A comparison of fluorescent stains for the assessment of viability and metabolic activity of lactic acid bacteria

Abstract

Lactic acid bacteria (LAB) are used as starter or probiotic cultures in the food and pharmaceutical industries and, therefore, rapid and accurate methods for the detection of their viability are of practical relevance. In this study 10 LAB strains, belonging to the genera Enterococcus, Lactococcus, Leuconostoc, Lactobacillus, Streptococcus and Weissella, were subjected to heat and oxidative stresses and cell injury or death was assessed comparing different fluorescent probes (Syto 9; Propidium Iodide, PI; 4,6-diamidino-2-phenylindole, DAPI; 5,(6)-carboxyfluorescein diacetate, cFDA) to identify the stain combination which most reliably allowed the detection of live/metabolically active and dead cells. Protocols for specimen preparation and staining were optimized and a simple procedure for automated cell counts was developed using NIH ImageJ macros. Cysteine and semi-solid agar solution were efficiently used as anti-fading agent and mounting medium, respectively. The double staining cFDA-PI apparently offered the best and most versatile indication of both cell metabolic activity and membrane integrity. An excellent correlation between manual and automated cell counts for the majority of strain/stain combinations was found. This work provides a simple protocol for specimen preparation and staining based on the use of safe, easy to prepare and inexpensive reagents as compared to other methods. Additionally, the automated cell count procedure developed can be applied to several bacterial species and allows an increase in the number of experimental trials and the reproducibility and sensitivity of the analysis.

Appendix: Automated count of bright field and fluorescent images

The macro commands for automated BF count performs the following steps: after converting the RGB colour image in 32 bit gray scale image, background correction, cell pixels are separated from background pixels by a thresholding function which produce a binary image with black cells on a white background. Clustered cells in chain-forming species can be separated from each other by watershed segmentation. The image is calibrated by inserting correction factors for the objective in use (100 × 1.3 NA Plan Fluor oil immersion objective, Nikon) and, finally, objects can be added or removed from images by tuning the “size” and “circularity” parameters. The counts and measures generated are then.

automatically tabulated and can be imported into Excel or other analysis programs. No background subtraction is needed for fluorescent images.

Macro commands for bright field images

• run(“32-bit”);

• run(“Subtract Background…”, “rolling = 50 light”);

• run(“Make Binary”);

• run(“Watershed”);

• run(“Set Measurements…”, “area centroid center perimeter circularity feret’s redirect = None decimal = 3”);

• run(“Set Scale…”, “distance = 1 known = 0.03 pixel = 1 unit = μm”);

• run(“Analyze Particles…”, “size = 0.10-2 circularity = 0.20–1.00 show = Outlines display clear include summarize”);

Macro commands for epifluorescence images

• run(“Brightness/Contrast…”);

• run(“Enhance Contrast”, “saturated = 0.5”);

• run(“32-bit”);

• run(“Make Binary”);

• run(“Watershed”);

• run(“Set Measurements…”, “area centroid center perimeter circularity feret’s redirect = None decimal = 3”);

• run(“Set Scale…”, “distance = 1 known = 0.03 pixel = 1 unit = μm”);

• run(“Analyze Particles…”, “size = 0.10-2 circularity = 0.20–1.00 show = Outlines display clear include summarize”);