteristics of the DR family, that is, three cysteine-rich domains, a transmembrane domain, and a death domain. To elucidate how members of xDR-M subfamily regulate cell death and survival, we examined the intracellular signaling mediated by these receptors in 293T and A6 cells. Overexpression of xDR-M2 induced apoptosis and activated caspase-8, c-Jun N-terminal kinase, and nuclear factor-kappaB, although its death domain to a greater extent than did that of xDR-M1 in 293T cells. A caspase-8 inhibitor potently blocked this apoptosis induced by xDR-M2. In contrast, xDR-M1 showed a greater ability to induce apoptosis through its death domain than did xDR-M2 in A6 cells. Interestingly, a general serine protease inhibitor, but not the caspase-8 inhibitor, blocked the xDR-M1-induced apoptosis. These results imply that activation of caspase-8 or serine protease(s) may be required for the xDR-M2- or xDR-M1-induced apoptosis, respectively. Although xDR-M1 and xDR-M2 are very similar to each other, the difference in their death domains may result in diverse signaling, suggesting distinct roles of xDR-M1 and xDR-M2 in cell death or survival.