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Review
, 68 (3), 538-59, table of contents

Single-cell Microbiology: Tools, Technologies, and Applications

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Review

Single-cell Microbiology: Tools, Technologies, and Applications

Byron F Brehm-Stecher et al. Microbiol Mol Biol Rev.

Abstract

The field of microbiology has traditionally been concerned with and focused on studies at the population level. Information on how cells respond to their environment, interact with each other, or undergo complex processes such as cellular differentiation or gene expression has been obtained mostly by inference from population-level data. Individual microorganisms, even those in supposedly "clonal" populations, may differ widely from each other in terms of their genetic composition, physiology, biochemistry, or behavior. This genetic and phenotypic heterogeneity has important practical consequences for a number of human interests, including antibiotic or biocide resistance, the productivity and stability of industrial fermentations, the efficacy of food preservatives, and the potential of pathogens to cause disease. New appreciation of the importance of cellular heterogeneity, coupled with recent advances in technology, has driven the development of new tools and techniques for the study of individual microbial cells. Because observations made at the single-cell level are not subject to the "averaging" effects characteristic of bulk-phase, population-level methods, they offer the unique capacity to observe discrete microbiological phenomena unavailable using traditional approaches. As a result, scientists have been able to characterize microorganisms, their activities, and their interactions at unprecedented levels of detail.

Figures

FIG. 1.
FIG. 1.
Fluorescence ratio imaging of nisin-mediated dissipation of ΔpH in Listeria monocytogenes. Fluorescence ratio imaging microscopy was used to monitor the intracellular acidification of broth-grown cells of L. monocytogenes after exposure to the membrane-permeabilizing lantibiotic nisin. The pH-dependent spectral response of carboxyfluorescein diacetate succinimidyl ester (CFSE) was used as a probe of intracellular pH (pHi). The ratio of CFSE fluorescence intensity at 490 nm to that at 435 nm was calibrated over a pH range of 5.0 to 9.0. (A) Live, intact cells of L. monocytogenes maintained pHi values between 8.0 and 8.4, even when the pH of the external medium was low (e.g. pH 5.5). (B) Nisin-mediated membrane permeabilization resulted in the equilibration of pHi with the pH of the medium after 12 min of exposure. Individual cellular responses were more heterogeneous for cells derived from colonies, suggesting the importance of microenvironmental factors in differential susceptibility to nisin (not shown). A color-coded pH scale is shown in the upper right-hand corner. Reprinted from reference with permission from the publisher.
FIG. 2.
FIG. 2.
Flow cytometric analysis of a genetically and metabolically complex cell mixture. This figure illustrates the power of single-cell staining methods in combination with flow cytometric analysis for the fluorescent “dissection” of complex microbial populations. Here, Salmonella enterica serotype Typhimurium is differentiated from a mixture of E. coli, Citrobacter freundii, Proteus vulgaris, and Shigella dysenteriae on the basis of both cytochemical activity (CTC staining) and genetic identity (Salmonella-specific FISH staining). A complex mixture containing both live and formalin-killed representatives of each cell type was incubated with CTC, fixed with 10% buffered formalin, hybridized with a Salmonella-specific DNA probe (Sal3-Cy5), and examined by flow cytometry. Four distinct populations can be seen. Clockwise from the bottom left, they are dead non-Salmonella members of the Enterobacteriaceae (A), live non-Salmonella members of the Enterobacteriaceae (B), live Salmonella (C), and dead Salmonella (D). The numbers in each quadrant represent percentages of the total population. The photographic inset provides a visual interpretation of the cytometry data. Reprinted from reference with permission from the publisher.
FIG. 3.
FIG. 3.
Single-cell determination of yeast glycogen content by image cytometry. The glycogen content of individual S. cerevisiae cells was determined from their optical density (OD) values after staining with Lugol's solution (I2-KI). Images were processed using a series of steps designed to extract quantitative information about cell size, shape, volume, and OD. The OD profile of cell A (glycogen poor) shows concentrated staining only on the periphery of the cell, whereas the profile of cell B (glycogen rich) shows dense staining throughout. To avoid overestimation of the mean glycogen content in glycogen-poor cells, only the central portion of each cell was used for measurement. The ability to quantitate the glycogen content in individual cells allows the determination of glycogen distribution within a population. Because the character of this distribution is related to yeast quality, image cytometry can be used as a tool for quality control. OD-L, optical density, Lugol staining. Reprinted from reference with permission from the publisher.
FIG. 4.
FIG. 4.
Single-molecule analysis of cyclic AMP (cAMP) receptor occupancy on the surface of a Dictyostelium discoideum cell during chemotaxis. Cells were exposed to a gradient of Cy3-labeled cAMP (Cy3-cAMP, shown to be functional as a chemoattractant) and observed for up to 10 min. Binding of Cy3-cAMP to cell surface receptors was monitored at single-molecule resolution by using total internal reflection fluorescence microscopy. Occupied cAMP receptors appear as bright yellow dots on the surface of the cell. The arrow indicates the direction of the Cy3-cAMP source. The time for each sequential image is given in seconds. Kinetic analysis showed that Cy3-cAMP receptor complexes located on anterior pseudopods dissociated faster than those on the posterior tail (239). This work enabled the discrete characterization of receptor dynamics in single living cells, suggesting a role for cell polarity in the chemotactic process. Reprinted from reference with permission from the publisher.
FIG. 5.
FIG. 5.
Raman spectrum of a single Clostridium beijerinckii cell. Spectral peaks ascribed to major cellular macromolecules (e.g., nucleic acids, proteins, lipids, and carbohydrates) are shown. The video inset shows a cell illuminated in the laser focus, which is of approximately the same diameter as the cell. The laser diffraction pattern, which can serve as a visual cue for achieving the proper laser focus, can also be seen. Single-cell Raman spectroscopy represents a noninvasive means of investigating the biochemical heterogeneity of microbial populations. Reprinted from reference with permission from the publisher.
FIG. 6.
FIG. 6.
Synchrotron X-ray fluorescence mapping of the relative elemental distribution in a single diatom. An X-ray microprobe was used to focus a monochromatic X-ray beam on a diatom collected from the Southern Ocean. The sample was scanned through the focused beam in pixel steps of 0.5 μm, and the full X-ray fluorescence spectrum was collected at each step. Two-dimensional elemental maps were generated from the resulting energy spectra by using element-specific filtering. Elemental concentrations were calculated from X-ray fluorescence data using National Institute of Standards and Technology thin-film or similar standards. Comparison of light and epifluorescence (epi) micrographs with elemental maps for the same diatom enabled the discrete localization of each element within the cell. Data collected for this diatom show that Si and K map onto the cell's siliceous frustule; P, S, Ca, Mn, Fe, Cu, and Zn appear to be associated with the cytoplasm; and Ni is present only on the outer membranes or frustule. This approach to characterizing elemental distributions within individual diatoms provides biologically relevant information not available from population-scale methods of elemental analysis. The resulting data may offer unique insights into the physiological state, ambient chemical environment, and role in elemental cycling of these organisms (238). Reprinted from reference with permission from the publisher.
FIG. 7.
FIG. 7.
Electrorotational analyses of single yeast cells. (A) Single cell of S. pombe during analysis in a microstructured electrorotation chamber. Four circular electrodes (dark semicircles), spaced 100 μm apart, are precisely positioned to allow dielectrophoretic trapping of individual cells. (B) Cellular dielectric properties are responsive to mechanical or chemical perturbation. This panel illustrates time-resolved changes in the electrorotation spectra of a single S. cerevisiae cell treated with nystatin at t = 12 min. Nystatin-mediated leakage of intracellular ions is expected to change the dielectric properties of the cell, leading to the frequency-dependent shifts in cell rotation rates seen for both cofield and antifield rotations. Panels A and B reprinted from references and , respectively, with permission from the publishers.
FIG. 8.
FIG. 8.
Comparison of whole-cell bursting responses from Staphylococcus epidermidis (left) and E. coli (right), as determined by micromanipulation. Force diagrams for single cells compressed between the surface of a glass slide and an optical fiber are shown. In both diagrams, datum point A indicates the first contact of the microprobe with the cell and datum point B corresponds to the point at which cell rupture takes place. The microprobe continues to advance after cell bursting, eventually compressing the cellular debris (points C and D). To correlate bursting properties with cell size, a video image was taken of each cell prior to manipulation. Data kindly provided by C. Shiu, Z. Zhang, and C. R. Thomas.
FIG. 9.
FIG. 9.
Serial microcapillary electrophoresis of three individual S. cerevisiae spheroplasts. The labeled peaks (T, D, M, and L) represent, respectively, the original substrate and three different fluorescent hydrolysis products of a tetramethylrhodamine-labeled triglucoside. The hydrolysis products accumulated in each cell due to in vivo enzymatic activity. The larger peaks (T and L) contain between 500 and 1,000 molecules of each fluorescent analyte. To ease visual comparison, the electropherograms from the first two cells have been shifted upward on the y axis. This work demonstrates the capacity of microcapillary electrophoresis to analyze sequential metabolic reactions occurring in single microbial cells (e.g., “metabolic cascades”). Reprinted from reference with permission from the publisher.

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