Quantitative proteomic analysis of rat liver for carcinogenicity prediction in a 28-day repeated dose study

Impact of beta-tricalcium phosphate on preventing tooth extraction-triggered bisphosphonate-related osteonecrosis of the jaw in rats

Antiresorptive or antiangiogenic drugs can cause medication-related osteonecrosis of the jaw that is refractory. Bisphosphonate-related osteonecrosis of the jaw (BRONJ) may be caused by procedures such as tooth extraction damage the alveolar bone, release bisphosphonates (BPs) and impede healing. This study investigated strategies for BRONJ prevention and molecular mechanisms of its onset. We assessed the effectiveness of filling extraction sockets with beta-tricalcium phosphate (β-TCP). Rats were administered zoledronic acid (ZA) 1.2 mg/kg once per week for 2 weeks, and a molar was extracted. They were randomly assigned to the β-TCP group (bone defects filled with 0.01 g of β-TCP) or control group. Tissue content measurements indicated 2.2 ng of ZA per socket in the β-TCP group and 4.9 ng in the control group, confirming BP distribution and BP adsorption by β-TCP in vivo. At 4 weeks after extraction, the β-TCP group had normal mucosal coverage without inflammation. Moreover, at 8 weeks after extraction, enhanced bone healing, socket coverage, and new bone formation were observed in the β-TCP group. Connective tissue in the extraction sockets suggested that local increases in BP concentrations may suppress the local autophagy mechanisms involved in BRONJ. Filling extraction sockets with β-TCP may prevent BRONJ.

Pharmaceutical Advances and Proteomics Researches

Proteomics enables understanding the composition, structure, function and interactions of the entire protein complement of a cell, a tissue, or an organism under exactly defined conditions. Some factors such as stress or drug effects will change the protein pattern and cause the present or absence of a protein or gradual variation in abundances. The aim of this study is to explore relationship between proteomics application and drug discovery. "proteomics", "Application", and "pharmacology were the main keywords that were searched in PubMed (PubMed Central), Web of Science, and Google Scholar. The titles that were stablished by 2019, were studied and after study of the appreciated abstracts, the full texts of the 118 favor documents were extracted. Changes in the proteome provide a snapshot of the cell activities and physiological processes. Proteomics shows the observed protein changes to the causal effects and generate a complete three-dimensional map of the cell indicating their exact location. Proteomics is used in different biological fields and is applied in medicine, agriculture, food microbiology, industry, and pharmacy and drug discovery. Biomarker discovery, follow up of drug effect on the patients, and in vitro and in vivo proteomic investigation about the drug treated subjects implies close relationship between proteomics advances and application and drug discovery and development. This review overviews and summarizes the applications of proteomics especially in pharmacology and drug discovery.

Establishment of combined analytical method to extract the genes of interest from transcriptome data

Techniques for analyzing genome-wide expression profiles, such as the microarray technique and next-generation sequencers, have been developed. While these techniques can provide a lot of information about gene expression, selection of genes of interest is complicated because of excessive gene expression data. Thus, many researchers use statistical methods or fold change as screening tools for finding gene sets whose expression is altered between groups, which may result in the loss of important information. In the present study, we aimed to establish a combined method for selecting genes of interest with a small magnitude of alteration in gene expression by coupling with proteome analysis. We used hypercholesterolemic rats to examine the effects of a crude herbal drug on gene expression and proteome profiles. We could not select genes of interest by using standard methods. However, by coupling with proteome analysis, we found several effects of the crude herbal drug on gene expression. Our results suggest that this method would be useful in selecting gene sets with expressions that do not show a large magnitude of alteration.

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Herbal crude drug SJG had mild effects on the gene expression profile.

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It was difficult to select genes altered by SJG with conventional methods.

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We established analytical method for transcriptome by using proteome experiments.

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We identified genes of interest that could not be selected by conventional methods.

Commitment of Annexin A2 in recruitment of microRNAs into extracellular vesicles

Extracellular vesicles (EVs) contain microRNAs (miRNAs). However, the exact molecular mechanisms of the recruitment of miRNAs in EVs are not well characterized. Based on proteomic analysis, we identified that silencing of Annexin A2 (ANXA2) significantly decreased the amount of miRNAs in EVs. In addition, microarray analysis revealed that ANXA2 regulated the loading of miRNAs into EVs in a sequence independent manner. Lastly, immunoprecipitation analysis confirmed that ANXA2 could bind miRNAs in EVs in the presence of Ca(2+). These observations demonstrate that ANXA2 plays an important role in the packaging process of miRNAs into EVs.

Development of a novel transgenic rice with hypocholesterolemic activity via high-level accumulation of the α' subunit of soybean β-conglycinin

Soybean 7S globulin, known as β-conglycinin, has been shown to regulate human plasma cholesterol and triglyceride levels. Furthermore, the α' subunit of β-conglycinin has specifically been shown to possess low-density lipoprotein (LDL)-cholesterol-lowering activity. Therefore, accumulation of the α' subunit of β-conglycinin in rice seeds could lead to the production of new functional rice that could promote human health. Herein, we used the low-glutelin rice mutant 'Koshihikari' (var. a123) and suppressed its glutelins and prolamins, the major seed storage proteins of rice, by RNA interference. The accumulation levels of the α' subunit in the lines with suppressed glutelin and prolamin levels were >20 mg in 1 g of rice seeds, which is considerably higher than those in previous studies. Oral administration of the transgenic rice containing the α' subunit exhibited a hypocholesterolemic activity in rats; the serum total cholesterol and LDL cholesterol levels were significantly reduced when compared to those of the control rice (var. a123). The cholesterol-lowering action by transgenic rice accumulating the α' subunit induces a significant increase in fecal bile acid excretion and a tendency to increase in fecal cholesterol excretion. This is the first report that transgenic rice exhibits a hypocholesterolemic activity in rats in vivo by using the β-conglycinin α' subunit.

A metabolomics investigation of non-genotoxic carcinogenicity in the rat

Non-genotoxic carcinogens (NGCs) promote tumor growth by altering gene expression, which ultimately leads to cancer without directly causing a change in DNA sequence. As a result NGCs are not detected in mutagenesis assays. While there are proposed biomarkers of carcinogenic potential, the definitive identification of non-genotoxic carcinogens still rests with the rat and mouse long-term bioassay. Such assays are expensive and time-consuming and require a large number of animals, and their relevance to human health risk assessments is debatable. Metabolomics and lipidomics in combination with pathology and clinical chemistry were used to profile perturbations produced by 10 compounds that represented a range of rat non-genotoxic hepatocarcinogens (NGC), non-genotoxic non-hepatocarcinogens (non-NGC), and a genotoxic hepatocarcinogen. Each compound was administered at its maximum tolerated dose level for 7, 28, and 91 days to male Fisher 344 rats. Changes in liver metabolite concentration differentiated the treated groups across different time points. The most significant differences were driven by pharmacological mode of action, specifically by the peroxisome proliferator activated receptor alpha (PPAR-α) agonists. Despite these dominant effects, good predictions could be made when differentiating NGCs from non-NGCs. Predictive ability measured by leave one out cross validation was 87% and 77% after 28 days of dosing for NGCs and non-NGCs, respectively. Among the discriminatory metabolites we identified free fatty acids, phospholipids, and triacylglycerols, as well as precursors of eicosanoid and the products of reactive oxygen species linked to processes of inflammation, proliferation, and oxidative stress. Thus, metabolic profiling is able to identify changes due to the pharmacological mode of action of xenobiotics and contribute to early screening for non-genotoxic potential.

Preventive effects of the anti-vasospasm agent via the regulation of the Rho-kinase pathway on the development of steroid-induced osteonecrosis in rabbits

A number of studies have suggested that ischemia is the principal pathomechanism of osteonecrosis, however, the detailed mechanism responsible for ischemia remains unclear. We examined the effects of fasudil, an anti-vasospasm agent, on the development of steroid-induced osteonecrosis in rabbits. One group of rabbits received 15mg/kg of fasudil intravenously, which were then injected once intramuscularly with 20mg/kg of methylprednisolone (n=33), and one received methylprednisolone alone as a control (n=28). Eight rabbits from each group were sacrificed 24h after methylprednisolone injection to analyze them by the expression of endothelinA-receptor and eNOS. Two weeks after the steroid injection, the femora and humeri were examined histopathologically for the incidence of osteonecrosis. In addition, plasma from each of four osteonecrosis-positive or -negative rabbits was used for the proteomic analysis in the fasudil group. The incidence of osteonecrosis was significantly lower in the fasudil group (32%) than that in the control group (75%) (P<0.01). Immunohistochemically, endothelinA-receptor expressions levels were decreased in the smooth muscle of the bone marrow in the fasudil group in comparison to that in the control group. The eNOS expressions levels in both serum and bone marrow in the MF group were significantly higher than those in the M group (P<0.05). Based on the proteomic analysis, several proteins related to vasospasm, such as fibrinogen, thrombin, and apolipoprotein E, were identified in rabbits with osteonecrosis soon after steroid administration. This study indicates that vasospasm is one of the important factors involved in the pathogenesis of steroid-induced osteonecrosis and that the anti-vasospasm agents seem to decrease the incidence of steroid-induced osteonecrosis.

Finding biomarkers is getting easier

Single biomarkers are rarely accurate. Even suites of biomarkers can give conflicting results. Ideally potent combinations of variables are isolated which accurately identify specific analytes and their level of toxicity. The search for such combinations can be done by reducing the thousands of candidate variables to the small number necessary for treatment classification. When the key variables are recognized by machine learning (ML) the results are quite surprising, given the apparent failure of other searching methods to produce good diagnostics. Proteins seem especially useful for portable field tests of a variety of adverse conditions. This review shows how ML, in particular artificial neural networks, can find potent biomarkers embedded in any type of expression data, mainly proteins in this article. A computer does multiple iterations to produce sets of proteins which systematically identify (to near 100% accuracy) the treatment classes of interest. Whether these proteins are useful in actual diagnoses is tested by presenting the computer model with unknown classes. Finding the biomarkers is getting easier but there still must be confirmation, by multivariable statistics and with field studies.

Mass spectrometry-based chemoproteomic approaches

The term "chemical proteomics" refers to a research area at the interface of chemistry, biochemistry, and cell biology that focuses on studying the mechanism of action of bioactive small molecule compounds, which comprises the mapping of their target proteins and their impact on protein expression and posttranslational modifications in target cells or tissues of interest on a proteome-wide level. For this purpose, a large arsenal of approaches has emerged in recent years, many of which employing quantitative mass spectrometry. This review briefly summarizes major experiment types employed in current chemical proteomics research.

Deficiency of glycine N-methyltransferase results in deterioration of cellular defense to stress in mouse liver

PURPOSE

Previously, we reported that glycine N-methyltransferase (GNMT) interacts with benzo[a]pyrene (BaP) and inhibits BaP-DNA adducts formation. In addition, Gnmt knockout (Gnmt(-/-)) mice developed chronic hepatitis and hepatocellular carcinoma (HCC). The aims of this study were to understand the gene expression profile of Gnmt(-/-) mice and to study the interaction between BaP and GNMT deficiency in vivo.

EXPERIMENTAL DESIGN

Gene expression profiles of Gnmt(-/-) mice were analyzed by 2-D PAGE and real-time PCR. Both wild-type and Gnmt(-/-) mice were challenged with BaP and sacrificed at the age of 13 months.

RESULTS

Compared with the wild-type mice, proteins involved in the anti-oxidation/detoxification response, glycolytic energy metabolism and one-carbon metabolism pathways were down-regulated significantly in Gnmt(-/-) mice. Malondialdehyde assay showed that lipid peroxidation was significantly increased in the Gnmt(-/-) mice liver. H(2)O(2) treatment demonstrated that the survival rate of HuH-7 cells overexpressing GNMT was significantly higher than the controls. BaP challenge experiments showed that 71.4% (5/7) of male and all (7/7) female Gnmt(-/-) mice developed HCC, while only 16.7% (1/6) of male and 20% (1/5) of female wild-type mice had HCC.

CONCLUSION AND CLINICAL RELEVANCE

GNMT regulates genes related to detoxification and anti-oxidation pathways. BaP is a liver cancer carcinogen especially during GNMT deficiency.

A novel immunoregulatory protein in human colostrum, syntenin-1, for promoting the development of IgA-producing cells from cord blood B cells

Human colostrum contains many bioactive factors that must promote the development of intestinal mucosal immunity in infants. Especially, the presence of certain cytokines such as transforming growth factor (TGF)-beta or IL-10 has been of great interest for IgA production as a function of mucosal immune response. In the present study, we attempted to investigate whether unidentified factors inducing generation of IgA-producing cells from naive B cells might exist in colostrum. For this purpose, colostrum samples were directly added to a culture consisting of naive B cells and dendritic cells from cord blood and CD40 ligand-transfected L cells, comparing with recombinant IL-10 (rIL-10) and/or rTGF-beta. It was noted that most colostrum samples alone were able to induce IgA-secreting cells at higher levels than rIL-10 and/or rTGF-beta. IgA-inducing activity of colostrum was abolished by neither anti-neutralizing mAbs against IL-10 nor TGF-beta, though partially by anti-IL-6 mAb. We prepared partially purified fractions from both pooled colostrums with and without IgA-inducing activity and comparatively performed quantitative proteomic analysis by two-dimensional difference gel electrophoresis followed by liquid chromatography-mass spectrometry. As a result, syntenin-1 was identified as a candidate for IgA-inducing protein in colostrum. Western blot analysis indicated that levels of syntenin-1 in colostrum samples were correlated with their IgA-inducing activities. Moreover, we demonstrated that recombinant syntenin-1 could induce preferentially IgA production from naive B cells. These results suggest that syntenin-1 serves as one of IgA-inducing factors for B cells.

Proteomic study of the effects of microcystin-LR on organelle and membrane proteins in medaka fish liver

The microcystin-leucine-arginine toxin (MC-LR) is produced by cyanobacteria that sometimes bloom in water reservoirs. It targets the liver, thus posing potential health risks to human and animals. Microcystin inhibits the protein phosphatases PP1 and PP2A, leading to diverse cellular deregulation processes. A proteomic approach was applied to the medaka fish (Oryzias latipes) to obtain an overview of the effects of MC-LR on the liver. As membrane and organelle proteins are major structural and functional components of several cell signalling pathways, we decided to investigate here the membrane and organelle-enriched fractions from the livers of control and MC-LR treated medaka fish. Seventeen proteins were identified by proteomic analysis as being modulated in response to MC-LR treatment. This is the first time for eight of them to be reported as being involved in MC-LR effects: prohibitin, fumarylacetoacetase, protein disulfide isomerase A4 and A6, glucose regulated protein 78kDa, 40S ribosomal protein SA, cytochrome b5, and ATP synthase mitochondrial d subunit. These proteins are involved in protein maturation or in the response to oxidative stress highlighting the role of organelles in protein processing and the complex cooperation associated with oxidative stress.

Revealing promiscuous drug-target interactions by chemical proteomics

The (poly-)pharmacological activities of a drug can only be understood if its interactions with cellular components are comprehensively characterized. Mass spectrometry-based chemical proteomics approaches have recently emerged as powerful tools for the characterization of drug-target interactions in samples from cell lines and tissues. At the same time, off-target activities can be identified. This information can contribute toward optimization of candidate drug molecules and reduction of side effects. In this review, we describe recent advances in chemical proteomics and outline potential applications in drug discovery.

Protein expression profiling

Protein expression profiling is defined in general as identifying the proteins expressed in a particular tissue, under a specified set of conditions and at a particular time, usually compared to expression in reference samples. This information is useful in drug discovery and diagnosis as well as in understanding response mechanisms at the protein level. We may identify all the proteins responding to a particular stimulus and select those whose expression changes most. Or we may isolate significant protein variables and then identify them. These definitive sets of proteins (protein expression signatures; PES) are specific to diseases, toxicants, physical stresses, and to degrees of stress severity. Here we describe a method, based on machine learning, for isolating the sets of proteins, before identifying them by name, which classify accurately the treatment classes in a study. The principle in this chapter is that if proteins associated with known classes of interest can be used to identify unknown classes then the proteins are definitive for diagnosis.The proteins in each class, including controls, are converted to digital data and serve as input to artificial neural network (ANN) models. Multiple two-dimensional electrophoresis (2DE) gel patterns are included in each treatment class. A training subset of digitized individual, not composite, gel images is used to construct an ANN model which is then applied to a test set of images. Successful classification of the unknown (test) data confirms that the variables included in the model are indeed significant in discrimination among the classes. In the study described here the misclassifications were 5% or less using the ANN models. The ANN method seems to be a useful complement to image analysis, described in Chapter "Troubleshooting Image Analysis in 2DE". The reduction in protein variables permits multivariable statistics such as cluster and discriminant analyses.