Operon structure of Staphylococcus aureus

In bacteria, gene regulation is one of the fundamental characteristics of survival, colonization and pathogenesis. Operons play a key role in regulating expression of diverse genes involved in metabolism and virulence. However, operon structures in pathogenic bacteria have been determined only by in silico approaches that are dependent on factors such as intergenic distances and terminator/promoter sequences. Knowledge of operon structures is crucial to fully understand the pathophysiology of infections. Presently, transcriptome data obtained from growth curves in a defined medium were used to predict operons in Staphylococcus aureus. This unbiased approach and the use of five highly reproducible biological replicates resulted in 93.5% significantly regulated genes. These data, combined with Pearson’s correlation coefficients of the transcriptional profiles, enabled us to accurately compile 93% of the genome in operon structures. A total of 1640 genes of different functional classes were identified in operons. Interestingly, we found several operons containing virulence genes and showed synergistic effects for two complement convertase inhibitors transcribed in one operon. This is the first experimental approach to fully identify operon structures in S. aureus. It forms the basis for further in vitro regulation studies that will profoundly advance the understanding of bacterial pathophysiology in vivo

The detection and estimation of long memory in stochastic volatility

We propose a new time series representation of persistence in conditional variance called a long memory stochastic volatility (LMSV) model. The LMSV model is constructed by incorporating an ARFIMA process in a standard stochastic volatility scheme. Strongly consistent estimators of the parameters of the model are obtained by maximizing the spectral approximation to the Gaussian likelihood. The finite sample properties of the spectral likelihood estimator are analyzed by means of a Monte Carlo study. An empirical example with a long time series of stock prices demonstrates the superiority of the LMS

Discovering lactic acid bacteria bygenomics

Low-moisture part-skim Mozzarella cheeses were manufactured from 2% fat milk and aged for 21 d. Treatments included cheeses made with one of three different strains of Lactobacillus delbrueckii ssp. bulgaricus in combination with a single strain of Streptococcus thermophilus. A fourth, control treatment consisted of cheeses made with only S. thermophilus. Although total proteolytic ability of these strains, as indicated by the o-phthaldialdehyde analysis, was similar in each of the three strains of L. bulgaricus, these strains exhibited different proteolytic specificities toward the peptide, αs1-CN (f 1-23). On the basis of their αs1-CN (f 1-23) cleavage patterns and a previously described classification, these strains were assigned to the groups I, III, and V. The objective of this study was to investigate the influence of lactobacilli proteolytic systems, based on specificity toward αs1-CN (f 1-23), on functionality of part-skim Mozzarella cheese. Moisture, fat, protein, salt-in-moisture, and moisture in nonfat substances content of cheeses made with groups I, III, and V strain were similar. Control cheese had a lower moisture content than did other treatments. Significant differences were observed in functional properties between cheeses manufactured using groups III and V strains. Cheeses made with groups I and III strains were similar in their meltability, hardness, cohesiveness, melt strength, and stretch quality. Meltability and cohesiveness increased with age, while melt strength and stretch quality decreased with age for all cheeses. Additionally, HPLC showed that total peak areas of water-soluble peptides derived from cleavage of αs1-CN (f 1-23) by different strains of lactobacilli could be highly correlated to meltability and stretch characteristics of cheeses made with those strains