Granular activated sludge has been described as a promising tool in treating wastewater. However, the effect of high concentrations of sulphur amino acids, cysteine and methionine, in the evolution, development and stability of AGS-SBRs (aerobic granular sludge in sequential batch reactors) and their microbial communities is not well-established. Therefore, this study aimed to evaluate microbial communities' size, structure and dynamics in two AGS-SBRs fed with two different concentrations of amino acids (50 and 100 mg L−1 of both amino acids). In addition, the impact of the higher level of amino acids was also determined under an acclimatization or shock strategy. While N removal efficiency decreased with amino acids, the removal of the organic matter was generally satisfactory. Moreover, the abrupt presence of both amino acids reduced even further the removal performance of N, whereas under progressive adaptation, the removal yield was higher. Besides, excellent removal rates of cysteine and methionine elimination were found, in all stages below 80% of the influent values. Generally considered, the addition of amino acids weakly impacts the microbial communities' total abundances. On the contrary, the presence of amino acids sharply modulated the dominant bacterial structures. Furthermore, the highest amino acid concentration under the shock strategy resulted in a severe change in the structure of the microbial community. Acidovorax, Flavobacterium, Methylophilus, Stenotrophomonas and Thauera stood out as the prominent bacteria to cope with the high presence of cysteine and methionine. Hence, the AGS-SBR technology is valuable for treating influents enriched in sulphur Aa inclusively when a shock strategy was used.

The high prevalence of antibiotic resistant bacteria (ARB) in several environments is a great concern threatening human health. Hence, it is vital to dispose of molecular tools that allow proper monitoring of antibiotic resistant genes (ARGs) encoding resistances to these important therapeutic compounds. For an accurate quantification of ARGs, there is a need for sensitive and robust qPCR assays supported by a good design of primers and validated protocols. In this study, eleven relevant ARGs were selected as targets, including aadA and aadB (conferring resistance to aminoglycosides), ampC, blaTEM, blaSHV, and mecA (resistance to beta-lactams); dfrA1 (resistance to trimethoprim); ermB (resistance to macrolides); fosA (resistance to fosfomycin); qnrS (resistance to quinolones); and tetA(A) (resistance to tetracyclines). The in silico design of the new primer sets was performed based on the alignment of all the sequences of the target ARGs (orthology grade > 70%) deposited in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, allowing higher coverages of the ARG’s biodiversity than those of several primers described to date. The adequate design and well performance of the new molecular tools were validated in vivo in six samples, retrieved from both natural and engineered environments. The hallmarks of the optimized qPCR assays were high amplification efficiency (> 90%), good linearity of the standard curve (R2 > 0.980), consistency across replicate experiments, and a wide dynamic range. The new methodology described here provide valuable tools to upgrade the monitorization of the abundance and emergence of the targeted ARGs in the environment by qPCR.