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.

Paediatric monkeypox patient with unknown source of infection, the Netherlands, June 2022.

Since May 2022, an international monkeypox (MPX) outbreak has been ongoing in more than 50 countries. While most cases are men who have sex with men, transmission is not restricted to this population. In this report, we describe the case of a male child younger than 10 years with MPX in the Netherlands. Despite thorough source tracing, a likely source of infection has not been identified. No secondary cases were identified in close contacts.

Tuberculous Granuloma: Emerging Insights From Proteomics and Metabolomics.

Mycobacterium tuberculosis infection, which claims hundreds of thousands of lives each year, is typically characterized by the formation of tuberculous granulomas - the histopathological hallmark of tuberculosis (TB). Our knowledge of granulomas, which comprise a biologically diverse body of pro- and anti-inflammatory cells from the host immune responses, is based mainly upon examination of lungs, in both human and animal studies, but little on their counterparts from other organs of the TB patient such as the brain. The biological heterogeneity of TB granulomas has led to their diverse, relatively uncoordinated, categorization, which is summarized here. However, there is a pressing need to elucidate more fully the phenotype of the granulomas from infected patients. Newly emerging studies at the protein (proteomics) and metabolite (metabolomics) levels have the potential to achieve this. In this review we summarize the diverse nature of TB granulomas based upon the literature, and amplify these accounts by reporting on the relatively few, emerging proteomics and metabolomics studies on TB granulomas. Metabolites (for example, trimethylamine-oxide) and proteins (such as the peptide PKAp) associated with TB granulomas, and knowledge of their localizations, help us to understand the resultant phenotype. Nevertheless, more multidisciplinary 'omics studies, especially in human subjects, are required to contribute toward ushering in a new era of understanding of TB granulomas - both at the site of infection, and on a systemic level.

Overview of Brain-to-Gut Axis Exposed to Chronic CNS Bacterial Infection(s) and a Predictive Urinary Metabolic Profile of a Brain Infected by Mycobacterium tuberculosis.

A new paradigm in neuroscience has recently emerged - the brain-gut axis (BGA). The contemporary focus in this paradigm has been gut → brain ("bottom-up"), in which the gut-microbiome, and its perturbations, affects one's psychological state-of-mind and behavior, and is pivotal in neurodegenerative disorders. The emerging brain → gut ("top-down") concept, the subject of this review, proposes that dysfunctional brain health can alter the gut-microbiome. Feedback of this alternative bidirectional highway subsequently aggravates the neurological pathology. This paradigm shift, however, focuses upon non-communicable neurological diseases (progressive neuroinflammation). What of infectious diseases, in which pathogenic bacteria penetrate the blood-brain barrier and interact with the brain, and what is this effect on the BGA in bacterial infection(s) that cause chronic neuroinflammation? Persistent immune activity in the CNS due to chronic neuroinflammation can lead to irreversible neurodegeneration and neuronal death. The properties of cerebrospinal fluid (CSF), such as immunological markers, are used to diagnose brain disorders. But what of metabolic markers for such purposes? If a BGA exists, then chronic CNS bacterial infection(s) should theoretically be reflected in the urine. The premise here is that chronic CNS bacterial infection(s) will affect the gut-microbiome and that perturbed metabolism in both the CNS and gut will release metabolites into the blood that are filtered (kidneys) and excreted in the urine. Here we assess the literature on the effects of chronic neuroinflammatory diseases on the gut-microbiome caused by bacterial infection(s) of the CNS, in the context of information attained via metabolomics-based studies of urine. Furthermore, we take a severe chronic neuroinflammatory infectious disease - tuberculous meningitis (TBM), caused by Mycobacterium tuberculosis, and examine three previously validated CSF immunological biomarkers - vascular endothelial growth factor, interferon-gamma and myeloperoxidase - in terms of the expected changes in normal brain metabolism. We then model the downstream metabolic effects expected, predicting pivotal altered metabolic pathways that would be reflected in the urinary profiles of TBM subjects. Our cascading metabolic model should be adjustable to account for other types of CNS bacterial infection(s) associated with chronic neuroinflammation, typically prevalent, and difficult to distinguish from TBM, in the resource-constrained settings of poor communities.