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Review
. 2000 Apr;13(2):167-95.
doi: 10.1128/CMR.13.2.167.

Applications of flow cytometry to clinical microbiology

A Alvarez-Barrientos  1 , J Arroyo, R Cantón, C Nombela, M Sánchez-Pérez
Affiliations
Review

Applications of flow cytometry to clinical microbiology

A Alvarez-Barrientos et al. Clin Microbiol Rev. 2000 Apr.

Abstract

Classical microbiology techniques are relatively slow in comparison to other analytical techniques, in many cases due to the need to culture the microorganisms. Furthermore, classical approaches are difficult with unculturable microorganisms. More recently, the emergence of molecular biology techniques, particularly those on antibodies and nucleic acid probes combined with amplification techniques, has provided speediness and specificity to microbiological diagnosis. Flow cytometry (FCM) allows single- or multiple-microbe detection in clinical samples in an easy, reliable, and fast way. Microbes can be identified on the basis of their peculiar cytometric parameters or by means of certain fluorochromes that can be used either independently or bound to specific antibodies or oligonucleotides. FCM has permitted the development of quantitative procedures to assess antimicrobial susceptibility and drug cytotoxicity in a rapid, accurate, and highly reproducible way. Furthermore, this technique allows the monitoring of in vitro antimicrobial activity and of antimicrobial treatments ex vivo. The most outstanding contribution of FCM is the possibility of detecting the presence of heterogeneous populations with different responses to antimicrobial treatments. Despite these advantages, the application of FCM in clinical microbiology is not yet widespread, probably due to the lack of access to flow cytometers or the lack of knowledge about the potential of this technique. One of the goals of this review is to attempt to mitigate this latter circumstance. We are convinced that in the near future, the availability of commercial kits should increase the use of this technique in the clinical microbiology laboratory.

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Figures

FIG. 1
FIG. 1
Light-scattering and fluorescence signal production at the flow cell analysis point of the flow cytometer. From Purdue Cytometry CD-ROM vol. 1 (adapted with permission of the publisher).
FIG. 2
FIG. 2
Scheme of optic (dichroic mirrors and bandpass filters) and illumination (laser) systems of a flow cytometer with six parameters detected (size, granularity, and four fluorescences) by separate photomultiplier tubes (except size, which can be detected by photodiode or a PMT tube) and sorting capacity. From Purdue Cytometry CD-ROM vol. 1 (adapted with permission of the publisher).
FIG. 3
FIG. 3
The data obtained from a flow cytometer can be displayed in several ways. The most common are the mono- and biparametric histograms (A and B), which usually include a statistical analysis of the results. (A) Monoparametric histogram showing the selected parameter on the x axis and the relative cell number on the y axis. (B) Biparametric histogram showing cells distributed as a function of their signal intensity with respect to each parameter. Cells located in the upper left quadrant are positive for the parameter represented on the y axis, cells located in the upper right quadrant are positive for both parameters, cells located in the lower left quadrant are double negative, while cells in the lower right panel are positive for the parameters on the x axis. (C and D) Three-dimensional representations. The z axis can represent the relative number of cells (C) or a third parameter (D), such as scattered light on the x and y axes and fluorescence signals on the z axis.
FIG. 4
FIG. 4
(A) Dual-parameter analysis of forward light scatter (size) and red fluorescence signals allowed the discrimination between two species of Candida, based on different fluorochrome staining backgrounds. These yeast species are indistinguishable by monoparametric analysis of forward light scatter or red autofluorescence. However, after addition of PI, they show different basal levels, and if this is plotted against size, it is possible to discriminate them. This kind of analysis permits quantification of both species in mixed cultures. (B) Quantification of different protein amounts (measured as FITC fluorescence) can be used to distinguish different microorganisms such as those represented in the histogram (from Purdue Cytometry CD-ROM, vol 2., ISSN 1091-2037, provided by Hazel M. Davey [adapted with permission of the publisher]). (C) Dual-fluorescence discrimination of fungal spores. Spores from Aspergillus, Mucor, Cladosporium, and Fusarium were fixed and stained with Calcofluor, which binds to chitin in the spore wall, and PI, which stains nucleic acids. As shown, the spores have different amounts of chitin and nucleic acids, permitting their segregation by FCM. Samples shown in panel A were run on a FACScan (Becton-Dickinson) flow cytometer, the ones shown in panel B were run on an EPICS Elite (Coulter) flow cytometer, and those shown in panel C were run on a Bryte-HS (Bio-Rad) flow cytometer.
FIG. 5
FIG. 5
Antimicrobial susceptibility testing by FCM using the Bac/live kit (Molecular Probes). Antimicrobial susceptibility is shown by the decrease in green fluorescence (live cells) and the increase in red fluorescence (dead cells). (A) Distribution of E. coli cultures without antimicrobial agent incubation; therefore, the cells appear mainly in quadrant 4 (positive for green fluorescence). (B) An E. coli culture was incubated for 2 h with vancomycin at 1.024 g/ml. The distribution is similar to that seen in panel A. Accordingly, this strain was not affected by antimicrobial agent treatment, although a small percentage of cells was positive for the red fluorescence, meaning that the cells were sensitive to vancomycin. The same protocol was applied to E. faecium (C) and E. faecalis (D) cultures. As described in the text, E. faecium is vancomycin resistant and E. faecalis is vancomycin sensitive. (C) One subpopulation of E. faecium lies in quadrant 1 (positive for red fluorescence only), another is in quadrant 2 (positive for red and green fluorescence), and the majority is in quadrant 4 (positive for green fluorescence only). This means that the behavior of the E. faecium population is not homogeneous in the presence of vancomycin, perhaps due to the loss of the element responsible for vancomycin resistance. (D) After 2 h of incubation, most E. faecalis cells appear in quadrant 1 and the rest appear in quadrant 2. Therefore, almost all cells are positive for red fluorescence and are dead. However, a small population (0.5%) is still present in quadrant 4, meaning that this population is less sensitive to vancomycin than the rest (over 99% of the cells).
FIG. 6
FIG. 6
FCM analysis of poliovirus-infected HeLa cells. (A) Kinetics of intracellular free calcium during poliovirus infection. Poliovirus infection was performed at a multiplicity of infection of 50. After 1 h of adsorption at the indicated times postinfection, poliovirus-infected cells were detached from the plates, incubated with 6 μM fluo-3 AM, and analyzed in a FACScan flow cytometer. (B) Effects of guanidine, cycloheximide, and Ro 09-179 on [Ca2+]i during poliovirus infection. Guanidine (GND) (500 μM), Ro 09-179 (Ro) (1 μg/ml), or cycloheximide (CHX) (50 μM) was added to the infected cells after 1 h of poliovirus adsorption. The [Ca2+]i was monitored using FCM 4 h postinfection. Nontreated poliovirus-infected cells (Poliovirus) and nontreated uninfected cells (Control) are also shown. (C) Simultaneous FCM analysis of cytopathic effect and [Ca2+]i on poliovirus-infected cells. Noninfected (top) and poliovirus-infected (bottom) HeLa cells were analyzed 4 h postinfection for cytosolic free calcium (as described in panel A) and cell size (measured as forward light scatter). Adapted from reference with permission of the publisher.
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References

    1. Reference deleted.
    1. Abad F X, Pinto R M, Bosch A. Flow cytometry detection of infectious rotaviruses in environmental and clinical samples. Appl Environ Microbiol. 1998;64:2392–2396. - PMC - PubMed
    1. Agar D W, Bailey J E. Cell cycle operation during batch growth of fission yeast populations. Cytometry. 1982;3:123–128. - PubMed
    1. Akbar A N, Borthwick N, Salmon M, Gombert W, Bofill M, Shamsadeen N, Pilling D, Pett S, Grundy J E, Janossy G. The significance of low bcl-2 expression by CD45RO T cells in normal individuals and patients with acute viral infections. The role of apoptosis in T cell memory. J Exp Med. 1993;178:427–438. - PMC - PubMed
    1. Alberghina L, Porro D. Quantitative flow cytometry: analysis of protein distributions in budding yeast. A mini-review. Yeast. 1993;9:815–823. - PubMed

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