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BackgroundMany human microbial infectious diseases including dental caries are polymicrobial in nature. How these complex multi-species communities evolve from a healthy to a diseased state is not well understood. Although many health- or disease-associated oral bacteria have been characterized in vitro, their physiology within the complex oral microbiome is difficult to determine with current approaches. In addition, about half of these species remain uncultivated to date with little known besides their 16S rRNA sequence. Lacking culture-based physiological analyses, the functional roles of uncultivated species will remain enigmatic despite their apparent disease correlation. To start addressing these knowledge gaps, we applied a combination of Magnetic Resonance Spectroscopy (MRS) with RNA and DNA based Stable Isotope Probing (SIP) to oral plaque communities from healthy children for in vitro temporal monitoring of metabolites and identification of metabolically active and inactive bacterial species.Methodology/Principal FindingsSupragingival plaque samples from caries-free children incubated with 13C-substrates under imposed healthy (buffered, pH 7) and diseased states (pH 5.5 and pH 4.5) produced lactate as the dominant organic acid from glucose metabolism. Rapid lactate utilization upon glucose depletion was observed under pH 7 conditions. SIP analyses revealed a number of genera containing cultured and uncultivated taxa with metabolic capabilities at pH 5.5. The diversity of active species decreased significantly at pH 4.5 and was dominated by Lactobacillus and Propionibacterium species, both of which have been previously found within carious lesions from children.Conclusions/SignificanceOur approach allowed for identification of species that metabolize carbohydrates under different pH conditions and supports the importance of Lactobacilli and Propionibacterium in the development of childhood caries. Identification of species within healthy subjects that are active at low pH can lead to a better understanding of oral caries onset and generate appropriate targets for preventative measures in the early stages.

BackgroundYersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas.ResultsHere we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain.ConclusionsY. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

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Base dynamics, heretofore observed only at TpA steps in DNA, were investigated as a function of sequence context by NMR spectroscopy. The large amplitude conformational dynamics have been previously observed in TnAn segments where n > or = 2. In order to determine whether the dynamic characteristics occur in more general sequence contexts, we examined four self-complementary DNA sequences, [d(CTTTA-NATNTAAAG)2] (where N = A, C, T, G and N = complement of N). The anomalous broadening of the TpA adenine H2 resonance which is indicative of large amplitude base motion was observed in all nine unique four nucleotide contexts. Furthermore, all the adenine H2 resonances experienced a linewidth maximum as a function of temperature, which is a characteristic of the dynamic process. Interestingly, the temperature of the linewidth maximum varied with sequence indicating that the thermodynamics of TpA base dynamics are also sequence dependent. In one example, neither a T preceding nor an A trailing the TpA step was required for base dynamics. These results show that base dynamics, heretofore observed in only a few isolated sequences, occurs at all TpA steps which are either preceded or followed by a thymine or adenine, respectively, and may be characteristic of all TpA steps in DNA notwithstanding sequence context.

High-throughput (HTP) technologies offer the capability to evaluate the genome, proteome, and metabolome of an organism at a global scale. This opens up new opportunities to define complex signatures of disease that involve signals from multiple types of biomolecules. However, integrating these data types is difficult due to the heterogeneity of the data. We present a Bayesian approach to integration that uses posterior probabilities to assign class memberships to samples using individual and multiple data sources; these probabilities are based on lower-level likelihood functions derived from standard statistical learning algorithms. We demonstrate this approach on microbial infections of mice, where the bronchial alveolar lavage fluid was analyzed by three HTP technologies, two proteomic and one metabolomic. We demonstrate that integration of the three datasets improves classification accuracy to ~89% from the best individual dataset at ~83%. In addition, we present a new visualization tool called Visual Integration for Bayesian Evaluation (VIBE) that allows the user to observe classification accuracies at the class level and evaluate classification accuracies on any subset of available data types based on the posterior probability models defined for the individual and integrated data.

Recent NMR-based, chemical shift mapping experiments with the minimal DNA-binding domain of XPA (XPA-MBD: M98-F219) suggest that a basic cleft located in the loop-rich subdomain plays a role in DNA-binding. Here, XPA-DNA interactions are further characterized by NMR spectroscopy from the vantage point of the DNA using a single-stranded DNA nonamer, dCCAATAACC (d9). Up to 2.5 molar equivalents of XPA-MBD was titrated into a solution of d9. A subset of (31)P resonances of d9 were observed to broaden and/or shift providing direct evidence that XPA-MBD binds d9 by a mechanism that perturbs the phosphodiester backbone of d9. The interior five residues of d9 broadened and/or shifted before (31)P resonances of phosphate groups at the termini, suggesting that when d9 is bound to XPA-MBD the internal residues assume a correlation time that is characteristic of the molecular weight of the complex while the residues at the termini undergo a fraying motion away from the surface of the protein on a timescale such that the line widths are more characteristic of the molecular weight of ssDNA. A molecular model of the XPA-MBD complex with d9 was calculated based on the (15)N (XPA-MBD) and (31)P (d9) chemical shift mapping studies and on the assumption that electrostatic interactions drive the complex formation. The model shows that a nine residue DNA oligomer fully covers the DNA-binding surface of XPA and that there may be an energetic advantage to binding DNA in the 3'-->5' direction rather than in the 5'-->3' direction (relative to XPA-MBD alpha-helix-3).

In-phase ligated DNA containing T(n)A(n) segments fail to exhibit the retarded polyacrylamide gel electrophoresis (PAGE) migration observed for in-phase ligated A(n)T(n) segments, a behavior thought to be correlated with macroscopic DNA curvature. The lack of macroscopic curvature in ligated T(n)A(n) segments is thought to be due to cancellation of bending in regions flanking the TpA steps. To address this issue, solution-state NMR, including residual dipolar coupling (RDC) restraints, was used to determine a high-resolution structure of [d(CGAGGTTTAAACCTCG)2], a DNA oligomer containing a T3A3 tract. The overall magnitude and direction of bending, including the regions flanking the central TpA step, was measured using a radius of curvature, Rc, analysis. The Rc for the overall molecule indicated a small magnitude of global bending (Rc = 138 +/- 23 nm) towards the major groove, whereas the Rc for the two halves (72 +/- 33 nm and 69 +/- 14 nm) indicated greater localized bending into the minor groove. The direction of bending in the regions flanking the TpA step is in partial opposition (109 degrees), contributing to cancellation of bending. The cancellation of bending did not correlate with a pattern of roll values at the TpA step, or at the 5' and 3' junctions, of the T3A3 segment, suggesting a simple junction/roll model is insufficient to predict cancellation of DNA bending in all T(n)A(n) junction sequence contexts. Importantly, Rc analysis of structures refined without RDC restraints lacked the precision and accuracy needed to reliably measure bending.