Amino acid metabolism of Salmonellae

Metabolomics Deciphered Metabolic Reprogramming Required for Biofilm Formation

Biofilm formation plays a key role in many bacteria causing infections, which mostly accounts for high-frequency infectious recurrence and antibiotics resistance. In this study, we sought to compare modified metabolism of biofilm and planktonic populations with UTI89, a predominant agent of urinary tract infection, by combining mass spectrometry based untargeted and targeted metabolomics methods, as well as cytological visualization, which enable us to identify the driven metabolites and associated metabolic pathways underlying biofilm formation. Surprisingly, our finding revealed distinct differences in both phenotypic morphology and metabolism between two patterns. Furthermore, we identified and characterized 38 differential metabolites and associated three metabolic pathways involving glycerolipid metabolism, amino acid metabolism and carbohydrate metabolism that were altered mostly during biofilm formation. This discovery in metabolic phenotyping permitted biofilm formation shall provide us a novel insight into the dissociation of biofilm, which enable to develop novel biofilm based treatments against pathogen causing infections, with lower antibiotic resistance.

Gas chromatography-mass spectrometry-based metabolite profiling of Salmonella enterica serovar Typhimurium differentiates between biofilm and planktonic phenotypes

The aim of this study was to utilize gas chromatography coupled with mass spectrometry (GC-MS) to compare and identify patterns of biochemical change between Salmonella cells grown in planktonic and biofilm phases and Salmonella biofilms of different ages. Our results showed a clear separation between planktonic and biofilm modes of growth. The majority of metabolites contributing to variance between planktonic and biofilm supernatants were identified as amino acids, including alanine, glutamic acid, glycine, and ornithine. Metabolites contributing to variance in intracellular profiles were identified as succinic acid, putrescine, pyroglutamic acid, and N-acetylglutamic acid. Principal-component analysis revealed no significant differences between the various ages of intracellular profiles, which would otherwise allow differentiation of biofilm cells on the basis of age. A shifting pattern across the score plot was illustrated when analyzing extracellular metabolites sampled from different days of biofilm growth, and amino acids were again identified as the metabolites contributing most to variance. An understanding of biofilm-specific metabolic responses to perturbations, especially antibiotics, can lead to the identification of novel drug targets and potential therapies for combating biofilm-associated diseases. We concluded that under the conditions of this study, GC-MS can be successfully applied as a high-throughput technique for "bottom-up" metabolomic biofilm research.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

Background

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem.

Results

Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches.

Conclusion

Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.