ABSTRACT
<p><b>OBJECTIVE</b>This study intends to explore the mechanism underlying the support of sortase A (SrtA) of the cariogenicity of Streptococcus mutans (S. mutans).</p><p><b>METHODS</b>We performed a metabonomics study based on ¹H nuclear magnetic resonance spectroscopy (NMR), in which we compared the extracellular metabolites of wild-type S. mutans UA159 with those of its SrtA-deficient strain. Metabolite differences among strains were identified using a combination of principal component analysis and orthogonality partial least square discriminant analysis.</p><p><b>RESULTS</b>Several differences corresponding mostly to unknown metabolites were identified. Some amino acids such as leucine and valine (δ 0.92×10⁻⁶-1.20×10⁻⁶), lactic acid ( δ1.28×10⁻⁶), oxoglutaric acid (δ 3.00×10⁻⁶), and glycine (δ 3.60×10⁻⁶) differed among strains.</p><p><b>CONCLUSIONS</b>This work establishes the feasibility of using ¹H NMR-based metabonomics to provide leads for research into molecular factors that promote caries. The database of microbial metabolites should be also improved in further studies.</p>
ABSTRACT
A two-dimensional liquid chromatography method was developed for the analysis of rice leaves proteomics based on the coupling of hydrophilic interaction liquid chromatography-reversed-phase liquid chromatography with online tandem mass spectrometry. The influence of pH value of chromatographic mobile phase on the orthogonality of the hydrophilic interaction-reversed-phase two-dimensional liquid chromatography was evaluated by the changes of standard peptide retention. The results indicated that the better orthogonality (R2=0.34113) was achieved from the system with hydrophilic interaction columns(pH 9.3) in the first and C18columns(pH 3.3) in the second LC dimension. Coupled with multiple fraction concatenation strategy,the orthogonality of two-dimensional liquid chromatography was further evaluated in the analysis of complex rice leaf proteins. The results showed that more than 50% of the total peptides were identified less than two times, and the peptides obtained from first-dimension were well distributed across the elution window,indicating that the method showed significant orthogonality in the identification of complex rice leaf proteins. Based on the proteome discoverer software,207345 peptides belonged to 2930 protein clusters were identified.