Characterising the urinary metabolic effects of HIV/TB co-infection, using GC-MS metabolomics

Abstract

The human immunodeficiency virus (HIV) and tuberculosis (TB) remain prominent global health threats. Individuals with HIV face increased vulnerability to various opportunistic infections due to compromised immune systems, elevating the risk of Mycobacterium tuberculosis (Mtb) infection and subsequent TB development. The co-infection of HIV and TB is particularly concerning in regions with high prevalence, such as South Africa, contributing significantly to the burden on healthcare systems. Combining resources for the treatment of co-infected patients intensifies the challenges posed by these interconnected diseases. Notably, 8% of global incident TB cases occur in people living with HIV, with southern Africa alone exceeding 50% prevalence of HIV/TB co-infection. The number of TB-diagnosed individuals aware of their HIV status has decreased to 4.2 million, underscoring gaps in testing and treatment for co-infected cases. The choice of urine as a sample matrix for investigating HIV/TB co-infection is optimal due to its comprehensive representation of normal and pathological cellular processes, allowing for a holistic metabolic assessment. Given the goal of non-targeted metabolomics to analyse various compound classes at varying concentrations, achieving optimal extraction is crucial. Since organic acid (OA) extraction is commonly employed for urine gas chromatography mass spectrometry (GC-MS), this study firstly explored the optimised urine volume used in our current in-house OA extraction protocol (Section A, Part 1). Hereafter, we optimised a low volume urine preparation procedure for non-targeted GC-MS. Five extraction methods (four OA extraction variations and a "direct analysis" [DA] approach) were assessed based on repeatability, metabolome coverage, and metabolite recovery (Section A, Part 2). 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 twostep derivatization but did not benefit from urease sample pre-treatment (Section A, Part 3). Following optimisation, the selected extraction method was used to analyse urine samples collected from healthy individuals and individuals with HIV, TB, and HIV/TB co-infection using two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC-TOFMS), aiming to elucidate the metabolic profile of co-infection (Section B). Statistical analysis identified 25 metabolites of interest that significantly differed among the four groups. Specifically, the results revealed significant alterations across various metabolite groups, reflecting the complex metabolic impact of HIV, TB, and their co-infection. Notable shifts were observed in amino acids and related metabolites, indicating profound changes in protein biosynthesis and breakdown. These alterations are particularly pronounced in HIV-positive individuals, where increased levels of glycine and pentane dioic acid suggest adaptations in amino acid and fatty acid metabolism. In TB patients, altered phenylalanine metabolism is highlighted by elevated 3-phenyllactic acid, linked to cachexia and disrupted insulin regulation. The study also observed a unique carbohydrate metabolism in TB, marked by decreased levels of L-threonic acid and ribitol, potentially due to impaired glucose metabolism and the interplay between TB and diabetes. Co-infection with HIV and TB further amplifies these metabolic disturbances, as evidenced by the highest levels of quinolinic acid, suggesting a synergistic effect on inflammatory responses. The findings demonstrate the intricate metabolic changes occurring in HIV and TB, offering insights into their pathogenesis and potential avenues for therapeutic intervention. Overall, this study established 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. As a proof of concept, our new approach was applied to clinical samples and found that eight major metabolite categories differed significantly between the comparative groups, with notable impacts on amino acid-related metabolites and energy metabolism. Both HIV and TB affect host metabolism, altering normal metabolic pathways. Although none of the identified metabolites were disease-specific, they provided valuable insights into induced metabolic changes. The complex interplay of these disease, however, challenges the anticipated observations of HIV/TB co-infection effects. Future studies may benefit from a more targeted approach to comprehensively understand this intricate relationship.