Publications by authors named "Rogelio E Zuniga-Montanez"
Article Synopsis
- Wastewater-based epidemiology (WBE) helps track COVID-19 trends and can complement clinical testing, but the relationship between wastewater and clinical data at smaller community levels is not well understood.
- The study, conducted in Davis, California, tests a new method combining the expectation maximization (EM) algorithm with Markov Chain Monte Carlo (MCMC) to better estimate missing data in wastewater testing compared to traditional nondetect methods.
- Results show that the new method may lead to better correlation between community-scale wastewater and clinical data, and the research proposes a way to integrate clinical and wastewater data on a more localized scale for improved public health monitoring.
New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes from complex microbial communities. Using long read data (ONT MinION) obtained from an ensemble of activated sludge enrichment bioreactors we recover 22 closed or complete genomes of community members, including several species known to play key functional roles in wastewater bioprocesses, specifically microbes known to exhibit the polyphosphate- and glycogen-accumulating organism phenotypes (namely Candidatus Accumulibacter and Dechloromonas, and Micropruina, Defluviicoccus and Candidatus Contendobacter, respectively), and filamentous bacteria (Thiothrix) associated with the formation and stability of activated sludge flocs. Additionally we demonstrate the recovery of close to 100 circularised plasmids, phages and small microbial genomes from these microbial communities using long read assembled sequence.
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