Unlike the digestive systems of vertebrate animals, the lumen of the alimentary canal of C. elegans is unsegmented and weakly acidic (pH ~ 4.4), with ultradian fluctuations to pH > 6 every 45 to 50 seconds. To probe the dynamics of this acidity, we synthesized novel acid-activated fluorophores termed Kansas Reds. These dicationic derivatives of rhodamine B become concentrated in the lumen of the intestine of living C. elegans and exhibit tunable pKa values (2.3–5.4), controlled by the extent of fluorination of an alkylamine substituent, that allow imaging of a range of acidic fluids in vivo. Fluorescence video microscopy of animals freely feeding on these fluorophores revealed that acidity in the C. elegans intestine is discontinuous; the posterior intestine contains a large acidic segment flanked by a smaller region of higher pH at the posterior-most end. Remarkably, during the defecation motor program, this hot spot of acidity rapidly moves from the posterior intestine to the anterior-most intestine where it becomes localized for up to 7 seconds every 45 to 50 seconds. Studies of pH-insensitive and base-activated fluorophores as well as mutant and transgenic animals revealed that this dynamic wave of acidity requires the proton exchanger PBO-4, does not involve substantial movement of fluid, and likely involves the sequential activation of proton transporters on the apical surface of intestinal cells. Lacking a specific organ that sequesters low pH, C. elegans compartmentalizes acidity by producing of a dynamic hot spot of protons that rhythmically migrates from the posterior to anterior intestine.

LipidomeDB Data Calculation Environment (DCE) is a web application to quantify complex lipids by processing data acquired after direct infusion of a lipid-containing biological extract, to which a cocktail of internal standards has been added, into an electrospray source of a triple quadrupole mass spectrometer. LipidomeDB DCE is located on the public Internet at http://lipidome.bcf.ku.edu:9000/Lipidomics. LipidomeDB DCE supports targeted analyses; analyte information can be entered, or pre-formulated lists of typical plant or animal polar lipid analytes can be selected. LipidomeDB DCE performs isotopic deconvolution and quantification in comparison to internal standard spectral peaks. Multiple precursor or neutral loss spectra from up to 35 samples may be processed simultaneously with data input as Excel files and output as tables viewable on the web and exportable in Excel. The pre-formulated compound lists and web access, used with direct-infusion mass spectrometry, provide a simple approach to lipidomic analysis, particularly for new users.

Plant phospholipids and glycolipids can be analyzed by direct infusion electrospray ionization triple-quadrupole mass spectrometry. A biological extract is introduced in solvent by continuous infusion into the mass spectrometer's electrospray ionization source, where ions are produced from the lipids. For analysis of membrane lipids, a series of precursor and neutral loss scans, each specific for lipids containing a common head group, are obtained sequentially. The mass spectral data are processed and combined, using the Web application LipidomeDB Data Calculation Environment, to create a lipid profile.

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OmicsMiner is a computational platform providing systematic access to state-of-the-art data processing and mining methods with the goal of facilitating the design of customized pipelines for processing a diverse range of biological data sets. Many built-in methods are provided for preprocessing, feature selection, clustering and classification of complex datasets. The platform supports convenient integration of additional algorithms that can further expand its functionality. OmicsMiner also provides convenient and concise interactive graphical user interfaces for data processing. OmicsMiner is a Java program that is platform-independent and does not require installation. It is available at http://www.bcf.ku.edu/ software.shtml Journal of Data Mining in Genomics & Proteomics J o u rn al of Da ta M in in g in Gen o m ic s & Proteom ic s