Biomedical subjects

Qiangwei Xia

Publications and source records attributed to Qiangwei Xia.

5 recordsLinked to original sources

PubMed2006

Comparison of spectral counting and metabolic stable isotope labeling for use with quantitative microbial proteomics.

Spectral counting, a promising method for quantifying relative changes in protein abundance in mass spectrometry-based proteomic analysis, was compared to metabolic stable isotope labeling using (15)N/(14)N "heavy/light" peptide pairs. The data were drawn primarily from a Methanococcus maripaludis experiment comparing a wild-type strain with a mutant deficient in a key enzyme relevant to energy metabolism. The dataset contained both proteome and transcriptome measurements. The normalization technique used previously for the isotopic measurements was inappropriate for spectral counting, but a simple adjustment for sampling frequency was sufficient for normalization. This adjustment was satisfactory both for M. maripaludis, an organism that showed relatively little expression change between the wild-type and mutant strains, and Porphyromonas gingivalis, an intracellular pathogen that has demonstrated widespread changes between intracellular and extracellular conditions. Spectral counting showed lower overall sensitivity defined in terms of detecting a two-fold change in protein expression, and in order to achieve the same level of quantitative proteome coverage as the stable isotope method, it would have required approximately doubling the number of mass spectra collected.

Animals↗

PubMed2006

Quantitative proteomics of the archaeon Methanococcus maripaludis validated by microarray analysis and real time PCR.

For the archaeon Methanococcus maripaludis, a fully sequenced and annotated model species of hydrogenotrophic methanogen, we report validation of quantitative protein level expression ratios on a proteome-wide basis. Using an approach based on quantitative multidimensional capillary HPLC and quadrupole ion trap mass spectrometry, coverage of gene expression approached that currently achievable with transcription microarrays. Comprehensive mass spectrometry-based proteomics and spotted cDNA arrays were used to compare global protein and mRNA levels in a wild-type (S2) and mutant strain (S40) of M. maripaludis. Using linear regression with 652 expression ratios generated by both the proteomic and microarray methods, a product moment correlation coefficient of 0.24 was observed. The correlation improved to 0.61 if only genes showing significant expression changes were included. A novel two-stage method of outlier detection was used for the protein measurements when Dixon's Q-test by itself failed to give satisfactory results. The log(2) transformations of the number of peptides or isotopic peptide pairs associated with each ORF, divided by the predicted molecular weight, were found to have moderately positive correlations with two bioinformatic predictors of gene expression based on codon bias. We detected peptides derived from 939 proteins or 55% of the genome coding capacity. Of these, 60 were overexpressed, and 34 were underexpressed in the mutant. Of the 1722 ORFs encoded in the genome, 1597 or 93% were probed by cDNA arrays. Of these, 50 were more highly expressed, and 45 showed lower expression levels in the mutant relative to the wild type. 15 ORFs were shown to be overexpressed by both methods, and two ORFs were shown to be overexpressed by proteomics and underexpressed by microarray.

Archaeal Proteins↗

PubMed2006

Analysis of the stochastic variation in LTQ single scan mass spectra.

A better understanding of the scan-to-scan signal intensity variation can lead to more sophisticated algorithms for database searching and de novo peptide sequencing using single scan mass spectra. In this study, we systematically studied the variation in relative intensity of m/z values in the single scan product ion mass spectra (MS2) derived from five representative precursor ions (MS1) collected using an LTQ linear ion trap under constant flow direct infusion conditions with peptide concentrations held constant. We applied a matching algorithm based on a pair hidden Markov model to align the peaks from each scan belonging to the same m/z value prior to assessing the signal intensity variation. The most significant single contributor to scan-to-scan signal intensity variation for high abundance ions was centroider error. Our study also showed that the variation in signal intensity is higher than what would be expected if the ion statistics derived from the dual geometry electron multiplier detector followed a Poisson distribution.

Algorithms↗

PubMed2006

Disruption of the operon encoding Ehb hydrogenase limits anabolic CO2 assimilation in the archaeon Methanococcus maripaludis.

Methanococcus maripaludis is a mesophilic archaeon that reduces CO2 to methane with H2 or formate as an energy source. It contains two membrane-bound energy-conserving hydrogenases, Eha and Ehb. To determine the role of Ehb, a deletion in the ehb operon was constructed to yield the mutant, strain S40. Growth of S40 was severely impaired in minimal medium. Both acetate and yeast extract were necessary to restore growth to nearly wild-type levels, suggesting that Ehb was involved in multiple steps in carbon assimilation. However, no differences in the total hydrogenase specific activities were found between the wild type and mutant in either cell extracts or membrane-purified fractions. Methanogenesis by resting cells with pyruvate as the electron donor was also reduced by 30% in S40, suggesting a defect in pyruvate oxidation. CO dehydrogenase/acetyl coenzyme A (CoA) synthase and pyruvate oxidoreductase had higher specific activities in the mutant, and genes encoding these enzymes, as well as AMP-forming acetyl-CoA synthetase, were expressed at increased levels. These observations support a role for Ehb in anabolic CO2 assimilation in methanococci.

Acetate-CoA Ligase↗

PubMed2006

Mass spectrometry-based proteomics and its application to studies of Porphyromonas gingivalis invasion and pathogenicity.

Porphyromonas gingivalis is a Gram-negative anaerobe that populates the subgingival crevice of the mouth. It is known to undergo a transition from its commensal status in healthy individuals to a highly invasive intracellular pathogen in human patients suffering from periodontal disease, where it is often the dominant species of pathogenic bacteria. The application of mass spectrometry-based proteomics to the study of P. gingivalis interactions with model host cell systems, invasion and pathogenicity is reviewed. These studies have evolved from qualitative identifications of small numbers of secreted proteins, using traditional gel-based methods, to quantitative whole cell proteomic studies using multiple dimension capillary HPLC coupled with linear ion trap mass spectrometry. It has become possible to generate a differential readout of protein expression change over the entire P. gingivalis proteome, in a manner analogous to whole genome mRNA arrays. Different strategies have been employed for generating protein level expression ratios from mass spectrometry data, including stable isotope metabolic labeling and most recently, spectral counting methods. A global view of changes in protein modification status remains elusive due to the limitations of existing computational tools for database searching and data mining. Such a view would be desirable for purposes of making global assessments of changes in gene regulation in response to host interactions during the course of adhesion, invasion and internalization. With a complete data matrix consisting of changes in transcription, protein abundance and protein modification during the course of invasion, the search for new protein drug targets would benefit from a more comprehensive understanding of these processes than what could be achieved prior to the advent of systems biology.

Bacterial Proteins↗