Dynamics and diversity of Escherichia coli in animals and system management of the manure on a commercial farrow-to-finish pig farm

The objective of this study was to determine the dynamics and diversity of Escherichia coli populations in animal and environmental lines of a commercial farrow-to-finish pig farm in Spain along a full production cycle (July 2008 to July 2009), with special attention to antimicrobial resistance and the presence of integrons. In the animal line, a total of 256 isolates were collected from pregnant sows (10 samples and 20 isolates), 1-week-old piglets (20 samples and 40 isolates), unweaned piglets (20 samples and 38 isolates), growers (20 samples and 40 isolates), and the finishers' floor pen (6 samples and 118 isolates); from the underfloor pits and farm slurry tank environmental lines, 100 and 119 isolates, respectively, were collected. Our results showed that E. coli populations in the pig fecal microbiota and in the farm environment are highly dynamic and show high levels of diversity. These issues have been proven through DNA-based typing data (repetitive extragenic palindromic PCR [REP-PCR]) and phenotypic typing data (antimicrobial resistance profile comprising 19 antimicrobials). Clustering of the sampling groups based on their REP-PCR typing results showed that the spatial features (the line) had a stronger weight than the temporal features (sampling week) for the clustering of E. coli populations; this weight was less significant when clustering was performed based on resistotypes. Among animals, finishers harbored an E. coli population different from those of the remaining animal populations studied, considering REP-PCR fingerprints and resistotypes. This population, the most important from a public health perspective, demonstrated the lowest levels of antimicrobial resistance and integron presence.

Automatic Counting of Microglial Cells in Healthy and Glaucomatous Mouse Retinas

Proliferation of microglial cells has been considered a sign of glial activation and a hallmark of ongoing neurodegenerative diseases. Microglia activation is analyzed in animal models of different eye diseases. Numerous retinal samples are required for each of these studies to obtain relevant data of statistical significance. Because manual quantification of microglial cells is time consuming, the aim of this study was develop an algorithm for automatic identification of retinal microglia. Two groups of adult male Swiss mice were used: age-matched controls (naïve, n = 6) and mice subjected to unilateral laser-induced ocular hypertension (lasered; n = 9). In the latter group, both hypertensive eyes and contralateral untreated retinas were analyzed. Retinal whole mounts were immunostained with anti Iba-1 for detecting microglial cell populations. A new algorithm was developed in MATLAB for microglial quantification; it enabled the quantification of microglial cells in the inner and outer plexiform layers and evaluates the area of the retina occupied by Iba-1+ microglia in the nerve fiber-ganglion cell layer. The automatic method was applied to a set of 6,000 images. To validate the algorithm, mouse retinas were evaluated both manually and computationally; the program correctly assessed the number of cells (Pearson correlation R = 0.94 and R = 0.98 for the inner and outer plexiform layers respectively). Statistically significant differences in glial cell number were found between naïve, lasered eyes and contralateral eyes (P<0.05, naïve versus contralateral eyes; P<0.001, naïve versus lasered eyes and contralateral versus lasered eyes). The algorithm developed is a reliable and fast tool that can evaluate the number of microglial cells in naïve mouse retinas and in retinas exhibiting proliferation. The implementation of this new automatic method can enable faster quantification of microglial cells in retinal pathologies.