Showing papers in "Omics A Journal of Integrative Biology in 2012"
TL;DR: An R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters and can be easily extended to other species and ontologies is presented.
Abstract: Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters The analysis module and visualization module were combined into a reusable workflow Currently, clusterProfiler supports three species, including humans, mice, and yeast Methods provided in this package can be easily extended to other species and ontologies The clusterProfiler package is released under Artistic-20 License within Bioconductor project The source code and vignette are freely available at http://bioconductororg/packages/release/bioc/html/clusterProfilerhtml
16,644 citations
TL;DR: The scientific study of chinmedomics is at an early stage and requires further scrutiny and validation, but the approach has major implications to improve the efficacy ofchinmediformulae.
Abstract: Traditional Chinese medicine (TCM) has been used for thousands of years to treat or prevent disease. The health care paradigm has shifted from a focus on disease to TCM therapy with a holistic approach. However, the actual value of TCM has not been fully recognized worldwide due to a lack of scientific approaches to its study. Today omics has become practically available, and resembles TCM in many aspects, and can serve as a key driving force for the translation of the traditional Chinese medical formulae (chinmediformulae) into practice, and will develop and advance the concept of the metabolomics of chinmediformulae (chinmedomics). Chinmedomics seeks to elucidate the therapeutic and synergistic properties and metabolism of chinmediformulae and the involved metabolic pathways using modern analytical techniques. It is an integral part of top-down systems biology, which aims to improve understanding of chinmediformulae. This approach of combining chinmedomics with chinmediformulae with modern health care systems may lead to a revolution in TCM therapy. Although the scientific study of chinmedomics is at an early stage and requires further scrutiny and validation, the approach has major implications to improve the efficacy of chinmediformulae. This article introduces and reviews the concept of chinmedomics, and highlights recent examples of the approach, which are presented for description and discussion.
158 citations
TL;DR: A predictive computational tool is generated that is able to predict which candidate proteolytic peptide bonds are likely to be missed by the standard enzyme trypsin, which will be a boon for quantitative proteomic pipelines as well as other areas of proteomics.
Abstract: Quantitative proteomics experiments are usually performed using proteolytic peptides as surrogates for their parent proteins, inferring protein amounts from peptide-level quantitation. This process is frequently dependent on complete digestion of the parent protein to its limit peptides so that their signal is truly representative. Unfortunately, proteolysis is often incomplete, and missed cleavage peptides are frequently produced that are unlikely to be optimal surrogates for quantitation, particularly for label-mediated approaches seeking to derive absolute values. We have generated a predictive computational tool that is able to predict which candidate proteolytic peptide bonds are likely to be missed by the standard enzyme trypsin. Our cross-validated prediction tool uses support vector machines and achieves high accuracy in excess of 0.94 precision (PPV), with attendant high sensitivity of 0.79, across multiple proteomes. We believe this is a useful tool for selecting candidate quantotypic peptides, seeking to minimize likely loss owing to missed cleavage, which will be a boon for quantitative proteomic pipelines as well as other areas of proteomics. Our results are discussed in the context of recent results examining the kinetics of missed cleavages in proteomic digestion protocols, and show agreement with observed experimental trends. The software has been made available at http://king.smith.man.ac.uk/mcpred .
76 citations
TL;DR: Microarray analysis of gene expression profiles in placentas from preeclamptic pregnancies and various dysregulated signaling pathways that are altered in preeclampsia provided evidence that a number of biological pathways, including Notch, Wnt, NF-κB, and transforming growth factor-β (TGF-β) signaling pathways, were aberrantly regulated in preeClampsia.
Abstract: The purpose of this study was to perform a comprehensive analysis of gene expression profiles in placentas from preeclamptic pregnancies versus normal placentas. Placental tissues were obtained immediately after delivery from women with normal pregnancies (n=6) and patients with preeclampsia (n=6). The gene expression profile was assessed by oligonucleotide-based DNA microarrays and validated by quantitative real-time RT-PCR. Functional relationships and canonical pathways/networks of differentially-expressed genes were evaluated by GeneSpring™ GX 11.0 software, and ingenuity pathways analysis (IPA). A total of 939 genes were identified that differed significantly in expression: 483 genes were upregulated and 456 genes were downregulated in preeclamptic placentas compared with normal placentas (fold change ≥2 and p<0.05 by unpaired t-test corrected with Bonferroni multiple testing). The IPA revealed that the primary molecular functions of these genes are involved in cellular function and maintena...
69 citations
TL;DR: These observations, while requiring replication, provide new evidence on potential epigenetic mechanisms by which genistein and daidzein might contribute to regulation of the BRCA1 and BrcA2.
Abstract: Although soy phytoestrogens have been postulated to exert a protective effect against breast cancer, the attendant mechanisms, in particular epigenetics underpinnings, have remained elusive. We investigated the putative effects on DNA methylation by two naturally occurring isoflavones, genistein and daidzein, in a study of the BRCA1 and BRCA2 oncosuppressor genes in breast cancer cell lines (MCF-7, MDA-MB 231, and MCF10a). A demethylant agent, the 5-azacytidine, and a methylant, the budesonide, were used as treatment controls. DNA methylation of BRCA1 and BRCA2 was investigated with methylated DNA immunoprecipitation coupled with PCR. In parallel, protein expression was determined by Western blot, immunohistochemistry, and confocal microscopy. Our results suggest that treatment with 18.5 μM Genistein or 78.5 μM Daidzein might reverse DNA hypermethylation and restore the expression of the oncosuppressor genes BRCA1 and BRCA2. 5-Azacitydine also enhanced the reexpression of these genes while budeso...
65 citations
TL;DR: The findings collectively highlight the potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders.
Abstract: Obesity is a risk factor for cardiovascular diseases and type 2 diabetes especially when the fat is accumulated to central depots. Novel biomarkers are crucial to develop diagnostics for obesity and related metabolic disorders. We evaluated the associations between metabolite profiles (136 lipid components, 12 lipoprotein subclasses, 17 low-molecular-weight metabolites, 12 clinical markers) and 28 phenotype parameters (including different body fat distribution parameters such as android (A), gynoid (G), abdominal visceral (VAT), subcutaneous (SAT) fat) in 215 plasma/serum samples from healthy overweight men (n=32) and women (n=83) with central obesity. (Partial) correlation analysis and partial least squares (PLS) regression analysis showed that only specific metabolites were associated to A:G ratio, VAT, and SAT, respectively. These association patterns were gender dependent. For example, insulin, cholesterol, VLDL, and certain triacylglycerols (TG 54:1-3) correlated to VAT in women, while in men VAT was associated with TG 50:1-5, TG 55:1, phosphatidylcholine (PC 32:0), and VLDL ((X)L). Moreover, multiple regression analysis revealed that waist circumference and total fat were sufficient to predict VAT and SAT in women. In contrast, only VAT but not SAT could be predicted in men and only when plasma metabolites were included, with PC 32:0 being most strongly associated with VAT. These findings collectively highlight the potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders.
64 citations
TL;DR: The function of the discriminating genes suggests that tumors have been classified according to their putative response to adjuvant targeted or classic therapies, and further pharmacogenetic studies might verify this observation.
Abstract: Colorectal cancer is one of the most common cancers in the world. Histological staging is efficient, but combination with molecular markers may improve tumor classification. Gene expression profiles have been defined as prognosis predictors among stage II and III tumors, but their implementation in medical practice remains controversial. Stage II tumors have been recognized as a heterogeneous group, and high-risk morphologic features have been used to justify adjuvant chemotherapy. We propose here the investigation of clinical features and expression profiles from stage II and stage III colon carcinomas without DNA mismatch repair defects. Two series of 130 and 66 colon cancer samples were obtained. Expression profiles were established on oligonucleotide microarrays and processed in the R/Bioconductor environment. Hierarchical, then supervised, analyses were successively performed by applying a data-sampling approach. A molecular signature of seven genes was found to cluster stage III tumors with...
63 citations
TL;DR: This work constructed a "Core" Alzheimer's disease protein interaction network by human curation of the primary literature and identified the MAPK/ERK pathway and clathrin-mediated receptor endocytosis as key pathways in Alzheimer's Disease.
Abstract: Network models combined with gene expression studies have become useful tools for studying complex diseases like Alzheimer's disease. We constructed a “Core” Alzheimer's disease protein interaction network by human curation of the primary literature. The Core network consisted of 775 nodes and 2,204 interactions. To our knowledge, this is the most comprehensive and accurate protein interaction network yet constructed for Alzheimer's disease. An “Expanded” network was computationally constructed by adding additional proteins that interacted with Core network proteins, and consisted of 4,945 nodes and 26,064 interactions. We then mapped existing gene expression studies to the Core network. This combined data model identified the MAPK/ERK pathway and clathrin-mediated receptor endocytosis as key pathways in Alzheimer's disease. Important proteins in the MAPK/ERK pathway that interacted in the Core network formed a downregulated cluster of nodes, whereas clathrin and several clathrin accessory protei...
59 citations
TL;DR: This report found 875 and 811 known miRNA and miRNA* in glioblastoma and normal brain tissue, respectively, representing the largest characterization of the miRNAs in GBM so far, and verified the data by quantitative RT-PCR, suggesting that deep sequencing was able to capture the expression profiles of mi RNAs.
Abstract: Glioblastoma is the most common and aggressive primary brain tumor. MicroRNAs (miRNAs) are a set of noncoding RNA of about 20∼22 nt in length and they play regulatory roles such as regulating the expression of proteins. Altered miRNA expression is related to cancers, including glioblastoma. In this report, we used deep sequencing to explore the miRNA profiles of glioblastoma and normal brain tissues. We found 875 and 811 known miRNA and miRNA* in glioblastoma and normal brain tissue, respectively, representing the largest characterization of the miRNAs in GBM so far. 33 of them were upregulated in glioblastoma, including miR-21, which is well known as an oncomir, while 40 of them were downregulated. Using miR-10b, miR-124, miR-433, and miR-92b as examples, we verified the data by quantitative RT-PCR, suggesting that deep sequencing was able to capture the expression profiles of miRNAs. In addition, we found 18 novel miRNA and 16 new miRNA* in glioblastoma and normal brain tissues. This report pro...
59 citations
TL;DR: A computational method that uses the relative binding of aGBP with glycans within a glycan microarray to automatically reveal the glycan structural motifs recognized by a GBP, and implemented the software with a web-based graphical interface for users to explore and visualize the discovered motifs.
Abstract: Assessing interactions of a glycan-binding protein (GBP) or lectin with glycans on a microarray generates large datasets, making it difficult to identify a glycan structural motif or determinant associated with the highest apparent binding strength of the GBP. We have developed a computational method, termed GlycanMotifMiner, that uses the relative binding of a GBP with glycans within a glycan microarray to automatically reveal the glycan structural motifs recognized by a GBP. We implemented the software with a web-based graphical interface for users to explore and visualize the discovered motifs. The utility of GlycanMotifMiner was determined using five plant lectins, SNA, HPA, PNA, Con A, and UEA-I. Data from the analyses of the lectins at different protein concentrations were processed to rank the glycans based on their relative binding strengths. The motifs, defined as glycan substructures that exist in a large number of the bound glycans and few non-bound glycans, were then discovered by our algorithm and displayed in a web-based graphical user interface ( http://glycanmotifminer.emory.edu ). The information is used in defining the glycan-binding specificity of GBPs. The results were compared to the known glycan specificities of these lectins generated by manual methods. A more complex analysis was also carried out using glycan microarray data obtained for a recombinant form of human galectin-8. Results for all of these lectins show that GlycanMotifMiner identified the major motifs known in the literature along with some unexpected novel binding motifs.
55 citations
TL;DR: It is hypothesized that there are putative changes in the body's construction of GAGs as tissue becomes cancerous and there may be innate structural person-to-person variations in GAG composition that facilitate the metastasis of tumors in some patients when they develop cancer.
Abstract: Cancer is one of the leading noncommunicable diseases that vastly impacts both developed and developing countries. Truly innovative diagnostics that inform disease susceptibility, prognosis, and/or response to treatment (theragnostics) are seriously needed for global public health and personalized medicine for patients with cancer. This study examined the structure and content of glycosaminoglycans (GAGs) in lethal and nonlethal breast cancer tissues from six patients. The glycosaminoglycan content isolated from tissue containing lethal cancer tumors was approximately twice that of other tissues. Molecular weight analysis showed that glycosaminoglycans from cancerous tissue had a longer weight average chain length by an average of five disaccharide units, an increase of approximately 15%. Dissacharide analysis found differences in sulfation patterns between cancerous and normal tissues, as well as sulfation differences in GAG chains isolated from patients with lethal and nonlethal cancer. Specifi...
TL;DR: This review will explain how proteomics can help in elucidating important plant processes in response to various abiotic stresses.
Abstract: Plant growth and productivity are influenced by various abiotic stresses. Stressful conditions may lead to delays in seed germination, reduced seedling growth, and decreased crop yields. Plants respond to environmental stresses via differential expression of a subset of genes, which results in changes in omic compositions, such as transcriptome, proteome, and metabolome. Since the development of modern biotechnology, various research projects have been carried out to understand the approaches that plants have adopted to overcome environmental stresses. Advancements in omics have made functional genomics easy to understand. Since the fundamentals of classical genomics were unable to clear up confusion related to the functional aspects of the metabolic processes taking place during stress conditions, new fields have been designed and are known as omics. Proteomics, the analysis of genomic complements of proteins, has caused a flurry of activity in the past few years. It defines protein functions in cells and explains how those protein functions respond to changing environmental conditions. The ability of crop plants to cope up with the variety of environmental stresses depends on a number of changes in their proteins, which may be up- and downregulated as a result of altered gene expression. Most of these molecules display an essential function, either in the regulation of the response (e.g., components of the signal transduction pathway), or in the adaptation process (e.g., enzymes involved in stress repair and degradation of damaged cellular contents), allowing plants to recover and survive the stress. Many of these proteins are constitutively expressed under normal conditions, but when under stress, they undergo a modification of their expression levels. This review will explain how proteomics can help in elucidating important plant processes in response to various abiotic stresses.
TL;DR: A review of some of the most popular techniques for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques and a critical appraisal of several software packages available to process and analyze the data produced.
Abstract: New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool ( http://www.proteosuite.org/?q=other_resources ) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology.
TL;DR: A Java programming interface is developed that can use the output files produced by Progenesis, allowing the basic MS features quantified across replicates to be used in a range of different experimental methods.
Abstract: Numerous software packages exist to provide support for quantifying peptides and proteins from mass spectrometry (MS) data. However, many support only a subset of experimental methods or instrument types, meaning that laboratories often have to use multiple software packages. The Progenesis LC-MS software package from Nonlinear Dynamics is a software solution for label-free quantitation. However, many laboratories using Progenesis also wish to employ stable isotope-based methods that are not natively supported in Progenesis. We have developed a Java programming interface that can use the output files produced by Progenesis, allowing the basic MS features quantified across replicates to be used in a range of different experimental methods. We have developed post-processing software (the Progenesis Post-Processor) to embed Progenesis in the analysis of stable isotope labeling data and top3 pseudo-absolute quantitation. We have also created export ability to the new data standard, mzQuantML, produced by the Proteomics Standards Initiative to facilitate the development and standardization process. The software is provided to users with a simple graphical user interface for accessing the different features. The underlying programming interface may also be used by Java developers to develop other routines for analyzing data produced by Progenesis.
TL;DR: System epidemiology is proposed as a novel approach to study the complexities of human pathophysiology by integrating various population-level omic-metrics and to identify new trans-omic biomarkers.
Abstract: Enabled by diverse high-throughput technologies, the rapidly evolving field of "-omics sciences" offers the potential to study health and disease in breadth and depth at the human population level. We have recently linked genomics and metabolomics to present the first genome-wide association study of metabolic traits in human urine providing new insights into the functional background of chronic kidney disease. We propose systems epidemiology as a novel approach to study the complexities of human pathophysiology by integrating various population-level omic-metrics and to identify new trans-omic biomarkers.
TL;DR: The presence of the MTHFR C677T and ABCB1 C3435T SNPs contribute to MTX toxicity in patients with RA, and observations contribute to a rapidly-growing knowledge base on the pharmacogenetics of RA and personalized medicine.
Abstract: Rheumatoid arthritis (RA) is a common illness of global significance for public health. Methotrexate (MTX) is the most broadly used disease-modifying antirheumatic drug for the treatment of RA, but it displays marked person-to-person variation in its propensity for toxicity. Several studies have suggested that polymorphisms in methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, reduced folate carrier (RFC1) G80A, and ABCB1 C3435T, could be related to methotrexate toxicity. This prospective study examined the different frequencies of MTHFR, RFC1, and ABCB1 pharmacogenetic variations between patients who have RA and those without RA. We also sought to assess the association between these polymorphisms and MTX toxicity. Four single-nucleotide polymorphisms (SNPs) were genotyped: C677T and A1298C from MTHFR, G80A from RFC1, and C3435T from ABCB1. The efficacy and toxicity of MTX were evaluated through clinical follow-up during 1 year of treatment. RA patients showed a higher frequency of th...
TL;DR: This study is the first of its kind to associate rifampicin resistance, rpoB mutations, and the β-subunit of RNA polymerase in M. tuberculosis, with an altered fatty acid metabolism, thereby demonstrating the role that pharmaco-metabolomics can play in identifying new markers associated with drug resistance.
Abstract: We investigated the use of gas chromatography mass spectrometry (GC-MS) metabolomics to better characterize rifampicin-resistance by comparing the fatty acid metabolomes of two rpoB mutant Mycobacterium tuberculosis strains (S522L and S531L) to that of a fully susceptible wild-type parent strain. Using the generated GC-MS metabolite data, principal component analysis (PCA) showed a clear differentiation between all three sample groups analyzed. We subsequently identified those metabolites contributing most to the variation in the data using PCA and partial least squares discriminant analysis (PLS-DA). The altered metabolite markers detected in the rifampicin-resistant mutants indicate a decreased synthesis of various 10-methyl branched-chain fatty acids and cell wall lipids, and an increased use of the shorter-chain fatty acids as carbon sources. Furthermore, the rpoB S531L mutant, previously reported to occur in well over 70% of all clinical rifampicin-resistant M. tuberculosis strains, potentia...
TL;DR: Overall, the adverse effects of salt stress tomato plants were alleviated by the exogenous application of SA at vegetative stage, which upregulated nutrition and the accumulation of some organic solutes and osmoprotectors such sugars, proline, and proteins.
Abstract: In Tunisia, like in the other countries of the Mediterranean, tomato is ranked among the important vegetables in the economic sphere. Tunisia ranks as the first consumer of this vegetable in the world. However, tomatoes are exposed to multiple environmental stresses. In particular, salinity is the most stressful limiting factor to productivity. Salt tolerance of the tomato is susceptible to be ameliorated by genetic and physiologic ways. Salicylic acid (SA), a plant phenolic, is now considered as a hormone-like endogenous regulator, and its role in the defense mechanisms against biotic and abiotic stressors has been well documented. So, the aim of this study was to investigate the impact of exogenous application of SA (0.01 mM) on growth, nutritional behavior, and some metabolic parameters (total chlorophyll, soluble sugars, proline, and proteins) of tomato plants cv. Moneymaker exposed to NaCl (100 mM). Our results showed that the application of 0.01 mM SA to tomato plants via root drenching att...
TL;DR: Multialignments of conserved domains in DREB1, WRKY1 transcription factors, and HKT-1 have been utilized to design specific primers in order to identify functional single nucleotide polymorphisms (SNPs) and several SNPs were found in salt and drought tolerant durum wheat genotypes.
Abstract: Tolerance mechanisms to salinity and drought stress are quite complex. Plants have developed a complex and elaborate signaling network that ensures their adaptation to this stress. For example, salinity tolerance is thought to be due to three main factors: Na(+) exclusion, tolerance to Na(+) in the tissues and osmotic tolerance. Recently, many transcription factors for tolerance to salt and drought stresses have been identified. In this study, multialignments of conserved domains in DREB1, WRKY1 transcription factors (TFs), and HKT-1 have been utilized to design specific primers in order to identify functional single nucleotide polymorphisms (SNPs). These primers have been used to probe on several genotypes of durum wheat that are differentially tolerant to salt and drought stress; they were grown in increasing concentrations of NaCl. The selected portions have been analyzed using high-resolution melting curve (HRM) technology that currently represents one of the most recent and powerful tools for detecting SNP and INDEL mutations. Analyzing the amplification profiles, observed in the resulting melting curves, samples corresponding to different treatment conditions were selected, sequenced, and aligned with the homolog sequences present in gene databases to identify and characterize potential SNP and INDEL mutations. The PCR amplicons, containing single and double SNPs, produced distinctive HRM profiles. By sequencing the polymerase chain reaction (PCR) products, several SNPs have been identified and validated. All the discovered mutations were able to generate changes in amino acid sequences of the corresponding proteins. Most of the identified SNPs were found in salt and drought tolerant durum wheat genotypes. These varieties are of great value for durum wheat breeding works.
TL;DR: An in-depth survey was taken to identify specific PP1α PIPs in human brain by a high-throughput Yeast Two-Hybrid approach, with a large protein interaction databases search performed to integrate with the results of the PP1 α Human Brain Yeast two-hybrid.
Abstract: Protein Phosphatase 1 (PP1) is a major serine/threonine-phosphatase whose activity is dependent on its binding to regulatory subunits known as PP1 interacting proteins (PIPs), responsible for targeting PP1 to a specific cellular location, specifying its substrate or regulating its action. Today, more than 200 PIPs have been described involving PP1 in panoply of cellular mechanisms. Moreover, several PIPs have been identified that are tissue and event specific. In addition, the diversity of PP1/PIP complexes can further be achieved by the existence of several PP1 isoforms that can bind preferentially to a certain PIP. Thus, PP1/PIP complexes are highly specific for a particular function in the cell, and as such, they are excellent pharmacological targets. Hence, an in-depth survey was taken to identify specific PP1α PIPs in human brain by a high-throughput Yeast Two-Hybrid approach. Sixty-six proteins were recognized to bind PP1α, 39 being novel PIPs. A large protein interaction databases search w...
TL;DR: It is revealed that the coordinated transcription and phospholipid composition changes contribute to the increased robustness of the T strain and highlight potential metabolic engineering targets for mutants with higher tolerance.
Abstract: A mixture of acetic acid, furfural, and phenol (AFP), three representative lignocellulose-derived inhibitors, significantly inhibited the growth and bioethanol production of Saccharomyces cerevisiae. In order to uncover the mechanisms behind the enhanced tolerance of an inhibitor-tolerant S. cerevisiae strain (T), we measured the plasma membrane properties, which significantly influence cellular adaptation to inhibitors, of T strain and its parental strain (P) with and without AFP treatment. We integrated data obtained from multi-statistics-assisted phospholipidomics and parallel transcriptomics by using LC–tandem MS and microarray analysis. With the AFP treatment, the transcriptional changes of fatty acid metabolic genes showed a strong correlation with the increase of fatty-acyl-chain length of phosphatidylcholine (PC) and phosphatidylinositol (PI). This suggests a possible compensatory mechanism to cope with the increase of plasma membrane permeability and fluidity in both strains. Moreover, t...
TL;DR: The hypothesis that curcumin is an interesting chemopreventive agent as it modulates the expression of proteins that potentially contribute to prostate carcinogenesis is supported.
Abstract: Due to high prevalence and slow progression of prostate cancer, primary prevention appears to be attractive strategy for its eradication. During the last decade, curcumin (diferuloylmethane), a natural compound from the root of turmeric (Curcuma longa), was described as a potent chemopreventive agent. Curcumin exhibits anti-inflammatory, anticarcinogenic, antiproliferative, antiangiogenic, and antioxidant properties in various cancer cell models. This study was designed to identify proteins involved in the anticancer activity of curcumin in androgen-dependent (22Rv1) and -independent (PC-3) human prostate cancer cell lines using two-dimensional difference in gel electrophoresis (2D-DIGE). Out of 425 differentially expressed spots, we describe here the MALDI-TOF-MS analysis of 192 spots of interest, selected by their expression profile. This approach allowed the identification of 60 differentially expressed proteins (32 in 22Rv1 cells and 47 in PC-3 cells). Nineteen proteins are regulated in both cell lines. Further bioinformatic analysis shows that proteins modulated by curcumin are implicated in protein folding (such as heat-shock protein PPP2R1A; RNA splicing proteins RBM17, DDX39; cell death proteins HMGB1 and NPM1; proteins involved in androgen receptor signaling, NPM1 and FKBP4/FKBP52), and that this compound could have an impact on miR-141, miR-152, and miR-183 expression. Taken together, these data support the hypothesis that curcumin is an interesting chemopreventive agent as it modulates the expression of proteins that potentially contribute to prostate carcinogenesis.
TL;DR: New biological challenges and opportunities for the application of new high-throughput genome, transcriptome, proteome, and metabolome analysis technologies in the development of efficient marker-assisted selection strategies in Prunus breeding include genome resequencing using DNA-Seq, the study of RNA regulation at transcriptional and posttranscriptional levels using tilling microarray and RNA-Sequ, protein and metabolite identification and annotation, and standardization of phenotype evaluation.
Abstract: The recent sequencing of the complete genome of the peach, together with the availability of new high-throughput genome, transcriptome, proteome, and metabolome analysis technologies, offers new possibilities for Prunus breeders in what has been described as the postgenomic era. In this context, new biological challenges and opportunities for the application of these technologies in the development of efficient marker-assisted selection strategies in Prunus breeding include genome resequencing using DNA-Seq, the study of RNA regulation at transcriptional and posttranscriptional levels using tilling microarray and RNA-Seq, protein and metabolite identification and annotation, and standardization of phenotype evaluation. Additional biological opportunities include the high level of synteny among Prunus genomes. Finally, the existence of biases presents another important biological challenge in attaining knowledge from these new high-throughput omics disciplines. On the other hand, from the philosop...
TL;DR: It is demonstrated that the urinary metabotype differs between obese patients and healthy controls, and the metabolic alterations identified after bariatric procedures increase knowledge about the metabolic traits associated with weight reduction.
Abstract: Bariatric surgery leads to a loss of excess weight and to a remission of diabetes in a majority of patients. In an attempt to explain these underlying mechanisms, a broad range of metabolic alterations have been suggested. We aimed to investigate short-term changes in the urinary metabolome after bariatric surgery. Data for 50 patients who underwent bariatric surgery at the Municipal Hospital of Dresden-Neustadt, Germany, were used. Healthy controls were selected from the Study of Health in Pomerania. Non-fasting, spontaneous urine samples were collected, (1)H NMR spectroscopic analysis was performed, and metabolites were quantified (Chenomx NMR suite). Orthogonal projections to latent structures discriminant analysis (OPLS-DA) models were carried out (pre-operative versus controls, and post-operative versus controls). On the basis of the urine metabolome separations between pre-operative (predictive ability Q2Y=85.6%; total explained variance R2X=58.3%), or post-operative (Q2Y=82.1%; R2X=44.4%) and controls were possible. Metabolites including hippuric acid, 3-hydroxybutyrate, 2-hydroxyisobutyrate, and trigonelline, were altered among patients. In obese patients, 2-hydroxyisobutyrate levels were higher, whereas trigonelline and hippuric acid levels were lower than in controls. The highest levels of 3-hydroxybutyrate were found in post-operative samples, whereas the metabolite was not present in controls, and only at low levels in pre-operative samples. In conclusion, we demonstrated that the urinary metabotype differs between obese patients and healthy controls. The metabolic alterations identified after bariatric procedures increase our knowledge about the metabolic traits associated with weight reduction. Whether urinary metabotypes might be used for early prediction of a successful bariatric procedure should be evaluated in long-term observations.
TL;DR: This work has tried to cover most pronounced recent developments in the field of "omics" related to abiotic stress tolerance of plants.
Abstract: Today, agriculture is facing a tremendous threat from the climate change menace. As human survival is dependent on a constant supply of food from plants as the primary producers, we must aware of the underlying molecular mechanisms that plants have acquired as a result of molecular evolution to cope this rapidly changing environment. This understanding will help us in designing programs aimed at developing crop plant cultivars best suited to our needs of a sustainable agriculture. The field of systems biology is rapidly progressing, and new insight is coming out about the molecular mechanisms involved in abiotic stress tolerance. There is a cascade of changes in transcriptome, proteome, and metabolome of plants during these stress responses. We have tried to cover most pronounced recent developments in the field of “omics” related to abiotic stress tolerance of plants. These changes are very coordinated, and often there is crosstalk between different components of stress tolerance. The functions ...
TL;DR: This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2 and the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences.
Abstract: Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the ...
TL;DR: Recent developments in analysis of plant metabolomics, available bioinformatics techniques and databases employed for comparative pathway analysis, metabolic QTLs, and their application in plants are reviewed.
Abstract: Metabolome refers to the complete set of metabolites synthesized through a series of multiple enzymatic steps from various biochemical pathways processing the information encrypted in the plant genome. Knowledge about synthesis and regulation of various plant metabolic substances has improved substantially with availability of Omics data originating from sequencing of plant genomes. Metabolic profiling of crops is increasingly becoming popular in assessing plant phenotypes and genetic diversity. Metabolic compositional changes vividly reflect the changes occurring during plant growth, development, and in response to stress. Hence, study of plant metabolic pathways, the interconnections between them in context of systems biology is increasingly becoming popular in identification of candidate genes. The present article reviews recent developments in analysis of plant metabolomics, available bioinformatics techniques and databases employed for comparative pathway analysis, metabolic QTLs, and their ...
TL;DR: This review aims to discuss recent knowledge about apoptotic signaling networks during odontogenesis, concentrating on the mouse, which is often used as a model organism for human dentistry.
Abstract: Apoptosis is an important morphogenetic event in embryogenesis as well as during postnatal life. In the last 2 decades, apoptosis in tooth development (odontogenesis) has been investigated with gradually increasing focus on the mechanisms and signaling pathways involved. The molecular machinery responsible for apoptosis exhibits a high degree of conservation but also organ and tissue specific patterns. This review aims to discuss recent knowledge about apoptotic signaling networks during odontogenesis, concentrating on the mouse, which is often used as a model organism for human dentistry. Apoptosis accompanies the entire development of the tooth and corresponding remodeling of the surrounding bony tissue. It is most evident in its role in the elimination of signaling centers within developing teeth, removal of vestigal tooth germs, and in odontoblast and ameloblast organization during tooth mineralization. Dental apoptosis is caspase dependent and proceeds via mitochondrial mediated cell death with possible amplification by Fas-FasL signaling modulated by Bcl-2 family members.
TL;DR: The aim of this work is to identify large and focal copy number abnormalities (CNA) and loss of heterozygosity (LOH) events in a malignant glioma population and hypothesized that these explorations will allow discovery of genetic markers that may improve diagnosis and predict outcome.
Abstract: Malignant gliomas are the most frequent type of primary brain tumors. Patients' outcome has not improved despite new therapeutics, thus underscoring the need for a better understanding of their genetics and a fresh approach to treatment. The lack of reproducibility in the classification of many gliomas presents an opportunity where genomics may be paramount for accurate diagnosis and therefore best for therapeutic decisions. The aim of this work is to identify large and focal copy number abnormalities (CNA) and loss of heterozygosity (LOH) events in a malignant glioma population. We hypothesized that these explorations will allow discovery of genetic markers that may improve diagnosis and predict outcome. DNA from glioma specimens were subjected to CNA and LOH analyses. Our studies revealed more than 4000 CNA and several LOH loci. Losses of chromosomes 1p and/or 19q, 10, 13, 14, and 22 and gains of 7, 19, and 20 were found. Several of these alterations correlated significantly with histology and ...
TL;DR: It is reported here that the serum levels of hemopexin, haptoglobin, serum amyloid P, and kininogen precursor, are altered in DF, which informs the pathogenesis and host immune response to dengue virus infection, as well as the current search for new diagnostic and molecular drug targets.
Abstract: The global burden of dengue continues to worsen, specifically in tropical and subtropical countries, and has evolved as a major public health problem. We investigated the changes in serum proteome in dengue fever (DF) patients from a dengue-endemic area of India to obtain mechanistic insights about the disease pathogenesis, the host immune response, and identification of potential serum protein biomarkers of this infectious disease. In this study, serum samples from DF patients, healthy subjects, and patients with falciparum malaria (an infectious disease control) were investigated by 2D-DIGE in combination with MALDI-TOF/TOF MS. The findings were validated with Western blotting. Functional clustering of the identified proteins was performed using PANTHER and DAVID tools. Compared to the healthy controls, we found significant changes in the expression levels of 48 protein spots corresponding to 18 unique proteins (7 downregulated and 11 upregulated) in DF patients (p<0.05). Among these differenti...