Statistical analysis and biological interpretation of the flow cytometric heterogeneity observed in bacterial axenic cultures

Skew-Laplace distribution in Gram-negative bacterial axenic cultures: new insights into intrinsic cellular heterogeneity

“…Another biological interpretation refers to the two independent subpopulations detected by the Laplace distribution. The Laplace fitting confirms that bacterial axenic cultures are made up of two subpopulations, as reported previously by others (Koch, 1987;Ló pez-Amoró s et al, 1994;Vives-Rego et al, 2003;Wagensberg et al, 1988). In addition, the Laplace fitting shows that the distributions of the two subpopulations are mutually independent.…”

“…This statistic can be interpreted as the critical sample size required to just detect a lack of fit at the 5 % level. The critical size, N crit , is a statistic based on the x 2 goodness-of-fit test, which, as we have shown (Vives-Rego et al, 2003), is more appropriate in our context (flow-cytometer or Multisizer II data) than other tests of goodness of fit, such as Kolmogorov. A comprehensive description of goodness-of-fit tests was described by Conover (1971).…”

“…Specifically, the unsuitability of the normal distribution to describe bacterialsize distribution in axenic cultures has been reported repeatedly (Koch, 1987;Vives-Rego et al, 1994;Wagensberg et al, 1988). More recently, the intrinsic cellular heterogeneity of bacterial axenic cultures has been substantiated through flow cytometry and advanced statistical analyses (Vives-Rego et al, 2003).…”

The establishment of critical control points at the washing and air chilling stages in poultry meat production using multivariate statistics

“…The Kolmogorov-Smirnov-Lilliefors test was used to evaluate the normality of every microbiological variable transformed at each stage, obtaining the results shown in Table 1. This table shows the values of D max which indicate the difference between the sampled and theoretical distribution (Martín, 2001;StatSoft, 2002;Vives-Rego, Resina, Comas, Loren, & Juliá, 2003) and it can be seen that these values are not significant (p < 0.05) in all cases. In other words, the difference is not significant (p < 0.05) and therefore the data show a normal distribution since null hypothesis is accepted (H 0 = normal distribution of samples).…”

Differences in stationary-phase cells of a commercial Saccharomyces cerevisiae wine yeast grown in aerobic and microaerophilic batch cultures assessed by electric particle analysis, light diffraction and flow cytometry

“…These uses include indirect assessment of size distribution in the population and study of its statistical characteristics [13][14][15]30], development of protocols to distinguish between normal and arrested fermentations [4], validation of yeast population growth models [5,27] as well as monitoring of microbial evolution during the transition from exponential to stationary phases [1]. In flow cytometry, the incident light scattered from one cell is collected at two different angles: a narrow forward angle (forward scatter) and approximately a right angle from the light beam (side scatter).…”