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Blattner, R.

Publications and source records attributed to Blattner, R..

2 recordsLinked to original sources

Compost bacteria as a promising new solution for degradation of diclofenac and related pharmaceuticals for water treatment processes

Diclofenac, a widely used pharmaceutical, poses a significant environmental problem due to its persistence in aquatic systems and resistance to conventional degradation processes. Mesophilic microorganisms, commonly employed in wastewater treatment, often struggle to break down diclofenac, necessitating alternative approaches for its removal. In this study, we investigated thermophilic compost microorganisms and their ability to degrade diclofenac. Compost communities were cultivated for 20 weeks at 50{degrees}C in a membrane bioreactor, with a continuous supply of 2 mg/L diclofenac as the sole carbon source. After two weeks, the microbial community steadily enhanced its ability to remove diclofenac, achieving removal rates up to 60%. The consortium demonstrated flexibility in the degradation of further pollutants, namely sulfamethoxazole, paracetamol, and ciprofloxacin, with changes in their community structure depending on the substrates. In addition, thermophilic isolates Chelatococcus sp. strain D3 and Mycobacterium sp. strain D1 were characterized and demonstrated variation in the first reaction of transforming diclofenac, which is the crucial step in mineralization of this pollutant, resulting in either 4-hydroxy-diclofenac or diclofenac-lactam, respectively. Furthermore, Chelotococcus sp. strain D3 demonstrated the capability to catalyze the biotransformation of diclofenac into 4-hydroxydiclofenac in treated wastewater. Notably, this transformation was effectively carried out even at lower temperatures (25 {degrees}C and 37{degrees}C). These results show that the use of thermophilic consortia can be applied for efficient bioremediation in wastewater treatment plants, specifically for compounds that mesophilic organisms degrade poorly.

microbiology↗

Optimization and scaling of patient-derived brain organoids uncovers deep phenotypes of disease

Cerebral organoids provide unparalleled access to human brain development in vitro. However, variability induced by current culture methodologies precludes using organoids as robust disease models. To address this, we developed an automated Organoid Culture and Assay (ORCA) system to support longitudinal unbiased phenotyping of organoids at scale across multiple patient lines. We then characterized organoid variability using novel machine learning methods and found that the contribution of donor, clone, and batch is significant and remarkably consistent over gene expression, morphology, and cell-type composition. Next, we performed multi-factorial protocol optimization, producing a directed forebrain protocol compatible with 96-well culture that exhibits low variability while preserving tissue complexity. Finally, we used ORCA to study tuberous sclerosis, a disease with known genetics but poorly representative animal models. For the first time, we report highly reproducible early morphological and molecular signatures of disease in heterozygous TSC+/- forebrain organoids, demonstrating the benefit of a scaled organoid system for phenotype discovery in human disease models.

neuroscience↗