Article

New Fluorescence Microscopy Methods for Microbiology: Sharper, Faster, and Quantitative

Department of Molecular Biology, Princeton University, Princeton, NJ 08540, USA.
Current opinion in microbiology (Impact Factor: 5.9). 05/2009; 12(3):341-6. DOI: 10.1016/j.mib.2009.03.001
Source: PubMed
ABSTRACT
In addition to the inherent interest stemming from their ecological and human health impacts, microbes have many advantages as model organisms, including ease of growth and manipulation and relatively simple genomes. However, the imaging of bacteria via light microscopy has been limited by their small sizes. Recent advances in fluorescence microscopy that allow imaging of structures at extremely high resolutions are thus of particular interest to the modern microbiologist. In addition, advances in high-throughput microscopy and quantitative image analysis are enabling cellular imaging to finally take advantage of the full power of bacterial numbers and ease of manipulation. These technical developments are ushering in a new era of using fluorescence microscopy to understand bacterial systems in a detailed, comprehensive, and quantitative manner.

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Available from: ncbi.nlm.nih.gov
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    • "This complexity emphasizes the need for single-cell analysis techniques in microbial research. Fluorescence imaging is a powerful tool to localize molecules in single cells [3,4], but the resolution remains limited to the wavelength of the light source. On the other hand, high-resolution images of microbial structures can be obtained by electron microscopy techniques. "
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    • "The subcellular localization and the dynamics of protein complexes have been under scrutiny in imaging cytoskeletal proteins29303132, the bacterial chromosome3334353637, flagellar motion [38, 39], and the dynamics of molecular-motor-like proteins [40, 41]. While many techniques of modern microscopy have become readily available to microbiology labs [2, 42], there are few standardized tools for the analysis of the images obtained (e.g. for cell segmentation [43]; see below). Therefore, images are often analyzed by visual inspection alone, which is generally subjective and therefore entails the danger of erroneous conclusions. "
    [Show abstract] [Hide abstract] ABSTRACT: Fluorescence microscopy is the primary tool for studying complex processes inside individual living cells. Technical advances in both molecular biology and microscopy have made it possible to image cells from many genetic and environmental backgrounds. These images contain a vast amount of information, which is often hidden behind various sources of noise, convoluted with other information and stochastic in nature. Accessing the desired biological information therefore requires new tools of computational image analysis and modeling. Here, we review some of the recent advances in computational analysis of images obtained from fluorescence microscopy, focusing on bacterial systems. We emphasize techniques that are readily available to molecular and cell biologists but also point out examples where problem-specific image analyses are necessary. Thus, image analysis is not only a toolkit to be applied to new images but also an integral part of the design and implementation of a microscopy experiment.
    Full-text · Article · May 2012 · BioEssays
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    • "Recent advances in fluorescence microscopy [1] have revealed a surprising degree of protein organization and segregation on bacterial membranes [2]. Proteins are found to localize to regions such as mid-cell planes and poles of rod-shaped bacteria that were not thought to be chemically distinct. "
    [Show abstract] [Hide abstract] ABSTRACT: Recent experiments suggest that in the bacterium, B. subtilis, the cue for the localization of small sporulation protein, SpoVM, that plays a central role in spore coat formation, is curvature of the bacterial plasma membrane. This curvature-dependent localization is puzzling given the orders of magnitude difference in lengthscale of an individual protein and radius of curvature of the membrane. Here we develop a minimal model to study the relationship between curvature-dependent membrane absorption of SpoVM and clustering of membrane-associated SpoVM and compare our results with experiments.
    Full-text · Article · Feb 2012 · PLoS ONE
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