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The genetic improvement of Lactococcus lactis is a matter of biotechnological interest in the food industry and in the pharmaceutical and medical fields. However, to construct a food-grade delivery system, both the presence of antibiotic markers or plasmid sequences should be avoided and the maintenance and expression of the cloned gene should be guaranteed. The objective of this work was to produce crossover mutants of L. lactis with a reporter gene under the control of an inducible promoter in order to evaluate the level of gene expression. We utilized a nuclease gene of Staphylococcus aureus as a reporter gene, P(nisA) as the nisin-inducible promoter, a non-essential gene involved in histidine biosynthesis of L. lactis as the site for homologous recombination, and pRV300 as a suicide vector for the genomic integration in L. lactis NZ9000. Single- and double-crossover mutants were identified by genotype and phenotype. Relative to episomal transformants of L. lactis, the level of expression of the heterologous protein after nisin induction was similar in the crossover mutants, suggesting that a single copy of the heterologous gene can be used to produce the protein of interest.

Polycyclic aromatic (46 PAHs) and aliphatic hydrocarbons (C12-C40) were studied in atmospheric particulate matter sampled in Rio de Janeiro Metropolitan Area (RJMA). In total, 236 samples from six different sites were collected simultaneously and weekly over 1 year (January-December 2011) allowing a robust atmospheric characterization of fine particulate matter (PM2.5). Hydrocarbon concentration was in general low compared to previous studies in the area (PAHs range 0.25-19.3 ng m(-3)), possibly due to changes in fuel composition over time. Precipitation is the main meteorological parameter that rules particulate and hydrocarbon concentration, modifying PAH typology by scavenging. Aliphatic and aromatic diagnostic ratios gave indications conflicting with combustion features. However, ratios showed differences among sites. Principal component analysis (PCA) associated to multiple linear regressions (MLR) allowed quantitative estimate of sources and effectively indicated vehicular emission as the main hydrocarbon source in the atmospheric particulate matter.

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