David P. De Souza

SOCS-6 Binds to Insulin Receptor Substrate 4, and Mice Lacking the SOCS-6 Gene Exhibit Mild Growth Retardation

ABSTRACT SOCS-6 is a member of the suppressor of cytokine signaling (SOCS) family of proteins (SOCS-1 to SOCS-7 and CIS) which each contain a central SH2 domain and a carboxyl-terminal SOCS box. SOCS-1, SOCS-2, SOCS-3, and CIS act to negatively regulate cytokine-induced signaling pathways; however, the actions of SOCS-4, SOCS-5, SOCS-6, and SOCS-7 remain less clear. Here we have used both biochemical and genetic approaches to examine the action of SOCS-6. We found that SOCS-6 and SOCS-7 are expressed ubiquitously in murine tissues. Like other SOCS family members, SOCS-6 binds to elongins B and C through its SOCS box, suggesting that it might act as an E3 ubiquitin ligase that targets proteins bound to its SH2 domain for ubiquitination and proteasomal degradation. We investigated the binding specificity of the SOCS-6 and SOCS-7 SH2 domains and found that they preferentially bound to phosphopeptides containing a valine in the phosphotyrosine (pY) +1 position and a hydrophobic residue in the pY +2 and pY +3 positions. In addition, these SH2 domains interacted with a protein complex consisting of insulin receptor substrate 4 (IRS-4), IRS-2, and the p85 regulatory subunit of phosphatidylinositol 3-kinase. To investigate the physiological role of SOCS-6, we generated mice lacking the SOCS-6 gene. SOCS-6−/− mice were born in a normal Mendelian ratio, were fertile, developed normally, and did not exhibit defects in hematopoiesis or glucose homeostasis. However, both male and female SOCS-6−/− mice weighed approximately 10% less than wild-type littermates.

Normalizing and integrating metabolomics data.

Metabolomics research often requires the use of multiple analytical platforms, batches of samples, and laboratories, any of which can introduce a component of unwanted variation. In addition, every experiment is subject to within-platform and other experimental variation, which often includes unwanted biological variation. Such variation must be removed in order to focus on the biological information of interest. We present a broadly applicable method for the removal of unwanted variation arising from various sources for the identification of differentially abundant metabolites and, hence, for the systematic integration of data on the same quantities from different sources. We illustrate the versatility and the performance of the approach in four applications, and we show that it has several advantages over the existing normalization methods.

Profiling of polar metabolites in biological extracts using diamond hydride-based aqueous normal phase chromatography

Highly polar metabolites, such as sugars and most amino acids are not retained by conventional RP LC columns. Without sufficient retention low concentration compounds are not detected due ion suppression and structural isomers are not resolved. In contrast, hydrophilic interaction chromatography (HILIC) and aqueous normal phase chromatography (ANP) retain compounds based on their hydrophilicity and therefore provides a means of separating highly polar compounds. Here, an ANP method based on the diamond hydride stationary phase is presented for profiling biological small molecules by LC. A rapid separation system based upon a fast gradient that delivers reproducible chromatography is presented. Approximately 1000 compounds were reproducibly detected in human urine samples and clear differences between these samples were identified. This chromatography was also applied to xylem fluid from soyabean (Glycine max) plants to which 400 compounds were detected. This method greatly increases the metabolite coverage over RP-only metabolite profiling in biological samples. We show that both forms of chromatography are necessary for untargeted comprehensive metabolite profiling and that the diamond hydride stationary phase provides a good option for polar metabolite analysis.

Central carbon metabolism of Leishmania parasites.

Leishmania spp. are sandfly-transmitted protozoa parasites that cause a spectrum of diseases in humans. Many enzymes involved in Leishmania central carbon metabolism differ from their equivalents in the mammalian host and are potential drug targets. In this review we summarize recent advances in our understanding of Leishmania central carbon metabolism, focusing on pathways of carbon utilization that are required for growth and pathogenesis in the mammalian host. While Leishmania central carbon metabolism shares many features in common with other pathogenic trypanosomatids, significant differences are also apparent. Leishmania parasites are also unusual in constitutively expressing most core metabolic pathways throughout their life cycle, a feature that may allow these parasites to exploit a range of different carbon sources (primarily sugars and amino acids) rapidly in both the insect vector and vertebrate host. Indeed, recent gene deletion studies suggest that mammal-infective stages are dependent on multiple carbon sources in vivo. The application of metabolomic approaches, outlined here, are likely to be important in defining aspects of central carbon metabolism that are essential at different stages of mammalian host infection.

A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments.

BackgroundGas chromatography-mass spectrometry (GC-MS) is a robust platform for the profiling of certain classes of small molecules in biological samples. When multiple samples are profiled, including replicates of the same sample and/or different sample states, one needs to account for retention time drifts between experiments. This can be achieved either by the alignment of chromatographic profiles prior to peak detection, or by matching signal peaks after they have been extracted from chromatogram data matrices. Automated retention time correction is particularly important in non-targeted profiling studies.ResultsA new approach for matching signal peaks based on dynamic programming is presented. The proposed approach relies on both peak retention times and mass spectra. The alignment of more than two peak lists involves three steps: (1) all possible pairs of peak lists are aligned, and similarity of each pair of peak lists is estimated; (2) the guide tree is built based on the similarity between the peak lists; (3) peak lists are progressively aligned starting with the two most similar peak lists, following the guide tree until all peak lists are exhausted. When two or more experiments are performed on different sample states and each consisting of multiple replicates, peak lists within each set of replicate experiments are aligned first (within-state alignment), and subsequently the resulting alignments are aligned themselves (between-state alignment). When more than two sets of replicate experiments are present, the between-state alignment also employs the guide tree. We demonstrate the usefulness of this approach on GC-MS metabolic profiling experiments acquired on wild-type and mutant Leishmania mexicana parasites.ConclusionWe propose a progressive method to match signal peaks across multiple GC-MS experiments based on dynamic programming. A sensitive peak similarity function is proposed to balance peak retention time and peak mass spectra similarities. This approach can produce the optimal alignment between an arbitrary number of peak lists, and models explicitly within-state and between-state peak alignment. The accuracy of the proposed method was close to the accuracy of manually-curated peak matching, which required tens of man-hours for the analyzed data sets. The proposed approach may offer significant advantages for processing of high-throughput metabolomics data, especially when large numbers of experimental replicates and multiple sample states are analyzed.

Specific plasma lipid classes and phospholipid fatty acids indicative of dairy food consumption associate with insulin sensitivity

BACKGROUND Reports have suggested that the consumption of dairy foods may reduce risk of type 2 diabetes on the basis of evidence of raised circulating ruminant fatty acids. OBJECTIVE We determined whether certain phospholipid species and fatty acids that are associated with full-fat dairy consumption may also be linked to diminished insulin resistance. DESIGN Four variables of insulin resistance and sensitivity were defined from oral-glucose-tolerance tests in 86 overweight and obese subjects with metabolic syndrome. Plasma phospholipids, sphingolipids, and fatty acids were determined by using a lipidomic analysis and gas chromatography-mass spectrometry to provide objective markers of dairy consumption. Food records provided information on dairy products. Associations were determined by using linear regression analyses adjusted for potential confounders age, sex, systolic blood pressure, waist:hip ratio, or body mass index (BMI) and corrected for multiple comparisons. RESULTS Lysophosphatidylcholine, lyso-platelet-activating factor, and several phospholipid fatty acids correlated directly with the number of servings of full-fat dairy foods. Lysophosphatidylcholine and lyso-platelet-activating factor were also associated directly with insulin sensitivity when accounting for the waist:hip ratio (Matsuda index unadjusted, P < 0.001 for both; adjusted for multiple comparisons, P < 0.02 for both) and inversely with insulin resistance (fasting insulin unadjusted, P < 0.001 for both; adjusted, P = 0.04 and P < 0.05, respectively; homeostasis model assessment of insulin resistance adjusted, P = 0.04 for both; post-glucose insulin area under the plasma insulin curve during the 120 min of the test adjusted, P < 0.01 for both). The substitution of BMI for the waist:hip ratio attenuated associations modestly. Phospholipid fatty acid 17:0 also tended to be associated directly with insulin sensitivity and inversely with resistance. CONCLUSION Variables of insulin resistance were lower at higher concentrations of specific plasma phospholipids that were also indicators of full-fat dairy consumption. This trial was registered at clinicaltrials.gov as NCT00163943.

LeishCyc: a biochemical pathways database for Leishmania major

BackgroundLeishmania spp. are sandfly transmitted protozoan parasites that cause a spectrum of diseases in more than 12 million people worldwide. Much research is now focusing on how these parasites adapt to the distinct nutrient environments they encounter in the digestive tract of the sandfly vector and the phagolysosome compartment of mammalian macrophages. While data mining and annotation of the genomes of three Leishmania species has provided an initial inventory of predicted metabolic components and associated pathways, resources for integrating this information into metabolic networks and incorporating data from transcript, protein, and metabolite profiling studies is currently lacking. The development of a reliable, expertly curated, and widely available model of Leishmania metabolic networks is required to facilitate systems analysis, as well as discovery and prioritization of new drug targets for this important human pathogen.DescriptionThe LeishCyc database was initially built from the genome sequence of Leishmania major (v5.2), based on the annotation published by the Wellcome Trust Sanger Institute. LeishCyc was manually curated to remove errors, correct automated predictions, and add information from the literature. The ongoing curation is based on public sources, literature searches, and our own experimental and bioinformatics studies. In a number of instances we have improved on the original genome annotation, and, in some ambiguous cases, collected relevant information from the literature in order to help clarify gene or protein annotation in the future. All genes in LeishCyc are linked to the corresponding entry in GeneDB (Wellcome Trust Sanger Institute).ConclusionThe LeishCyc database describes Leishmania major genes, gene products, metabolites, their relationships and biochemical organization into metabolic pathways. LeishCyc provides a systematic approach to organizing the evolving information about Leishmania biochemical networks and is a tool for analysis, interpretation, and visualization of Leishmania Omics data (transcriptomics, proteomics, metabolomics) in the context of metabolic pathways. LeishCyc is the first such database for the Trypanosomatidae family, which includes a number of other important human parasites. Flexible query/visualization capabilities are provided by the Pathway Tools software and its Web interface. The LeishCyc database is made freely available over the Internet http://www.leishcyc.org.

PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools

BackgroundGas chromatography–mass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data tightly integrate data processing methods with graphical user interface facilitating interactive data processing. While interactive processing remains critically important in GC-MS applications, high-throughput studies increasingly dictate the need for command line tools, suitable for scripting of high-throughput, customized processing pipelines.ResultsPyMS comprises a library of functions for processing of instrument GC-MS data developed in Python. PyMS currently provides a complete set of GC-MS processing functions, including reading of standard data formats (ANDI- MS/NetCDF and JCAMP-DX), noise smoothing, baseline correction, peak detection, peak deconvolution, peak integration, and peak alignment by dynamic programming. A novel common ion single quantitation algorithm allows automated, accurate quantitation of GC-MS electron impact (EI) fragmentation spectra when a large number of experiments are being analyzed. PyMS implements parallel processing for by-row and by-column data processing tasks based on Message Passing Interface (MPI), allowing processing to scale on multiple CPUs in distributed computing environments. A set of specifically designed experiments was performed in-house and used to comparatively evaluate the performance of PyMS and three widely used software packages for GC-MS data processing (AMDIS, AnalyzerPro, and XCMS).ConclusionsPyMS is a novel software package for the processing of raw GC-MS data, particularly suitable for scripting of customized processing pipelines and for data processing in batch mode. PyMS provides limited graphical capabilities and can be used both for routine data processing and interactive/exploratory data analysis. In real-life GC-MS data processing scenarios PyMS performs as well or better than leading software packages. We demonstrate data processing scenarios simple to implement in PyMS, yet difficult to achieve with many conventional GC-MS data processing software. Automated sample processing and quantitation with PyMS can provide substantial time savings compared to more traditional interactive software systems that tightly integrate data processing with the graphical user interface.

A fusion protein system for the recombinant production of short disulfide-containing peptides

A recombinant fusion protein system for the production, oxidation, and purification of short peptides containing a single disulfide bond is described. The peptides are initially expressed in Escherichia coli as a fusion to an engineered mutant of the N-terminal SH2 domain of the intracellular phosphatase, SHP-2. This small protein domain confers several important properties which facilitate the production of disulfide-containing peptides: (i) it is expressed at high levels in E. coli; (ii) it can be purified via a hexahistidine tag and reverse-phase HPLC; (iii) it contains no endogenous cysteine residues, allowing the formation of an intrapeptide disulfide bond while still attached to the fusion partner; (iv) it is highly soluble in native buffers, facilitating the production of very hydrophobic peptides and the direct use of fusion products in biochemical assays; (v) it contains a unique methionine residue at the junction of the peptide and fusion partner to facilitate peptide cleavage by treatment with cyanogen bromide (CNBr). This method is useful for producing peptides, which are otherwise difficult to prepare through traditional chemical synthesis approaches, and this has been demonstrated by preparing a number of hydrophobic disulfide-containing peptides derived from phage-display libraries.

Host reticulocytes provide metabolic reservoirs that can be exploited by malaria parasites.

Human malaria parasites proliferate in different erythroid cell types during infection. Whilst Plasmodium vivax exhibits a strong preference for immature reticulocytes, the more pathogenic P. falciparum primarily infects mature erythrocytes. In order to assess if these two cell types offer different growth conditions and relate them to parasite preference, we compared the metabolomes of human and rodent reticulocytes with those of their mature erythrocyte counterparts. Reticulocytes were found to have a more complex, enriched metabolic profile than mature erythrocytes and a higher level of metabolic overlap between reticulocyte resident parasite stages and their host cell. This redundancy was assessed by generating a panel of mutants of the rodent malaria parasite P. berghei with defects in intermediary carbon metabolism (ICM) and pyrimidine biosynthesis known to be important for P. falciparum growth and survival in vitro in mature erythrocytes. P. berghei ICM mutants (pbpepc-, phosphoenolpyruvate carboxylase and pbmdh-, malate dehydrogenase) multiplied in reticulocytes and committed to sexual development like wild type parasites. However, P. berghei pyrimidine biosynthesis mutants (pboprt-, orotate phosphoribosyltransferase and pbompdc-, orotidine 5′-monophosphate decarboxylase) were restricted to growth in the youngest forms of reticulocytes and had a severe slow growth phenotype in part resulting from reduced merozoite production. The pbpepc-, pboprt- and pbompdc- mutants retained virulence in mice implying that malaria parasites can partially salvage pyrimidines but failed to complete differentiation to various stages in mosquitoes. These findings suggest that species-specific differences in Plasmodium host cell tropism result in marked differences in the necessity for parasite intrinsic metabolism. These data have implications for drug design when targeting mature erythrocyte or reticulocyte resident parasites.