PEGylated ofloxacin nanoparticles render strong antibacterial activity against many clinically important human pathogens.

The rise of bacterial resistance against important drugs threatens their clinical utility. Fluoroquinones, one of the most important classes of contemporary antibiotics has also reported to suffer bacterial resistance. Since the general mechanism of bacterial resistance against fluoroquinone antibiotics (e.g. ofloxacin) consists of target mutations resulting in reduced membrane permeability and increased efflux by the bacteria, strategies that could increase bacterial uptake and reduce efflux of the drug would provide effective treatment. In the present study, we have compared the efficiencies of ofloxacin delivered in the form of free drug (OFX) and as nanoparticles on bacterial uptake and antibacterial activity. Although both poly(lactic-co-glycolic acid) (OFX-PLGA) and methoxy poly(ethylene glycol)-b-poly(lactic-co-glycolic acid) (OFX-mPEG-PLGA) nanoformulations presented improved bacterial uptake and antibacterial activity against all the tested human bacterial pathogens, namely, Escherichia coli, Proteus vulgaris, Salmonella typhimurium, Pseudomonas aeruginosa, Klebsiella pneumoniae and Staphylococcus aureus, OFX-mPEG-PLGA showed significantly higher bacterial uptake and antibacterial activity compared to OFX-PLGA. We have also found that mPEG-PLGA nanoencapsulation could significantly inhibit Bacillus subtilis resistance development against OFX.

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

Construction of an innocuous Salmonella phage

Dissertação de mestrado em Bioengenharia

Influence of oxygen conditions on bacterial interactions within biofilms related with cystic fibrosis

Dissertação de mestrado em Bioengineering

Evaluation of antimicrobial strategies against biomaterial-associated infections: impact of the surrounding environmental conditions

Dissertação de mestrado em Bioengenharia