For proteomic analysis using tandem mass spectrometry, linear ion trap instruments provide unsurpassed sensitivity, but unreliably detect low mass peptide fragments, precluding their use with iTRAQ reagent labeled samples. While the popular LTQ linear ion trap supports analyzing iTRAQ reagent labeled peptides via pulsed Q dissociation, PQD, its effectiveness remains questionable. Using a standard mixture, we found careful tuning of relative collision energy necessary for fragmenting iTRAQ reagent labeled peptides, and increasing microscan acquisition and repeat count improves quantification, but identifies somewhat fewer peptides. We developed software to calculate abundance ratios via summing reporter ion intensities across spectra matching to each protein, thereby providing maximized accuracy. Testing found results closely corresponded between analysis using optimized LTQ-PQD settings plus our software and using a Qstar instrument. Thus, we demonstrate the effectiveness of LTQ-PQD analyzing iTRAQ reagent labeled peptides, and provide guidelines for successful quantitative proteomic studies.

Whole human saliva possesses tremendous potential in clinical diagnostics, particularly for conditions within the oral cavity such as oral cancer. Although many have studied the soluble fraction of whole saliva, few have taken advantage of the diagnostic potential of the cells present in saliva, and none have taken advantage of proteomics capabilities for their study. We report on a novel proteomics method with which we characterized for the first time cells contained in whole saliva from patients diagnosed with oral squamous cell carcinoma. Our method uses three dimensions of peptide fractionation, combining the following steps: preparative IEF using free flow electrophoresis, strong cation exchange step gradient chromatography, and microcapillary reverse-phase liquid chromatography. We determined that the whole saliva samples contained enough cells, mostly exfoliated epithelial cells, providing adequate amounts of total protein for proteomics analysis. From a mixture of four oral cancer patient samples, the analysis resulted in a catalogue of over 1000 human proteins, each identified from at least two peptides, including numerous proteins with a role in oral squamous cell carcinoma signaling and tumorigenesis pathways. Additionally proteins from over 30 different bacteria were identified, some of which putatively contribute to cancer development. The combination of preparative IEF followed by strong cation exchange chromatography effectively fractionated the complex peptide mixtures despite the closely related physiochemical peptide properties of these separations (pI and solution phase charge, respectively). Furthermore compared with our two-step method combining preparative IEF and reversephase liquid chromatography, our three-step method identified significantly more cellular proteins while retaining higher confidence protein identification enabled by peptide pI information gained through IEF. Thus, for detecting salivary markers of oral cancer and possibly other conditions of the oral cavity, the results confirm both the potential of analyzing the cells in whole saliva and doing so with our proteomics method. Molecular & Cellular Proteomics 7:486 -498, 2008.Whole human saliva is easily collected in the clinic in a non-invasive, on-demand manner and in relatively large, easily stored quantities, making it an optimal bodily fluid for clinical diagnostics (1, 2). Diagnosis of oral cancer could benefit greatly from the development of whole saliva-based clinical tests given the physical proximity of the site of cancer development with the diagnostic fluid. In fact, oral cancer, usually diagnosed in the form of oral squamous cell carcinoma (OSCC), 1 has not seen a drop in its 50% mortality rate over the last 30 years (3), motivating the development of new and reliable, saliva-based clinical diagnostic tests for the early detection of OSCC. Such tests would lead to more informed treatment of patients and a reduction in the suffering and death caused by this cancer.To develop these tests, molecular markers that ar...

Studies of neuronal differentiation in vitro often involve tracing and analysis of neurites. NeuronJ (Meijering et al., Cytometry Part A 2004;58A:167-176; http://www. imagescience.org/meijering/software/neuronj/) is a program that can be used for semiautomated tracing of individual neurons; when tracing is completed, a text file containing neurite length measurements is generated. Using cultured hippocampal neurons, we have found that to reach statistical significance it is generally necessary to trace about 100 neurons in each treatment group. Posttracing data analysis requires importing each text file into a statistics program. Analysis of distinct parameters, such as effects of a treatment on axonal versus dendritic branching, requires a great deal of time consuming posttracing data manipulation. We have developed XL_Calculations, a Java-based program that performs batch analysis on NeuronJ measurement files and automatically makes multiple calculations, including the number, length, and total output (sum length) of primary, secondary, and tertiary neurites on axons and dendrites, and writes the calculations into an Excel worksheet. Batch processing of NeuronJ measurement files dramatically reduces the time required to analyze neuronal morphology. In addition, our program performs more than 45 distinct calculations, enabling detailed determination of treatment effects on neuronal differentiation. Using this program to analyze NeuronJ tracing data, we demonstrate that continuous exposure of differentiating hippocampal neurons to Netrin 1 increases the number of secondary branches on both axons and dendrites, without significantly altering the length of the axon, dendrites, or branches. Similar results were obtained when neurons were grown on poly-D-lysine or laminin. '