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Introduction: The human immunodeficiency virus (HIV) and tuberculosis (TB) co-infection presents significant challenges due to the complex interplay between these diseases, leading to exacerbated metabolic disturbances. Understanding these metabolic profiles is crucial for improving diagnostic and therapeutic approaches., Objective: This study aimed to characterise the urinary acylcarnitine and amino acid profiles, including 5-hydroxyindoleacetic acid (5-HIAA), in patients co-infected with HIV and TB using targeted liquid chromatography mass spectrometry (LC-MS) metabolomics., Methods: Urine samples, categorised into HIV, TB, HIV/TB co-infected, and healthy controls, were analysed using HPLC-MS/MS. Statistical analyses included one-way ANOVA and a Kruskal-Wallis test to determine significant differences in the acylcarnitine and amino acid profiles between groups., Results: The study revealed significant metabolic alterations, especially in TB and co-infected groups. Elevated levels of medium-chain acylcarnitines indicated increased fatty acid oxidation, commonly associated with cachexia in TB. Altered amino acid profiles suggested disruptions in protein and glucose metabolism, indicating a shift towards diabetes-like metabolic states. Notably, TB was identified as a primary driver of these changes, affecting protein turnover, and impacting energy metabolism in co-infected patients., Conclusion: The metabolic profiling of HIV/TB co-infection highlights the profound impact of TB on metabolic pathways, which may exacerbate the clinical complexities of co-infection. Understanding these metabolic disruptions can guide the development of targeted treatments and improve management strategies, ultimately enhancing the clinical outcomes for these patients. Further research is required to validate these findings and explore their implications in larger, diverse populations., (© 2024. The Author(s).)

Introduction: Amid the global health crisis, HIV/TB co-infection presents significant challenges, amplifying the burden on patients and healthcare systems alike. Metabolomics offers an innovative window into the metabolic disruptions caused by co-infection, potentially improving diagnosis and treatment monitoring., Aim: This study uses untargeted metabolomics to investigate the urinary metabolic signature of HIV/TB co-infection, enhancing understanding of the metabolic interplay between these infections., Methods: Urine samples from South African adults, categorised into four groups - healthy controls, TB-positive, HIV-positive, and HIV/TB co-infected - were analysed using GCxGC-TOFMS. Metabolites showing significant differences among groups were identified through Kruskal-Wallis and Wilcoxon rank sum tests., Results: Various metabolites (n = 23) were modulated across the spectrum of health and disease states represented in the cohorts. The metabolomic profiles reflect a pronounced disruption in biochemical pathways involved in energy production, amino acid metabolism, gut microbiome, and the immune response, suggesting a bidirectional exacerbation between HIV and TB. While both diseases independently perturb the host's metabolism, their co-infection leads to a unique metabolic phenotype, indicative of an intricate interplay rather than a simple additive effect., Conclusion: Metabolic profiling revealed a unique metabolic landscape shaped by HIV/TB co-infection. The findings highlight the potential of urinary differential metabolites for co-infection, offering a non-invasive tool for enhancing diagnostic precision and tailoring therapeutic interventions. Future research should focus on expanding sample sizes and integrating longitudinal analyses to build upon these foundational insights, paving the way for metabolomic applications in combating these concurrent pandemics., (© 2024. The Author(s).)

Urine is ideal for non-targeted metabolomics, providing valuable insights into normal and pathological cellular processes. Optimal extraction is critical since non-targeted metabolomics aims to analyse various compound classes. Here, we optimised a low-volume urine preparation procedure for non-targeted GC-MS. Five extraction methods (four organic acid [OA] extraction variations and a "direct analysis" [DA] approach) were assessed based on repeatability, metabolome coverage, and metabolite recovery. The DA method exhibited superior repeatability, and achieved the highest metabolome coverage, detecting 91 unique metabolites from multiple compound classes comparatively. Conversely, OA methods may not be suitable for all non-targeted metabolomics applications due to their bias toward a specific compound class. In accordance, the OA methods demonstrated limitations, with lower compound recovery and a higher percentage of undetected compounds. The DA method was further improved by incorporating an additional drying step between two-step derivatization but did not benefit from urease sample pre-treatment. Overall, this study establishes an improved low-volume urine preparation approach for future non-targeted urine metabolomics applications using GC-MS. Our findings contribute to advancing the field of metabolomics and enable efficient, comprehensive analysis of urinary metabolites, which could facilitate more accurate disease diagnosis or biomarker discovery., (© 2023. Springer Nature Limited.)

In the quest to identify novel biomarkers for pulmonary tuberculosis (TB), high-throughput systems biology approaches such as metabolomics has become increasingly widespread. Such biomarkers have not only successfully been used for better disease characterization, but have also provided new insights toward the future development of improved diagnostic and therapeutic approaches. In this review, we give a summary of the metabolomics studies done to date, with a specific focus on those investigating various aspects of pulmonary TB, and the infectious agent responsible, Mycobacterium tuberculosis. These studies, done on a variety of sample matrices, including bacteriological culture, sputum, blood, urine, tissue, and breath, are discussed in terms of their intended research outcomes or future clinical applications. Additionally, a summary of the research model, sample cohort, analytical apparatus and statistical methods used for biomarker identification in each of these studies, is provided., (Copyright © 2019. Published by Elsevier Ltd.)

Aim: Predicting a poor treatment outcome would offer significant benefits for patient care and for new drug development. Materials, methods & results: Urine samples from tuberculosis-positive patients with a successful and unsuccessful treatment outcome were collected at baseline and analyzed. The identified metabolites were used in a forward logistic regression model, which achieved a receiver operating characteristic area under the curve of 0.94 (95% CI: 0.84-1) and cross-validated well in a leave-one-out context, with an area under the curve of 0.89 (95% CI: 0.7-1). Two possible predictors were identified, which are associated with a gut microbiota imbalance., Discussion & Conclusion: Our findings show the capacity of metabolomics to predict treatment failure at the time of diagnosis, which potentially offers significant benefits for the use in new drug development clinical trials and individualized patient care.

Despite the fact that tuberculosis (TB) is a curable disease, it still results in approximately 1.8 million deaths annually. Various inadequacies in the current TB treatment strategies are major contributors to this high disease prevalence, including the long duration of therapy, the severe side effects associated with TB drugs, treatment failure due to drug resistance, post-treatment disease relapse, and HIV co-infection. In this review, we describe how metabolomics has contributed toward better explaining/elucidating the mechanisms of drug action/metabolism, drug toxicity and microbial drug resistance, and how metabolite biomarkers may serve as prognostic indicators for predicting treatment outcome as well as for the development of new TB drugs. We also discuss possible future contributions that metabolomics can make toward more efficient, less toxic TB treatment strategies.

Numerous studies have contributed to our current understanding of the complex biology of pulmonary tuberculosis and subsequently provided solutions to its control or eradication. Metabolomics, a newcomer to the Omics research domain, has significantly contributed to this understanding by identifying biomarkers originating from the disease-associated metabolome adaptations of both the microbe and host. These biomarkers have shed light on previously unknown disease mechanisms, many of which have been implemented toward the development of improved diagnostic strategies. In this review, we will discuss the role that metabolomics has played in tuberculosis research to date, with a specific focus on new biomarker identification, and how these have contributed to improved disease characterization and diagnostics, and their potential clinical applications.

Endurance athlete performance is greatly dependent on sufficient post-race system recovery, as endurance races have substantial physiological, immunological and metabolic effects on these athletes. To date, the effects of numerous recovery modalities have been investigated, however, very limited literature exists pertaining to metabolic recovery of athletes after endurance races without the utilisation of recovery modalities. As such, this investigation is aimed at identifying the metabolic recovery trend of athletes within 48 h after a marathon. Serum samples of 16 athletes collected 24 h before, immediately after, as well as 24 h and 48 h post-marathon were analysed using an untargeted two-dimensional gas chromatography time-of-flight mass spectrometry metabolomics approach. The metabolic profiles of these comparative time-points indicated a metabolic shift from the overall post-marathon perturbed state back to the pre-marathon metabolic state during the recovery period. Statistical analyses of the data identified 61 significantly altered metabolites including amino acids, fatty acids, tricarboxylic acid cycle, carbohydrates and associated intermediates. These intermediates recovered to pre-marathon related concentrations within 24 h post-marathon, except for xylose which only recovered within 48 h. Furthermore, fluctuations in cholesterol and pyrimidine intermediates indicated the activation of alternative recovery mechanisms. Metabolic recovery of the athletes was attained within 48 h post-marathon, most likely due to reduced need for fuel substrate catabolism. This may result in the activation of glycogenesis, uridine-dependent nucleotide synthesis, protein synthesis, and the inactivation of cellular autophagy. These results may be beneficial in identifying more efficient, targeted recovery approaches to improve athletic performance. [ABSTRACT FROM AUTHOR]