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A Streptomyces strain MS-6-6 with promising anti-tuberculous activity was isolated from soil samples in Saudi Arabia. The nucleotide sequence of its 16S rRNA gene (1426 bp) evidenced a 100% similarity to Streptomyces mutabilis. Through an anti-tuberculous activity-guided approach, a polyketide macrolide was isolated and identified as treponemycin (TP). The structure of the isolated compound was determined by comprehensive analyses of its 1D and 2D NMR as well as HRESI-MS. In addition to the promising anti-tuberculous activity (MIC = 13.3 µg/mL), TP showed broad spectrum of activity against the Gram positive, Gram negative strains, and Candida albicans. Improvement of TP productivity (150%) was achieved through modification in liquid starch nitrate medium by replacing KNO3 with corn steep liquor and yeast extract or tryptone, and removing CaCO3 and K2HPO4. The follow up of TP percentage as well as its metabolites profile for each media was assessed by LC/DAD/MS.

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Background: Chemometrics is a discipline that allows the spectral resolution of drugs in a complicated matrix (e.g., environmental water samples) as an alternative to chromatographic methods. Objective: Three analgesics were traced in wastewater samples with simple and cost-effective multivariate approaches using spectrophotometric data. Methods and Results: Four chemometric approaches were applied for the simultaneous determination of diclofenac, paracetamol, and ibuprofen. Partial least squares (PLS), principal component regression (PCR), artificial neural networks (ANN), and multivariate curve resolution (MCR)–alternating least squares (ALS) were selected. The presented methods were compared and validated for their qualitative and quantitative analyses. Moreover, statistical comparison between the results obtained by the proposed methods and the official methods showed no significant differences. Conclusions: The proposed multivariate calibrations were accurate and specific for quantitative analysis of the studied components. MCR-ALS is the only method that has the capacity for both the quantitative and qualitative analysis of the studied drugs. Highlights: Four chemometric approaches were used for analysis of severally overlapped ternary mixture of three analgesics. The analytical performance of PCR, PLS, MCR-ALS, and ANN was compared and validated in terms of root mean square error of calibration (RMSEC), SE of prediction, and recoveries. ANN gave the highest predicted concentrations with the lowest RMSEC and root mean square error of prediction. MCR-ALS has the capacity for both qualitative and quantitative measurement. The methods have been effectively applied for real samples and compared to official methods.