Ies became available and were used for immunophenotyping by flow cytometry. Today the most frequent use of flow cytometry is still in medical diagnosis. Prior to flow cytometry it was also common belief that in PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/26162776 a single strain culture all cells behave homogeneously. Flow cytometry has shown that in reality quite surprising variations are present, which may be caused both by genetic or epigenetic alterations or by differences in the state of individual cells which will diversify theirreaction to BRDU solubility present culture conditions. Analysis of cells in culture has shown that with the exception of DNA content, all other cellular components are distributed over a wide range, which is the reason why such parameters are usually presented on a logarithmic scale in flow cytometry histograms. This variation of cellular properties is of special interest for strain improvement purposes, as it allows the sorting of cells with diverging and potentially optimized properties. The principle of flow cytometry can be described as a fluorescent microscope without morphological resolution where the cells travel in a liquid stream instead of resting on a slide. Each single cell, as it passes the exciting light and the measuring optics, sends out a number of signals, including the size and structure related forward and side scatter and the fluorescent signals, which in turn are dependent on the staining procedure that has been used. These signals are measured and stored for each individualPage 1 of(page number not for citation purposes)Microbial Cell Factories 2006, 5:http://www.microbialcellfactories.com/content/5/1/AR2 RBRFigure 1 Multiparameter analysis methods Multiparameter analysis methods. By gating on different subpopulations, their properties with regard to additional parameters can be determined. Most commercial flow cytometers can measure between 4 and 8 fluorescence signals in addition to forward scatter (FSC) and side scatter (SSC). As an illustration of the compexity of multiparameter data, the graph below shows a sample of yeast cells stained for viability with ethidium bromide. A: ethidium bromide fluorescence (FL2) against cell size (FSC). B: size (FSC) against granularity characteristics (SSC). Cells marked in panel A as belonging to distinct subpopulations are identified by the same colors in panel B. cell. One of the revolutionary properties of flow cytometry is the possibility to measure correlated data: by staining with several fluorescent labels, it is possible to obtain the distribution of each of these parameters within the population, but also their interrelationship (Fig. 1). This information can of course also be obtained using a fluorescent microscope and image analysis, but only from a limited number of cells. With flow cytometry, analyzing 104 cells is standard procedure and it is possible to look at millions of cells without much trouble. This feature is especially important for biotechnological applications, because it is usually the rare cell which is of interest: the cell with altered properties, a higher production rate, better metabolic parameters or containing the protein with a higher binding affinity. Such rare cells with altered properties are the main target of cell sorting. To be able to sort, it is a prerequisite that flow cytometric methods have been established that allow the characterization of a specific cellular property. Analysis by flow cytometry will provide the distribution of parameters within the population and.