Intracellular pH determination of pristinamycin-producing Streptomyces pristinaespiralis by image analysis.

Intracellular pH (pH(i)) is an essential parameter in the regulation of intracellular processes. Thus, its measurement might provide clues regarding the physiological state of cells cultivated in vitro. pH(i) of the filamentous, pristinamycin-producing Streptomyces pristinaespiralis was determined by epifluorescence microscopy and image analysis using the pH-sensitive fluorescent probe BCECF-AM [2', 7'-bis(2-carboxyethyl)-5(6)-carboxyfluorescein, acetoxymethyl ester]. Staining cell culture samples (OD(660)=1) of S. pristinaespiralis with 20 microM BCECF at 28 degrees C for 30 min yielded a green/red fluorescence ratio (R:(527/600)) that correlated with the pH(i) of the cells for values ranging from 6.5 to 8.5. When S. pristinaespiralis was cultivated in pristinamycin-producing conditions (in batch mode, with a constant external pH of 6.8), the measured pH(i) varied between 6.3 and 8.7. In fact, pH(i) correlated with the excretion of pristinamycins and glucose consumption during the production process.

Biomass quantification by image analysis.

Microbiologists have always rely on microscopy to examine microorganisms. When microscopy, either optical or electron-based, is coupled to quantitative image analysis, the spectrum of potential applications is widened: counting, sizing, shape characterization, physiology assessment, analysis of visual texture, motility studies are now easily available for obtaining information on biomass. In this chapter the main tools used for cell visualization as well as the basic steps of image treatment are presented. General shape descriptors can be used to characterize the cell morphology, but special descriptors have been defined for filamentous microorganisms. Physiology assessment is often based on the use of fluorescent dyes. The quantitative analysis of visual texture is still limited in bioengineering but the characterization of the surface of microbial colonies may open new prospects, especially for cultures on solid substrates. In many occasions, the number of parameters extracted from images is so large that data-mining tools, such as Principal Components Analysis, are useful for summarizing the key pieces of information.

Physiological investigations by image analysis.

Modern quantitative image analysis has been extensively used to characterize the morphology of microorganisms, especially those of the filamentous type. More recently physiological features have been quantified, making use of classical stains as well as fluorescent dyes. The potential of the technique is illustrated by a detailed analysis of the differentiation of Streptomyces ambofaciens. Three different staining procedures have been used to monitor the thinning and septation of hyphae (with propidium iodide staining), the leakage of cellular components through the membrane (with carbol gentian violet staining) and the respiration (with INT staining) in a batch submerged culture.

Characterization of Penicillium chrysogenum physiology in submerged cultures by color and monochrome image analysis.

Although filamentous microorganisms are widely used in industrial fermentation processes, their growth and differentiation are not yet fully understood, because their biomass is structured, and therefore difficult to describe and to quantify. This lack of appropriate tools can hinder the optimization and control of the fermentation. A quantitative image analysis method was therefore developed for characterizing the physiology of the penicillin-producing mold Penicillium chrysogenum. This method is based on a differential staining procedure showing six physiological states: growing material, three differentiated states characterized by an increasing granulation, a highly vacuolized state, and dead segments having lost their cytoplasm. The image analysis software, with versions written for monochrome and color images, consisted of a semiautomatic binary mask computation step and a fully automatic segmentation step based on a fuzzy classification.

Morphological characterization of yeast by image analysis.

A semiautomatic image analysis method, with minimal operator intervention, has been developed to characterize the morphology of yeast cells under the assumption that they have an ellipsoidic shape. The cells are observed by optical microscopy and the surface and the minor and major half-axes of the projection of the ellipsoid on the image plane are determined. Using this method, yeast size distributions and population kinetics (single and budding cells, cell clusters) are determined during alcoholic fermentations. Combination of image analysis with a methylene blue viability test is examined but the staining procedure induces a change in the size of the cells. .

Application of quantitative image analysis to a mammalian cell line grown on microcarriers.

Quantitative image analysis has been applied to the monitoring of cultures of a mammalian cell line on microcarriers. Procedures have been developed to investigate microcarrier colonization and cluster formation and to determine the eventual modification of cell size during cultivation using scanning electron microscopy (SEM) microphotography. The human kidney tumor cells (TCL 598) on which the procedures were tested underwent a slight size decrease during the development of the first cell layer on the microcarriers. The cluster size and the cell size remained constant during the culture stationary phase.