Genetic studies on mitochondrially inherited mikamycin-resistance in Paramecium aurelia

Summary Mutants of Paramecium aurelia resistant to mikamycin were shown by microinjection experiments to be due to changes in the extranuclear, mitochondrial genetic system. These mutants were also resistant to a low concentration of erythromycin.Double mutants, resistant to a high level of erythromycin and to mikamycin, were obtained by a two-stage mutation-like process. Injection of mitochondria from these resulted in transformation to the double mutant type, irrespective of the selective medium used to obtain the transformants.     

Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

In this study, host-associated molecular markers and bacterial 16S rRNA gene community analysis using high-throughput sequencing were used to identify the sources of fecal pollution in environmental waters in Brisbane, Australia. A total of 92 fecal and composite wastewater samples were collected from different host groups (cat, cattle, dog, horse, human, and kangaroo), and 18 water samples were collected from six sites (BR1 to BR6) along the Brisbane River in Queensland, Australia. Bacterial communities in the fecal, wastewater, and river water samples were sequenced. Water samples were also tested for the presence of bird-associated (GFD), cattle-associated (CowM3), horse-associated, and human-associated (HF183) molecular markers, to provide multiple lines of evidence regarding the possible presence of fecal pollution associated with specific hosts. Among the 18 water samples tested, 83%, 33%, 17%, and 17% were real-time PCR positive for the GFD, HF183, CowM3, and horse markers, respectively. Among the potential sources of fecal pollution in water samples from the river, DNA sequencing tended to show relatively small contributions from wastewater treatment plants (up to 13% of sequence reads). Contributions from other animal sources were rarely detected and were very small (<3% of sequence reads). Source contributions determined via sequence analysis versus detection of molecular markers showed variable agreement. A lack of relationships among fecal indicator bacteria, host-associated molecular markers, and 16S rRNA gene community analysis data was also observed. Nonetheless, we show that bacterial community and host-associated molecular marker analyses can be combined to identify potential sources of fecal pollution in an urban river. This study is a proof of concept, and based on the results, we recommend using bacterial community analysis (where possible) along with PCR detection or quantification of host-associated molecular markers to provide information on the sources of fecal pollution in waterways.