Tuberculous meningitis in infants and children: Insights from nuclear magnetic resonance metabolomics

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12 years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

CSF Metabolomics of Tuberculous Meningitis: A Review

From the World Health Organization's global TB report for 2020, it is estimated that in 2019 at least 80,000 children (a particularly vulnerable population) developed tuberculous meningitis (TBM)-an invariably fatal disease if untreated-although this is likely an underestimate. As our latest technologies have evolved-with the unprecedented development of the various "omics" disciplines-a mountain of new data on infectious diseases have been created. However, our knowledge and understanding of infectious diseases are still trying to keep pace. Metabolites offer much biological information, but the insights they permit can be difficult to derive. This review summarizes current metabolomics studies on cerebrospinal fluid (CSF) from TBM cases and collates the metabolic data reported. Collectively, CSF metabolomics studies have identified five classes of metabolites that characterize TBM: amino acids, organic acids, nucleotides, carbohydrates, and "other". Taken holistically, the information given in this review serves to promote the mechanistic action of hypothesis generation that will drive and direct future studies on TBM.

Mass spectrometry-based metabolomics for tuberculosis meningitis

Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described.