Surface microbial consortia from Livarot, a French smear-ripened cheese

The surface microflora (902 isolates) of Livarot cheeses from three dairies was investigated during ripening. Yeasts were mainly identified by Fourier transform infrared spectroscopy. Geotrichum candidum was the dominating yeast among 10 species. Bacteria were identified using Biotype 100 strips, dereplicated by repetitive extragenic palindromic PCR (rep-PCR); 156 representative strains were identified by either BOX-PCR or (GTG) 55-PCR, and when appropriate by 16S rDNA sequencing and SDS-PAGE analysis. Gram-positive bacteria accounted for 65% of the isolates and were mainly assigned to the genera Arthrobacter, Brevibacterium, Corynebacterium, and Staphylococcus. New taxa related to the genera Agrococcus and Leucobacter were found. Yeast and Gram-positive bacteria strains deliberately added as smearing agents were sometimes undetected during ripening. Thirty-two percent of the isolates were Gram-negative bacteria, which showed a high level of diversity and mainly included members of the genera Alcaligenes, Hafnia, Proteus, Pseudomonas, and Psychrobacter. Whatever the milk used (pasteurized or unpasteurized), similar levels of biodiversity were observed in the three dairies, all of which had efficient cleaning procedures and good manufacturing practices. It appears that some of the Gramnegative bacteria identified should now be regarded as potentially useful in some cheese technologies. The assessment of their positive versus negative role should be objectively examined.

The microbiology of the eye

Infection of the external structures of the eye is one of the commonest types of eye disease worldwide. In addition, although relatively impermeable to microorganisms, infection within the eye can result from trauma, surgery or systemic disease. This article reviews the general biology of viruses, bacteria, fungi and protozoa and the major ocular infections that they cause. In addition, the effectiveness of the various antimicrobial agents in controlling ocular disease is discussed. Because of changes in the normal ocular flora, continuous monitoring of the microbiology of the eye will continue to be important in predicting future types of eye infection. Basic research is also needed into the interactions of microbes at the ocular surface. There is increasing microbial resistance to the antimicrobial agents used to treat ocular infections and hence, new antimicrobial agents will continue to be needed together with new methods of drug delivery to increase the effectiveness of existing antimicrobial agents.

The use of analysis of variance (ANOVA) in applied microbiology

Experiments combining different groups or factors and which use ANOVA are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the number of replications required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the DF of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for each error term of the ANOVA. Finally, it is important to consider the design of the experiment because this determines the appropriate ANOVA to use. Some of the most common experimental designs used in the biosciences and their relevant ANOVAs are discussed by. If there is doubt about which ANOVA to use, the researcher should seek advice from a statistician with experience of research in applied microbiology.

Statistical analysis in microbiology:statnotes

This book is aimed primarily at microbiologists who are undertaking research and who require a basic knowledge of statistics to analyse their experimental data. Computer software employing a wide range of data analysis methods is widely available to experimental scientists. The availability of this software, however, makes it essential that investigators understand the basic principles of statistics. Statistical analysis of data can be complex with many different methods of approach, each of which applies in a particular experimental circumstance. Hence, it is possible to apply an incorrect statistical method to data and to draw the wrong conclusions from an experiment. The purpose of this book, which has its origin in a series of articles published in the Society for Applied Microbiology journal ‘The Microbiologist’, is an attempt to present the basic logic of statistics as clearly as possible and therefore, to dispel some of the myths that often surround the subject. The 28 ‘Statnotes’ deal with various topics that are likely to be encountered, including the nature of variables, the comparison of means of two or more groups, non-parametric statistics, analysis of variance, correlating variables, and more complex methods such as multiple linear regression and principal components analysis. In each case, the relevant statistical method is illustrated with examples drawn from experiments in microbiological research. The text incorporates a glossary of the most commonly used statistical terms and there are two appendices designed to aid the investigator in the selection of the most appropriate test.

Contrast summation across eyes and space is revealed along the entire dipper function by a "Swiss cheese" stimulus.

Previous contrast discrimination experiments have shown that luminance contrast is summed across ocular (T. S. Meese, M. A. Georgeson, & D. H. Baker, 2006) and spatial (T. S. Meese & R. J. Summers, 2007) dimensions at threshold and above. However, is this process sufficiently general to operate across the conjunction of eyes and space? Here we used a "Swiss cheese" stimulus where the blurred "holes" in sine-wave carriers were of equal area to the blurred target ("cheese") regions. The locations of the target regions in the monocular image pairs were interdigitated across eyes such that their binocular sum was a uniform grating. When pedestal contrasts were above threshold, the monocular neural images contained strong evidence that the high-contrast regions in the two eyes did not overlap. Nevertheless, sensitivity to dual contrast increments (i.e., to contrast increments in different locations in the two eyes) was a factor of ∼1.7 greater than to single increments (i.e., increments in a single eye), comparable with conventional binocular summation. This provides evidence for a contiguous area summation process that operates at all contrasts and is influenced little, if at all, by eye of origin. A three-stage model of contrast gain control fitted the results and possessed the properties of ocularity invariance and area invariance owing to its cascade of normalization stages. The implications for a population code for pattern size are discussed.