Metabolomics data

To investigate how early mono- and dual species biofilms of oral Actinomyces naeslundii and Streptococcus gordonii clinical isolates metabolized glucose in the presence of the complex salivary mucin MUC5B, this study employed NMR-based metabolomics with interpretation of network integration. Untargeted NMR data analysis for metabolite detection and annotation and in silico studies of biochemical relationships between metabolites and cellular processes was performed to study functional differences in the early biofilm metabolomes. Significant differences in metabolite abundance elicited by the presence of MUC5B were detected. The main metabolites that distinguished the biofilms grown with 25% MUC5B with 20 mM glucose (MUC5B+G) from those grown with physiologic buffer with 20 mM glucose (PBS+G) were the unannotated metabolites 68 and 73. In the conditions were they were each present, pyruvate, ethanol and metabolite 134 were significantly more abundant in the presence of MUC5B, while metabolites 84, 97 and sarcosine were significantly less abundant. The pathway enrichment analysis of the metabolites that were differently expressed in early A. naeslundii, S. gordonii and dual species biofilms grown with PBS+G or MUC5B+G showed that pyruvate metabolism was significantly over-represented. Studying the metabolic interactions between commensal members of oral biofilms and modulatory effects of host factors such as glycoproteins in saliva during metabolism of substrates that are potential drivers of dysbiosis, such as glucose, is essential to understand the roles of oral microbial ecosystems in oral health and disease.

Dental caries is characterized by a dysbiotic shift at the biofilm-tooth surface interface, yet comprehensive biochemical characterizations of the biofilm are scant. We used metabolomics to identify biochemical features of the supragingival biofilm associated with early childhood caries (ECC) prevalence and severity. The study's analytical sample comprised 289 children ages 3 to 5 (51% with ECC) who attended public preschools in North Carolina and were enrolled in a community-based cross-sectional study of early childhood oral health. Clinical examinations were conducted by calibrated examiners in community locations using International Caries Detection and Classification System (ICDAS) criteria. Supragingival plaque collected from the facial/buccal surfaces of all primary teeth in the upper-left quadrant was analyzed using ultra-performance liquid chromatography-tandem mass spectrometry. Associations between individual metabolites and 18 clinical traits (based on different ECC definitions and sets of tooth surfaces) were quantified using Brownian distance correlations (dCor) and linear regression modeling of log2-transformed values, applying a false discovery rate multiple testing correction. A tree-based pipeline optimization tool (TPOT)-machine learning process was used to identify the best-fitting ECC classification metabolite model. There were 503 named metabolites identified, including microbial, host, and exogenous biochemicals. Most significant ECC-metabolite associations were positive (i.e., upregulations/enrichments). The localized ECC case definition (ICDAS ≥1 caries experience within the surfaces from which plaque was collected) had the strongest correlation with the metabolome (dCor P = 8 × 10-3). Sixteen metabolites were significantly associated with ECC after multiple testing correction, including fucose (P = 3.0 × 10-6) and N-acetylneuraminate (p = 6.8 × 10-6) with higher ECC prevalence, as well as catechin (P = 4.7 × 10-6) and epicatechin (P = 2.9 × 10-6) with lower. Catechin, epicatechin, imidazole propionate, fucose, 9,10-DiHOME, and N-acetylneuraminate were among the top 15 metabolites in terms of ECC classification importance in the automated TPOT model. These supragingival biofilm metabolite findings provide novel insights in ECC biology and can serve as the basis for the development of measures of disease activity or risk assessment.

Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea in children and adults in endemic areas. Gene regulation of ETEC during growth in vitro and in vivo needs to be further evaluated, and here we describe the full transcriptome and metabolome of ETEC during growth from mid-logarithmic growth to early stationary phase in rich medium (LB medium). We identified specific genes and pathways subjected to rapid transient alterations in gene expression and metabolite production during the transition from logarithmic to stationary growth. The transient phase was found to be different from the subsequent induction of early stationary phase-induced genes. The transient phase was characterized by the repression of genes and metabolites involved in organic substance transport. Genes involved in fucose and putrescine metabolism were upregulated, and genes involved in iron transport were repressed. Expression of toxins and colonization factors were not changed, suggesting retained virulence from mid-logarithmic to the start of the stationary phase. Metabolomic analyses showed that the transient phase was characterized by a drop of intracellular amino acids, e.g., L-tyrosine, L-tryptophan, L-phenylalanine, L-leucine and L-glutamic acid, followed by increased levels at induction of stationary phase. A pathway enrichment analysis of the entire combined transcriptome and metabolome revealed that significant pathways during progression from logarithmic to early stationary phase are involved in the degradation of neurotransmitters aminobutyrate (GABA) and precursors of 5-hydroxytryptamine (serotonin). This work provides a comprehensive framework for further studies on transcriptional and metabolic regulation in pathogenic E. coli.

Molecular networks in neurological diseases are complex. Despite this fact, contemporary biomarkers are in most cases interpreted in isolation, leading to a significant loss of information and power. We present an analytical approach to scrutinize and combine information from biomarkers originating from multiple sources with the aim of discovering a condensed set of biomarkers that in combination could distinguish the progressive degenerative phenotype of multiple sclerosis (SPMS) from the relapsing-remitting phenotype (RRMS).

METHODS: Clinical and magnetic resonance imaging (MRI) data were integrated with data from protein and metabolite measurements of cerebrospinal fluid, and a method was developed to sift through all the variables to establish a small set of highly informative measurements. This prospective study included 16 SPMS patients, 30 RRMS patients and 10 controls. Protein concentrations were quantitated with multiplexed fluorescent bead-based immunoassays and ELISA. The metabolome was recorded using liquid chromatography-mass spectrometry. Clinical follow-up data of the SPMS patients were used to assess disease progression and development of disability.

RESULTS: Eleven variables were in combination able to distinguish SPMS from RRMS patients with high confidence superior to any single measurement. The identified variables consisted of three MRI variables: the size of the spinal cord and the third ventricle and the total number of T1 hypointense lesions; six proteins: galectin-9, monocyte chemoattractant protein-1 (MCP-1), transforming growth factor alpha (TGF-α), tumor necrosis factor alpha (TNF-α), soluble CD40L (sCD40L) and platelet-derived growth factor AA (PDGF-AA); and two metabolites: 20β-dihydrocortisol (20β-DHF) and indolepyruvate.

The proteins myelin basic protein (MBP) and macrophage-derived chemokine (MDC), as well as the metabolites 20β-DHF and 5,6-dihydroxyprostaglandin F1a (5,6-DH-PGF1), were identified as potential biomarkers of disability progression.

CONCLUSION: Our study demonstrates, in a limited but well-defined and data-rich cohort, the importance and value of combining multiple biomarkers to aid diagnostics and track disease progression.

Cohort 2 assays are reported in the current study MTBLS558.

Cohort 1 assays are reported in MTBLS1464.

Background: Salmonella Typhi and Salmonella Paratyphi A are the agents of enteric (typhoid) fever; both can establish chronic carriage in the gallbladder. Chronic Salmonella carriers are typically asymptomatic, intermittently shedding bacteria in the feces, and contributing to disease transmission. Detecting chronic carriers is of public health relevance in areas where enteric fever is endemic, but there are no routinely used methods for prospectively identifying those carrying Salmonella in their gallbladder. Methodology/Principal Findings: Here we aimed to identify biomarkers of Salmonella carriage using metabolite profiling. We performed metabolite profiling on plasma from Nepali patients undergoing cholecystectomy with confirmed S. Typhi or S. Paratyphi A gallbladder carriage (and non-carriage controls) using two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOFMS) and supervised pattern recognition modeling. We were able to significantly discriminate Salmonella carriage samples from non-carriage control samples. We were also able to detect differential signatures between S. Typhi and S. Paratyphi A carriers. We additionally compared carriage metabolite profiles with profiles generated during acute infection; these data revealed substantial heterogeneity between metabolites associated with acute enteric fever and chronic carriage. Lastly, we found that Salmonella carriers could be significantly distinguished from non-carriage controls using only five metabolites, indicating the potential of these metabolites as diagnostic markers for detecting chronic Salmonella carriers. Conclusions/Significance: Our novel approach has highlighted the potential of using metabolomics to search for diagnostic markers of chronic Salmonella carriage. We suggest further epidemiological investigations of these potential biomarkers in alternative endemic enteric fever settings.

The metabolism of the parasite Trypanosoma brucei has been the focus of numerous studies since the 1940s. Recently it was shown, using metabolomics coupled with heavy-atom isotope labelled glucose, that the metabolism of the bloodstream form parasite is more complex than previously thought. The present study also raised a number of questions regarding the origin of several metabolites, for example succinate, only a proportion of which derives from glucose. In order to answer some of these questions and explore the metabolism of bloodstream form T. brucei in more depth we followed the fate of five heavy labelled amino acids – glutamine, proline, methionine, cysteine and arginine – using an LC–MS based metabolomics approach. We found that some of these amino acids have roles beyond those previously thought and we have tentatively identified some unexpected metabolites which need to be confirmed and their function determined.

Bacterial metabolism in oral biofilms is comprised of complex networks of nutritional chains and biochemical regulations. These processes involve both intraspecies and interspecies networks as well as interactions with components from host saliva, gingival crevicular fluid, and dietary intake. In a previous paper, a large salivary glycoprotein, mucin MUC5B, was suggested to promote a dental health-related phenotype in the oral type strain of Streptococcus gordonii DL1, by regulating bacterial adhesion and protein expression. In this study, nuclear magnetic resonance-based metabolomics was used to examine the effects on the metabolic output of monospecies compared to dual species early biofilms of two clinical strains of oral commensal bacteria, S. gordonii and Actinomyces naeslundii, in the presence of MUC5B. The presence of S. gordonii increased colonization of A. naeslundii on salivary MUC5B, and both commensals were able to utilize MUC5B as a sole nutrient source during early biofilm formation. The metabolomes suggested that the bacteria were able to release mucin carbohydrates from oligosaccharide side chains as well as amino acids from the protein core. Synergistic effects were also seen in the dual species biofilm metabolome compared to the monospecies, indicating that A. naeslundii and S. gordonii cooperated in the degradation of salivary MUC5B. A better understanding of bacterial interactions and salivary-mediated regulation of early dental biofilm activity is meaningful for understanding oral biofilm physiology and may contribute to the development of future prevention strategies for biofilm-induced oral disease.