Chronic human immunodeficiency virus (HIV) infection, separately and in combination with highly active antiretroviral therapy (HAART) is closely associated with oxidative stress (OS). Most studies demonstrating redox imbalances in HIV-infected individuals have done so using conventional biochemical methodologies. The limited simultaneous detection of multiple OS markers within one sample is a major drawback of these methodologies and can be addressed through the use of metabonomics. HIV-metabonomic studies utilizing biofluids from HAART cohorts as the investigative source, are on the increase. Data from many of these studies identified metabolic markers indicative of HIV-induced OS, usually as an outcome of an untargeted metabonomics study. Untargeted studies cast a wide net for any and all detectable metabolites in complex mixtures. Given the prevalence of OS during HIV infection and antiviral treatment, it is perhaps not surprising that indicators of this malady would become evident during metabolite identification. At times, targeted studies for specific (non-OS) metabolites would also yield OS markers as an outcome. This review examines the findings of these studies by first providing the necessary background information on OS and the main ways in which free radicals/reactive oxygen species (ROS) produced during OS, cause biomolecular damage. This is followed by information on the biomarkers which come about as a result of free radical damage and the techniques used for assaying these stress indicators. The established links between elevated ROS and lowered antioxidants during HIV infection and the subsequent use of HAART is then presented followed by a review of the OS markers detected in HIV metabonomic studies to date. We identify gaps in HIV/HAART-associated OS research and finally suggest how these research gaps can be addressed through metabonomic analysis, specifically targeting the multiple markers of HIV-induced OS.

Infiltrating low grade gliomas (LGGs) are heterogeneous in their behavior and the strategies used for clinical management are highly variable. A key factor in clinical decision-making is that patients with mutations in the isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes are more likely to have a favorable outcome and be sensitive to treatment. Because of their relatively long overall median survival, more aggressive treatments are typically reserved for patients that have undergone malignant progression (MP) to an anaplastic glioma or secondary glioblastoma (GBM). In the current study, ex vivo metabolic profiles of image-guided tissue samples obtained from patients with newly diagnosed and recurrent LGG were investigated using proton high-resolution magic angle spinning spectroscopy (¹H HR-MAS). Distinct spectral profiles were observed for lesions with IDH-mutated genotypes, between astrocytoma and oligodendroglioma histologies, as well as for tumors that had undergone MP. Levels of 2-hydroxyglutarate (2HG) were correlated with increased mitotic activity, axonal disruption, vascular neoplasia, and with several brain metabolites including the choline species, glutamate, glutathione, and GABA. The information obtained in this study may be used to develop strategies for in vivo characterization of infiltrative glioma, in order to improve disease stratification and to assist in monitoring response to therapy.

Monitoring the progression of HIV infection to full-blown acquired immune deficiency syndrome (AIDS) and assessing responses to treatment will benefit greatly from the identification of novel biological markers especially since existing clinical indicators of disease are not infallible. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are powerful methodologies used in metabonomic analyses for an approximation of HIV-induced changes to the phenotype of an infected individual. Although early in its application to HIV/AIDS, (biofluid) metabonomics has already identified metabolic pathways influenced by both HIV and/or its treatment. To date, biofluid NMR and MS data show that the virus and highly active antiretroviral treatment (HAART) mainly influence carbohydrate and lipid metabolism, suggesting that infected individuals are susceptible to very specific metabolic complications. A number of well-defined biofluid metabonomic studies clearly distinguished HIV negative, positive and treatment experienced patient profiles from one another. While many of the virus or treatment affected metabolites have been identified, the metabonomics measurements were mostly qualitative. The identities of the molecules were not always validated neither were the statistical models used to distinguish between groups. Assigning particular metabolic changes to specific drug regimens using metabonomics also remains to be done. Studies exist where identified metabolites have been linked to various disease states suggesting great potential for the use of metabonomics in disease prognostics. This review therefore examines the field of metabonomics in the context of HIV/AIDS, comments on metabolites routinely detected as being affected by the pathogen or treatment, explains what existing data suggest and makes recommendations on future research.

Background: The synergy between the human immunodeficiency virus (HIV) and Mycobacterium tuberculosis during co-infection of a host is well known. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms that contribute to the associated disease burden experienced during HIV/tuberculosis (TB) co-infection remain poorly understood. Furthermore, while anti-HIV treatments suppress viral replication, these therapeutics give rise to host metabolic disruption and adaptations beyond that induced by only infection or disease. Methods: In this study, the serum metabolic profiles of healthy controls, untreated HIV-negative TB-positive patients, untreated HIV/TB co-infected patients, and HIV/TB co-infected patients on antiretroviral therapy (ART), were measured using two-dimensional gas chromatography time-of-flight mass spectrometry. Since no global metabolic profile for HIV/TB co-infection and the effect of ART has been published to date, this pilot study aimed to elucidate the general areas of metabolism affected during such conditions. Results: HIV/TB co-infection induced significant changes to the host’s lipid and protein metabolism, with additional microbial product translocation from the gut to the blood. The results suggest that HIV augments TB synergistically, at least in part, contributing to increased inflammation, oxidative stress, ART-induced mitochondrial damage, and its detrimental effects on gut health, which in turn, affects energy availability. ART reverses these trends to some extent in HIV/TB co-infected patients but not to that of healthy controls. Conclusion: This study generated several new hypotheses that could direct future metabolic studies, which could be combined with other research techniques or methodologies to further elucidate the underlying mechanisms of these changes.

The HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) and tuberculosis (TB) pandemics are perpetuated by a significant global burden of HIV/TB co-infection. The synergy between HIV and Mycobacterium tuberculosis (Mtb) during co-infection of a host is well established. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms thereof remain poorly understood. Metabolomics has been applied to study various aspects of HIV and Mtb infection separately, yielding insights into infection- and treatment-induced metabolic adaptations experienced by the host. Despite the contributions that metabolomics has made to the field, this approach has not yet been systematically applied to characterize the HIV/TB co-infected state. Considering that limited HIV/TB co-infection metabolomics studies have been published to date, this review briefly summarizes what is known regarding the HIV/TB co-infection synergism from a conventional and metabolomics perspective. It then explores metabolomics as a tool for the improved characterization of HIV/TB co-infection in the context of previously published human-related HIV infection and TB investigations, respectively as well as for addressing the gaps in existing knowledge based on the similarities and deviating trends reported in these HIV infection and TB studies.