Aquaculture of Triploid Crassostrea ariakensis in the Chesapeake Bay A Symposium Report

A Symposium Held at the College of William and Mary, Williamsburg, Virginia October 18-19, 200

Integration of lipidomics and transcriptomics data towards a systems biology model of sphingolipid metabolism

<p>Abstract</p> <p>Background</p> <p>Sphingolipids play important roles in cell structure and function as well as in the pathophysiology of many diseases. Many of the intermediates of sphingolipid biosynthesis are highly bioactive and sometimes have antagonistic activities, for example, ceramide promotes apoptosis whereas sphingosine-1-phosphate can inhibit apoptosis and induce cell growth; therefore, quantification of the metabolites and modeling of the sphingolipid network is imperative for an understanding of sphingolipid biology.</p> <p>Results</p> <p>In this direction, the LIPID MAPS Consortium is developing methods to quantitate the sphingolipid metabolites in mammalian cells and is investigating their application to studies of the activation of the RAW264.7 macrophage cell by a chemically defined endotoxin, Kdo₂-Lipid A. Herein, we describe a model for the C₁₆-branch of sphingolipid metabolism (i.e., for ceramides with palmitate as the N-acyl-linked fatty acid, which is selected because it is a major subspecies for all categories of complex sphingolipids in RAW264.7 cells) integrating lipidomics and transcriptomics data and using a two-step matrix-based approach to estimate the rate constants from experimental data. The rate constants obtained from the first step are further refined using generalized constrained nonlinear optimization. The resulting model fits the experimental data for all species. The robustness of the model is validated through parametric sensitivity analysis.</p> <p>Conclusions</p> <p>A quantitative model of the sphigolipid pathway is developed by integrating metabolomics and transcriptomics data with legacy knowledge. The model could be used to design experimental studies of how genetic and pharmacological perturbations alter the flux through this important lipid biosynthetic pathway.</p

Atmospheric sampling of Supertyphoon Mireille with NASA DC-8 aircraft on September 27,1991, during PEM-West A

The DC-8 mission of September 27, 1991, was designed to sample air flowing into Typhoon Mireille in the boundary layer, air in the upper tropospheric eye region, and air emerging from the typhoon and ahead of the system, also in the upper troposphere. The objective was to find how a typhoon redistributes trace constituents in the West Pacific region and whether any such redistribution is important on the global scale. The boundary layer air (300 m), in a region to the SE of the eye, contained low mixing ratios of the tracer species O3, CO, C2H6, C2H2, C3H8, C6H6and CS2 but high values of dimethylsulfide (DMS). The eye region relative to the boundary layer, showed somewhat elevated levels of CO, substantially increased levels of O3, CS2 and all nonmethane hydrocarbons (NMHCs), and somewhat reduced levels of DMS. Ahead of the eye, CO and the NMHCs remained unchanged, O3 and CS2 showed a modest decrease, and DMS showed a substantial decrease. There was no evidence from lidar cross sections of ozone for the downward entrainment of stratospheric air into the eye region; these sections show that low ozone values were measured in the troposphere. The DMS data suggest substantial entrainment of boundary layer air into the system, particularly into the eye wall region. Estimates of the DMS sulphur flux between the boundary layer and the free troposphere, based on computations of velocity potential and divergent winds, gave values of about 69 μg S m−2 d−1 averaged over a 17.5° grid square encompassing the typhoon. A few hours after sampling with the DC-8, Mireille passed over Oki Island, just to the north of Japan, producing surface values of ozone of 5.5 ppbv. These O3 levels are consistent with the low tropospheric values found by lidar and are more typical of equatorial regions. We suggest that the central eye region may act like a Taylor column which has moved poleward from low latitudes. The high-altitude photochemical environment within Typhoon Mireille was found to be quite active as evidenced by significant levels of measured gas phase H2O2 and CH3OOH and model-computed levels of OH

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials (“standards”), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for “standards-free” identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials (“standards”), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for “standards-free” identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples

An Introduction to Sphingolipid Metabolism and Analysis by New Technologies

Sphingolipids (SP) are a complex class of molecules found in essentially all eukaryotes and some prokaryotes and viruses where they influence membrane structure, intracellular signaling, and interactions with the extracellular environment. Because of the combinatorial nature of their biosynthesis, there are thousands of SP subspecies varying in the lipid backbones and complex phospho- and glycoheadgroups. Therefore, comprehensive or “sphingolipidomic” analyses (structure-specific, quantitative analyses of all SP, or at least all members of a critical subset) are needed to know which and how much of these subspecies are present in a system as a step toward understanding their functions. Mass spectrometry and related novel techniques are able to quantify a small fraction, but nonetheless a substantial number, of SP and are beginning to provide information about their localization. This review summarizes the basic metabolism of SP and state-of-art mass spectrometric techniques that are producing insights into SP structure, metabolism, functions, and some of the dysfunctions of relevance to neuromedicine

Predictors of Hospitalization for Injection Drug Users Seeking Care for Soft Tissue Infections

BACKGROUND: Soft tissue infections (STIs) from injection drug use are a common cause of Emergency Department visits, hospitalizations, and operating room procedures, yet little is known about factors that may predict the need for these costly medical services. OBJECTIVE: To describe a cohort of injection drug users seeking Emergency Department care for STIs and to identify risk factors associated with hospitalization. We hypothesized that participants who delayed seeking care would be hospitalized more often than those who did not. DESIGN: Cohort study using in-person structured interviews and medical record review. Logistic regression assessed the association between hospital admission and delay in seeking care as well as other demographic, clinical, and psychosocial factors. PARTICIPANTS: Injection drug users who sought Emergency Department care for STIs from May 2001 to March 2002. RESULTS: Of the 136 participants, 55 (40%) were admitted to the hospital. Delay in seeking care was not associated with hospital admission. Participants admitted for their infection were significantly more likely to be living in a shelter (P = .01) and to report being hospitalized 2 or more times in the past year (P < .01). CONCLUSIONS: We identified a subpopulation of injection drug users, mostly living in shelters, who were hospitalized frequently in the past year and who were more likely to be hospitalized for their current infections compared to others. As members of this subpopulation can be easily identified and located, they may benefit from interventions to reduce the health care utilization resulting from these infections

Diagnostic reliability of magnetic resonance imaging for central nervous system syndromes in systemic lupus erythematosus: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Previous studies of magnetic resonance imaging (MRI) as a diagnostic tool for central nervous system (CNS) syndromes in systemic lupus erythematosus (SLE) contained several limitations such as study design, number of enrolled patients, and definition of CNS syndromes. We overcame these problems and statistically evaluated the diagnostic values of abnormal MRI signals and their chronological changes in CNS syndromes of SLE.</p> <p>Methods</p> <p>We prospectively studied 191 patients with SLE, comparing those with (n = 57) and without (n = 134) CNS syndrome. CNS syndromes were characterized using the American College of Rheumatology case definitions.</p> <p>Results</p> <p>Any abnormal MRI signals were more frequently observed in subjects in the CNS group (n = 25) than in the non-CNS group (n = 32) [relative risk (RR), 1.7; 95% confidence interval (CI), 1.1-2.7; <it>p </it>= 0.016] and the positive and negative predictive values for the diagnosis of CNS syndrome were 42% and 76%, respectively. Large abnormal MRI signals (ø ≥ 10 mm) were seen only in the CNS group (n = 7; RR, 3.7; CI, 2.9-4.7; <it>p </it>= 0.0002), whereas small abnormal MRI signals (ø < 10 mm) were seen in both groups with no statistical difference. Large signals always paralleled clinical outcome (<it>p </it>= 0.029), whereas small signals did not (<it>p </it>= 1.000).</p> <p>Conclusions</p> <p>Abnormal MRI signals, which showed statistical associations with CNS syndrome, had insufficient diagnostic values. A large MRI signal was, however, useful as a diagnostic and surrogate marker for CNS syndrome of SLE, although it was less common.</p

Identification of aberrant forms of alkaline sphingomyelinase (NPP7) associated with human liver tumorigenesis

Alkaline sphingomyelinase (alk-SMase) is expressed in the intestine and human liver. It may inhibit colonic tumorigenesis, and loss of function mutations have been identified in human colon cancer. The present study investigates its expression in human liver cancer. In HepG2 liver cancer cells, RT–PCR identified three transcripts with 1.4, 1.2 and 0.4 kb, respectively. The 1.4 kb form is the wild-type cDNA with five translated exons, the 1.2 kb product lacks exon 4 and the 0.4 kb form is a combination of exons 1 and 5. Genomic sequence showed that these aberrant transcripts were products of alternative splicing. Transient expression of the 1.2 kb form showed no alk-SMase activity. In HepG2 cells, the alk-SMase activity is low in monolayer condition and increased with cell polarisation. Coexistence of 1.4 and 1.2 kb forms was also identified in one hepatoma biopsy. GenBank search identified a cDNA clone from human liver tumour, which codes a protein containing full length of alk-SMase plus a 73-amino-acid tag at the N terminus. The aberrant form was translated by an alternative starting codon upstream of the wild-type mRNA. Expression study showed that linking the tag markedly reduced the enzyme activity. We also analysed human liver biopsy samples and found relatively low alk-SMase activity in diseases with increased risk of liver tumorigenesis. In conclusion, expression of alk-SMase is changed in hepatic tumorigenesis, resulting in loss or marked reduction of the enzyme function