Genome-scale analyses of health-promoting bacteria: probiogenomics

The human body is colonized by an enormous population of bacteria (microbiota) that provides the host with coding capacity and metabolic activities. Among the human gut microbiota are health-promoting indigenous species (probiotic bacteria) that are commonly consumed as live dietary supplements. Recent genomics-based studies (probiogenomics) are starting to provide insights into how probiotic bacteria sense and adapt to the gastrointestinal tract environment. In this Review, we discuss the application of probiogenomics in the elucidation of the molecular basis of probiosis using the well-recognized model probiotic bacteria genera Bifidobacterium and Lactobacillus as examples.

On classical and other methods of discriminant analysis and estimation of log-odds

For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.

Mutational and molecular analyses of lactococcal bacteriophages TP901-1 and Tuc2009

Bacteriophages belonging to the Siphoviridae family represent viruses with a noncontractile tail that function as extremely efficient bacterium-infecting nanomachines. The Siphoviridae phages TP901-1 and Tuc2009 infect Lactococcus lactis, and both belong to the so-called P335 species. As P335 phages are typically capable of a lytic and lysogenic life cycle, a number of molecular tools are available to analyse their virions. This doctoral thesis describes mutational and molecular analyses of TP901-1 and Tuc2009, with emphasis on the role of their tail-associated structural proteins. Several novel and intriguing findings discovered during the course of this study on the nature of Siphoviridae phages furthers a basic molecular understanding of their virions, and the role of their virion proteins, during the initial stages of infection. While Siphoviridae virions represent complex quaternary structures of multiple proteins and subunits thereof, mutagenic analysis represents an efficient mechanism to discretely characterize the function of individual proteins, and constituent amino acids, in the assembly of the phage structure and their biological function. However, as always, more research is required to delve deeper into the mechanisms by which phages commence infection. This is important to advance our understanding of this intricate process and to facilitate application of such findings to manipulate phage infections. On the one hand, we may want to prevent phages from infecting starter cultures used in the dairy industry, while on the other hand it may be desirable to optimize viral infection for the application of phages as bacterial parasites and therapeutic agents.