A metagenomic analysis for combination therapy of multiple classes of antibiotics on the prevention of the spread of antibiotic-resistant genes.

Antibiotics used systemically to treat infections may have off-target effects on the gut microbiome, potentially resulting in the emergence of drug-resistant bacteria or selection of pathogenic species. These organisms may present a risk to the host and spread to the environment with a risk of transmission in the community. To investigate the risk of emergent antibiotic resistance in the gut microbiome following systemic treatment with antibiotics, this metagenomic analysis project used next-generation sequencing, a custom-built metagenomics pipeline, and differential abundance analysis to study the effect of antibiotics (ampicillin, ciprofloxacin, and fosfomycin) in monotherapy and different combinations at high and low doses, to determine the effect on resistome and taxonomic composition in the gut of Balb/c mice. The results showed that low-dose monotherapy treatments showed little change in microbiome composition but did show an increase in expression of many antibiotic-resistant genes (ARGs) posttreatment. Dual combination treatments allowed the emergence of some conditionally pathogenic bacteria and some increase in the abundance of ARGs despite a general decrease in microbiota diversity. Triple combination treatment was the most successful in inhibiting emergence of relevant opportunistic pathogens and completely suppressed all ARGs after 72 h of treatment. The relative abundances of mobile genetic elements that can enhance transmission of antibiotic resistance either decreased or remained the same for combination therapy while increasing for low-dose monotherapy. Combination therapy prevented the emergence of ARGs and decreased bacterial diversity, while low-dose monotherapy treatment increased ARGs and did not greatly change bacterial diversity.

Biological removal of nitrate by an oil reservoir culture capable of autotrophic and heterotrophic activities: kinetic evaluation and modeling of heterotrophic process.

Kinetics of heterotrophic denitrification was investigated using an oil reservoir culture with the ability to function under both autotrophic and heterotrophic conditions. In the batch system nitrate at concentrations up to 30 mM did not influence the kinetics but with 50mM slower growth and removal rates were observed. A kinetic model, representing the denitrification as reduction of nitrate to nitrite, and subsequent reduction of nitrite to nitrous oxides and nitrogen gas was developed. The value of various kinetic coefficients, including maximum specific growth rate, saturation constant, yield and activation energy for nitrate and nitrite reductions were determined by fitting the experimental data into the developed model. In continuous bioreactors operated with 10 or 30 mM nitrate, complete removal of nitrate (no residual nitrite) and linear dependency between nitrate loading and removal rates were observed for loading rates up to 0.21 and 0.58 mM h(-1), respectively. The highest removal rates of 0.31 and 0.94 mM h(-1) observed at loading rates of 0.42 mM h(-1) and 1.26 mM h(-1), with corresponding removal percentages of nitrate and total nitrogen being 75.4, 54.4%, and 74.4 and 17.9%, respectively. Developed kinetic model predicted the performance of the continuous bioreactors with accuracy.