Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For this, we generate synthetic metabolic profiles for benchmarking purposes based on a well-established model for red blood cell metabolism. A variety of data sets is generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We apply ARACNE, a mainstream transcriptional networks reverse engineering algorithm, to these data sets and observe performance comparable to that obtained in the transcriptional domain, for which the algorithm was originally designed.Comment: 14 pages, 3 figures. Presented at the DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 200

Reverse-Polarity Activity-Based Protein Profiling

Reverse-polarity activity-based protein profiling (RP-ABPP) is a chemical proteomics approach that uses clickable, nucleophilic hydrazine probes to capture and identify protein-bound electrophiles in cells. The RP-ABPP approach is used to characterize the structure and function of reactive electrophilic PTMs and the proteins that harbor them, which may uncover unknown or novel functions of proteins in an endogenous setting. RP-ABPP has demonstrated utility as a versatile method to monitor metabolic regulation of electrophilic cofactors, as was done with the pyruvoyl cofactor in S-adenosyl-L- methionine decarboxylase (AMD1) and discover novel types of electrophilic modifications on proteins in human cells, as was done with the glyoxylyl modification on secernin-3 (SCRN3). These cofactors cannot be predicted by sequence and as such this area is relatively undeveloped. RP-ABPP is the only global unbiased approach to discover these electrophiles. Here, the utility of these experiments is described and a detailed protocol is provided for de novo discovery, quantitation, and global profiling of electrophilic functionality of proteins through the use of nitrogenous nucleophilic probes deployed directly to living cells in culture

Optimized Analytical Procedures for the Untargeted Metabolomic Profiling of Human Urine and Plasma by Combining Hydrophilic Interaction (HILIC) and Reverse-Phase Liquid Chromatography (RPLC)-Mass Spectrometry.

Profiling of body fluids is crucial for monitoring and discovering metabolic markers of health and disease and for providing insights into human physiology. Since human urine and plasma each contain an extreme diversity of metabolites, a single liquid chromatographic system when coupled to mass spectrometry (MS) is not sufficient to achieve reasonable metabolome coverage. Hydrophilic interaction liquid chromatography (HILIC) offers complementary information to reverse-phase liquid chromatography (RPLC) by retaining polar metabolites. With the objective of finding the optimal combined chromatographic solution to profile urine and plasma, we systematically investigated the performance of five HILIC columns with different chemistries operated at three different pH (acidic, neutral, basic) and five C18-silica RPLC columns. The zwitterionic column ZIC-HILIC operated at neutral pH provided optimal performance on a large set of hydrophilic metabolites. The RPLC columns Hypersil GOLD and Zorbax SB aq were proven to be best suited for the metabolic profiling of urine and plasma, respectively. Importantly, the optimized HILIC-MS method showed excellent intrabatch peak area reproducibility (CV < 12%) and good long-term interbatch (40 days) peak area reproducibility (CV < 22%) that were similar to those of RPLC-MS procedures. Finally, combining the optimal HILIC- and RPLC-MS approaches greatly expanded metabolome coverage with 44% and 108% new metabolic features detected compared with RPLC-MS alone for urine and plasma, respectively. The proposed combined LC-MS approaches improve the comprehensiveness of global metabolic profiling of body fluids and thus are valuable for monitoring and discovering metabolic changes associated with health and disease in clinical research studies

Downregulation of plasma MiR-142-3p and MiR-26a-5p in patients with colorectal carcinoma

Background: Colorectal cancer is one of the most commonly diagnosed cancers and cancer- related death worldwide. Identification of new specific biomarkers could be helpful to detection of this malignancy. Altered plasma microRNA expression has been identified in many cancers, including colorectal cancer. Objectives: The main objective of this study was to identify the circulating microRNAs with the most expression changes in colorectal cancer patients compared with neoplasm free healthy individuals. Materials and Methods: MicroRNA expression profiling was performed on plasma samples of 37 colorectal cancer patients and 8 normal subjects using microRNA microarray. Quantitative real-time reverse transcription polymerase chain reaction was used to validate the two selected altered microR NAs. Plasma samples from 61 colorectal cancer patients and 24 normal subjects were used in our validation study. Results: In profiling study we found a panel of six plasma microRNAs with significant downregulation. MicroRNA-142-3p and microRNA-26a-5p were selected and validated by polymerase chain reaction. Our results demonstrated that expression levels of plasma microRNA-142-3p and microRNA-26a-5p were significantly downregulated in patients with colorectal cancer when compared to control group. Conclusions: Our findings suggest that downregulation of plasma microRNA-142-3p and microRNA-26a-5p might serve as novel noninvasive biomarkers in the diagnosis of colorectal cancer, although more studies are needed to highlight the theoretical strengths. © 2015, Iranian Journal of Cancer Prevention