Nuclear Magnetic Resonance for Analysis of Metabolite Composition of Escherichia Coli

Discrimination of Escherichia coli and Shigella spp. by Nuclear Magnetic Resonance Based Metabolomic Characterization of Culture Media

Dysentery is a major health threat that dramatically impacts childhood morbidity and mortality in developing countries. Various pathogenic agents cause dysentery, such as Shigella spp. and Escherichia coli, which are very closely related if not identical species. Sensitive and precise detection and identification of the infectious agent is important to target the best therapeutic strategy, but the differential diagnosis of these two groups remains a challenge using conventional methods. Here, we present a nuclear magnetic resonance (NMR) based multivariate classification model employing bacterial metabolic footprints in postculture growth media with remarkable segregation capability, including the discrimination of lactose negative E. coli and Shigella spp. Our results confirm the potential of metabolomic markers in the field of bacterial identification for the distinction of even very closely related species.

Identification and Antibiotic-Susceptibility Profiling of Infectious Bacterial Agents: A Review of Current and Future Trends

Antimicrobial resistance is one of the most worrying threats to humankind with extremely high healthcare costs associated. The current technologies used in clinical microbiology to identify the bacterial agent and profile antimicrobial susceptibility are time-consuming and frequently expensive. As a result, physicians prescribe empirical antimicrobial therapies. This scenario is often the cause of therapeutic failures, causing higher mortality rates and healthcare costs, as well as the emergence and spread of antibiotic resistant bacteria. As such, new technologies for rapid identification of the pathogen and antimicrobial susceptibility testing are needed. This review summarizes the current technologies, and the promising emerging and future alternatives for the identification and profiling of antimicrobial resistance bacterial agents, which are expected to revolutionize the field of clinical diagnostics.

Qualitative Alterations of Bacterial Metabolome after Exposure to Metal Nanoparticles with Bactericidal Properties: A Comprehensive Workflow Based on (1)H NMR, UHPLC-HRMS, and Metabolic Databases

Metal nanoparticles (NPs) have proven to be more toxic than bulk analogues of the same chemical composition due to their unique physical properties. The NPs, lately, have drawn the attention of researchers because of their antibacterial and biocidal properties. In an effort to shed light on the mechanism through which the bacteria elimination is achieved and the metabolic changes they undergo, an untargeted metabolomic fingerprint study was carried out on Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria species. The (1)H NMR spectroscopy, in conjunction with high resolution mass-spectrometry (HRMS) and an unsophisticated data processing workflow were implemented. The combined NMR/HRMS data, supported by an open-access metabolomic database, proved to be efficacious in the process of assigning a putative annotation to a wide range of metabolite signals and is a useful tool to appraise the metabolome alterations, as a consequence of bacterial response to NPs. Interestingly, not all the NPs diminished the intracellular metabolites; bacteria treated with iron NPs produced metabolites not present in the nonexposed bacteria sample, implying the activation of previously inactive metabolic pathways. In contrast, copper and iron-copper NPs reduced the annotated metabolites, alluding to the conclusion that the metabolic pathways (mainly alanine, aspartate, and glutamate metabolism, beta-alanine metabolism, glutathione metabolism, and arginine and proline metabolism) were hindered by the interactions of NPs with the intracellular metabolites.

Identification of bacterial species by untargeted NMR spectroscopy of the exo-metabolome

Identification of bacterial species is a crucial bottleneck for clinical diagnosis of infectious diseases. Quick and reliable identification is a key factor to provide suitable antibiotherapies and avoid the development of multiple-drug resistance. We propose a novel nuclear magnetic resonance (NMR)-based metabolomics strategy for rapid discrimination and identification of several bacterial species that relies on untargeted metabolic profiling of supernatants from bacterial culture media. We show that six bacterial species (Gram negative: Escherichia coli, Pseudomonas aeruginosa, Proteus mirabilis; Gram positive: Enterococcus faecalis, Staphylococcus aureus, and Staphylococcus saprophyticus) can be well discriminated from multivariate statistical analysis, opening new prospects for NMR applications to microbial clinical diagnosis.

Unraveling the concentration-dependent metabolic response of Pseudomonas sp. HF-1 to nicotine stress by ¹H NMR-based metabolomics

Nicotine can cause oxidative damage to organisms; however, some bacteria, for example Pseudomonas sp. HF-1, are resistant to such oxidative stress. In the present study, we analyzed the concentration-dependent metabolic response of Pseudomonas sp. HF-1 to nicotine stress using ¹H NMR spectroscopy coupled with multivariate data analysis. We found that the dominant metabolites in Pseudomonas sp. HF-1 were eight aliphatic organic acids, six amino acids, three sugars and 11 nucleotides. After 18 h of cultivation, 1 g/L nicotine caused significant elevation of sugar (glucose, trehalose and maltose), succinate and nucleic acid metabolites (cytidine, 5'-CMP, guanine 2',3'-cyclic phosphate and adenosine 2',3'-cyclic phosphate), but decrease of glutamate, putrescine, pyrimidine, 2-propanol, diethyl ether and acetamide levels. Similar metabolomic changes were induced by 2 g/L nicotine, except that no significant change in trehalose, 5'-UMP levels and diethyl ether were found. However, 3 g/L nicotine led to a significant elevation in the two sugars (trehalose and maltose) levels and decrease in the levels of glutamate, putrescine, pyrimidine and 2-propanol. Our findings indicated that nicotine resulted in the enhanced nucleotide biosynthesis, decreased glucose catabolism, elevated succinate accumulation, severe disturbance in osmoregulation and complex antioxidant strategy. And a further increase of nicotine level was a critical threshold value that triggered the change of metabolic flow in Pseudomonas sp. HF-1. These findings revealed the comprehensive insights into the metabolic response of nicotine-degrading bacteria to nicotine-induced oxidative toxicity.