Quantifying community-wide antibiotic usage via urban water fingerprinting: Focus on contrasting resource settings in South Africa.

There has been a significant increase in antimicrobial agents (AAs) usage, globally - however the relative consumption is unevenly distributed between nations. Inappropriate use of antibiotics can harbour inherent antimicrobial resistance (AMR); therefore, it is important to understand and monitor community-wide prescribing and consumption behaviours throughout different communities around the world. Wastewater-Based Epidemiology (WBE) is a novel tool enabling low cost and large scale studies focussed on AA usage patterns. The back-calculation of community antimicrobial intake was performed from quantities measured in municipal wastewater and informal settlement discharge in the city of Stellenbosch, utilising WBE. Seventeen antimicrobials, and their human metabolites, were evaluated, in concordance with prescription records corresponding to the catchment region. The proportional excretion, biological/chemical stability, and method recovery of each analyte were all crucial factors in the efficacy of the calculation. Mass per day measurements were normalised to the catchment area via population estimates. Municipal wastewater treatment plant population estimates were used to normalise the wastewater samples and prescription data (mg/day/1000 inhabitants). Population estimates for the informal settlements were less accurate due to a lack of reliable sources that were relevant to the sampling time period. Both mass loads and normalised loads suggested higher than average usage throughout the settlements, relative to municipal wastewater. This was seen most prominently in emtricitabine and lamivudine; but also, sulfamethoxazole, trimethoprim, sulfadiazine, clindamycin, ciprofloxacin, ofloxacin, and doxycycline. Urban water fingerprinting (UWF) data triangulation with prescription datasets showed good correlations for several antimicrobial agents (AAs) (e.g., clindamycin, clarithromycin, ofloxacin, and doxycycline). It also revealed discrepancies in usage for some compounds (e.g., tetracycline and sulfapyridine). This might be linked with a lack of pharma compliance in prescription datasets; erroneous association of prescription boundaries with the sewerage catchment; and/or uncertainties within the sewerage catchment (e.g., population estimations). The UWF tool provided a comprehensive overview of multiclass AAs usage, both prescription and over-the counter. For example, tetracycline was not reported in available prescription statistics, but was detected at an average of 18.4 mg/day/1000inh; and no antiviral prescriptions were obtained, but emtricitabine and lamivudine were quantified at 2415.4 and 144.4 mg/day/1000inh, respectively. A lack of clarity regarding prescriptions and a lack of inclusion of several critical (often over-the-counter) medications in public health databases makes WBE a useful and comprehensive epidemiology tool for tracking pharma usage within a catchment.

Computational modelling of the Δ4 and Δ5 adrenal steroidogenic pathways provides insight into hypocortisolism.

This study demonstrates the application of a mathematical steroidogenic model, constructed with individual in vitro enzyme characterisations, to simulate in vivo steroidogenesis in a diseased state. This modelling approach was applied to the South African Angora goat, that suffers from hypocortisolism caused by altered adrenal function. These animals are extremely vulnerable to cold stress, leading to substantial monetary loss in the mohair industry. The Angora goat has increased CYP17A1 17,20-lyase enzyme activity in comparison with hardy livestock species. Determining the effect of this altered adrenal function on adrenal steroidogenesis during a cold stress response is difficult. We developed a model describing adrenal steroidogenesis under control conditions, and under altered steroidogenic conditions where the animal suffers from hypocortisolism. The model is parameterised with experimental data from in vitro enzyme characterisations of a hardy control species. The increased 17,20-lyase activity of the Angora goat CYP17A1 enzyme was subsequently incorporated into the model and the response to physiological stress is simulated under both control and altered adrenal steroidogenic conditions.

The A-ring reduction of 11-ketotestosterone is efficiently catalysed by AKR1D1 and SRD5A2 but not SRD5A1.

Testosterone and its 5α-reduced form, 5α-dihydrotestosterone, were previously thought to represent the only active androgens in humans. However, recent studies have shown that the potent androgen, 11-ketotestosterone, derived from the adrenal androgen precursor, 11ß-hydroxyandrostenedione, may in fact serve as the primary androgen in healthy women. Yet, despite recent renewed interest in these steroids, their downstream metabolism has remained undetermined. We therefore set out to investigate the metabolism of 11-ketotestosterone by characterising the 5α- or 5ß-reduction commitment step. We show that inactivation of 11-ketotestosterone is predominantly driven by AKR1D1, which efficiently catalyses the 5ß-reduction of 11-ketotestosterone, committing it to a metabolic pathway that terminates in 11-ketoetiocholanolone. We demonstrate that 5α-reduction of 11-ketotestosterone is catalysed by SRD5A2, but not SRD5A1, and terminates in 11-ketoandrosterone, but is only responsible for a minority of 11-ketotestosterone inactivation. However, as 11-ketoetiocholanolone is also generated by the metabolism of the glucocorticoid cortisone, 11-ketoandrosterone should be considered a more specific urinary marker of 11-ketotestosterone production.