The possible relationship(s) between intestinal dysbiosis and various degenerative intestinal-based diseases, e.g. diabetes and obesity, is an ongoing focus of intense investigation. [1][2][3][4] As a consequence of the results of such research, the focus is now on therapeutic strategies for such diseases based on modification of the gut microbiota. 2,4 Fecal transplantation is one such strategy, which was suggested by Zhang and co-workers 2 as a treatment for diabetes mellitus and by Kang and co-workers 4 for treatment of obesity. Kang and co-workers also reported different strategies involving fecal gut microbiota transplantation to treat obesity. Other studies correlated other degenerative diseases to gut microbiota activities and suggested therapeutic strategies to alleviate those disease states. 1 This interesting prospect, i.e., fecal gut microbiota transplantation to combat intestine-related diseases, has led to the development of methods by different research groups to evaluate the gut microbiota status in human subjects. 5-8 These approaches can be classified as:a. Untargeted approaches that search for bacteria responsible for dysbiosis without any prior knowledge of which types of bacterium might be involved. 5,6 b. Targeted approaches that search for specific pathogens and the correlation of these to gut microbiota-related dysbiosis. 7,8 One example of an untargeted approach is that of Pinheiro de Oliveira and co-workers who developed a method that detects thousands of different species using DNA gene amplification. 5 For the aforementioned DNA approaches, it is difficult to determine a correlation between the presence of a bacterial species and its involvement in intestinal dysbiosis without knowledge of how its metabolism affects the intestinal environment. 5,6

In this work, the isolation step in the linear ion trap was performed using different "q values" conditions at a low collision-induced dissociation (CID) energy leading to the parent ion resolution improvements, reasonably due to better ion energy distribution.According to the results, we obtained a greater resolution and mass accuracy operating in both traditional electrospray and low voltage ionization near the q value = 0.778 and with a CID energy of 10%. This effect was evaluated with lowmolecular-mass compounds (skatole and arginine). The proposed optimization yielded a superior instrument performance without adding technological complexity to mass spectrometry analyses.

Rationale Advances in metabolomics, together with consolidated genetic approaches, have opened the way for investigating the health of patients using a large number of molecules simultaneously, thus providing firm scientific evidence for personalized medicine and consequent interventions. Metabolomics is an ideal approach for investigating specific biochemical alterations occurring in rare clinical situations, such as those caused by rare associations between comorbidities and immunosuppression. Methods Metabolomic database matching enables clear identification of molecular factors associated with a metabolic disorder and can provide a rationale for elaborating personalized therapeutic protocols. Mass spectrometry (MS) forms the basis of metabolomics and uses mass‐to‐charge ratios for metabolite identification. Here, we used an MS–based approach to diagnose and develop treatment options in the clinical case of a patient afflicted with a rare disease further complicated by immunosuppression. The patient's data were analyzed using proprietary databases, and a personalized and efficient therapeutic protocol was consequently elaborated. Results The patient exhibited significant alterations in homocysteine:methionine and homocysteine:thiodiglycol acid plasma concentration ratios, and these were associated with low immune system function. This led to cysteine concentration deficiency causing extreme oxidative stress. Plasmatic thioglycolic acid concentrations were initially altered and were used for therapeutic follow‐up and to evaluate cysteine levels. Conclusions An MS–based pharmacometabolomics approach was used to define a personalized protocol in a clinical case of rare peritoneal carcinosis with confounding immunosuppression. This personalized protocol reduced both oxidative stress and resistance to antibiotics and antiviral drugs.

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