About us

 

The main goal of the Lipidomics facility at Texas A&M University Health Sciences Center (TAMHSC) is to maintain a targeted analytical platform for qualitative and quantitative Lipidomics, focused on developing comprehensive analytical approaches that can be exploited by  basic scientists, clinicians, and veterinarians alike. Another goal focuses on select biomarker phospholipids whose quantification in cells and tissues (including clinical and veterinary samples) are of great interest from both basic science and clinical outcome perspectives. This facility fosters translational interactions between Veterinary Medicine, Plant/Agricultural Research, Nutrition, Reproductive Biology, the College of Medicine, and others; and interfaces general biomedical research (on healthy and diseased states) with the analytical chemistry and the advanced Mass Spectrometry expertise already housed in the ILSB, the Department of Chemistry, the department of Biochemistry and Biophysics, and the school of veterinary medicine.The integration of analytical chemistry with biological and medical contexts and with computational/informatics power seeks to forge strong links between the various TAMU units, as well as regional Medical Centers (including TAMHSC Temple Campus, IBT, Texas Medical Center, among many others).This structure also provides downstream opportunities for launching ‘systems modeling’ of organ function, such as lung function, pancreatic islet biology, and tumor biology to mention a few.

This facility is implemented at a time when lipid metabolism and lipid signaling are being recognized as key nodes of regulation in cells, and nodes of derangement in disease. The capability to measure properly key lipid biomarkers should draw both basic science and clinical (i.e. translational) interest.

AIMS

  • To perform qualitative and quantitative measurements of phospholipids (and their corresponding molecular species) using shotgun lipidomics. Shotgun lipidomicsis a versatile platform usefult to determine the standard phospholipids, and species such as lyso-phosphatidic acid (a biomarker for ovarian cancer and other disorders) and cardiolipin (a mitochondrial-specific phospholipid that is useful in reporting mitochondrial status).
  • Quantification of Phosphatidylinositol-3,4,5-P3 (PIP3). We strive todevelope/improve existing methods for quantifying PtdIns 3-OH kinase signaling. It is already known that many tumors are ‘addicted’ to PtdIns 3-OH kinase activity, and the PTEN PIP3 phosphatase is the second most frequently mutated gene in cancer, PtdIns 3-OH kinase signaling is also a key player in insulin signaling and diabetes. Suggesting that a platform dedicated to these measurements is of general interest to the clinical communisty.From a clinical perspective, this should be a particular useful capability in monitoring treatment efficacies in real time.
  • Quantification of Other Phosphoinositides. Development of a reliable quantification platforms for phosphoinositides in general is enormously useful for the scientific community — including plant biologists (esp those interested in drought resistance and osmotic stress), clinicians, nutrition scientists, etc. These measurements could be achieved by non-MS means, in particular, by quantification of phosphoinositides from their deacylated derivatives using suppressed conductivity methods.

The TAMHSC Lipidomics Facility

  • 1. Sample preparations
    • 1.1. From Yeast
    • 1.2. From Human samples
    • 1.3. From bacteria
    • 1.4. From Plants
  • 2. Fractionation
    • 2.1. HPLC
    • 2.2. Acid/base exchanges
    • 2.3. Organic phase
  • 3. Quality control
    • 3.1. HPLC
    • 3.2. TLC
  • 4. Identification and/or characterization
    • 4.1. MS
      • 4.1.1. LC-MS
      • 4.1.2. Shotgun MS
      • 4.1.3. MALDI
      • 4.1.4. TLC-Maldi
      • 4.1.5. Lipid based Maldi-imaging
      • 4.1.6. GC-MS
    • 4.2. LC
      • 4.2.1. Suppressed conductivity
      • 4.2.2. SCX & SIX
      • 4.2.3. Affinity chromatography
    • 4.3. NMR
      • 4.3.1. Solution NMR
      • 4.3.2. Solid state NMR
    • 4.4. Nanotechnology
      • 4.4.1. Nanostructured surfaces
  • 5. Data management
    • 5.1. Data Analysis
      • 5.1.2. LipidXplorer
      • 5.1.3. Limsa
      • 5.1.4. ALEX
      • 5.1.5. SimLipid
      • 5.1.6. LipidAt
    • 5.2. Databases (include: exact mass, fragmentation patterns, HPLC elution characteristics)
      • 5.2.1. Lipid maps
    • 5.3. Bioinformatics
  • 6. Applications