Laurence Preziosi-Belloy

Antimicrobial activity of carvacrol related to its chemical structure

Aims:  To investigate the relation between the chemical structure and the antimicrobial activity of carvacrol, eugenol, menthol and two synthesized carvacrol derivative compounds: carvacrol methyl ether and carvacryl acetate against bacteria, Escherichia coli, Pseudomonas fluorescens, Staphylococcus aureus, Lactobacillus plantarum, Bacillus subtilis, a yeast Saccharomyces cerevisiae and one fungi Botrytis cinerea.

Assessing yeast viability from cell size measurements

During microbial cell cultures, environmental conditions affect cell physiology and subsequently process efficiency. Physiological changes result in changing cell morphology, such as cell size variations. The aim of this work was to study cell size evolution of a Saccharomyces cerevisiae population exposed to various stresses during alcoholic batch fermentations, and to evaluate the potential use of cell size measurements to infer cell viability. During a reference culture, without perturbation, viability as assessed by propidium iodide staining (PI) remained 100% and mean cell diameter was found to be above 5microm. A rapid temperature shift from 33 to 43 degrees C at 50gl(-1) of ethanol resulted in an immediate arrest of growth and triggered a progressive loss of viability from 100% to 0% and a decrease of mean cell diameter from 5.2 to 3.7microm. Cell size distribution curves obtained with a cell counter showed an increasing subpopulation of significantly smaller cells. At single-cell level, combined microscopy size measurements and PI staining showed that this subpopulation was exclusively composed of dead cells. Similar results were obtained after acetic acid or furfural additions. Accordingly, a multivariate data analysis was achieved to estimate the ratio of dead cells from cell size distributions obtained using the cell counter.

Determination of yeast viability during a stress-model alcoholic fermentation using reagent-free microscopy image analysis.

A dedicated microscopy imaging system including automated positioning, focusing, image acquisition, and image analysis was developed to characterize a yeast population with regard to cell morphology. This method was used to monitor a stress‐model alcoholic fermentation with Saccharomyces cerevisiae. Combination of dark field and epifluorescence microscopy after propidium iodide staining for membrane integrity showed that cell death went along with important changes in cell morphology, with a cell shrinking, the onset of inhomogeneities in the cytoplasm, and a detachment of the plasma membrane from the cell wall. These modifications were significant enough to enable a trained human operator to make the difference between dead and viable cells. Accordingly, a multivariate data analysis using an artificial neural network was achieved to build a predictive model to infer viability at single‐cell level automatically from microscopy images without any staining. Applying this method to in situ microscope images could help to detect abnormal situations during a fermentation course and to prevent cell death by applying adapted corrective actions.