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


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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    • "Specifically, detailed knowledge can be obtained using 3C-based techniques [36] that map at high resolution the spatial interaction frequencies between genomic sites. Super-resolution imaging techniques [37], [38] can provide single-cell information on the position and function of these proteins within the nucleoidal framework, as well as on spatial distance of genomic sites of interest. Finally, it is not known if macrodomains are maintained under different physiological conditions. "
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    ABSTRACT: The Escherichia coli chromosome is organized into four macrodomains, the function and organisation of which are poorly understood. In this review we focus on the MatP, SeqA, and SlmA proteins that have recently been identified as the first examples of factors with macrodomain-specific DNA-binding properties. In particular, we review the evidence that these factors contribute towards the control of chromosome replication and segregation by specifically targeting subregions of the genome and contributing towards their unique properties. Genome sequence analysis of multiple related bacteria, including pathogenic species, reveals that macrodomain-specific distribution of SeqA, SlmA, and MatP is conserved, suggesting common principles of chromosome organisation in these organisms. This discovery of proteins with macrodomain-specific binding properties hints that there are other proteins with similar specificity yet to be unveiled. We discuss the roles of the proteins identified to date as well as strategies that may be employed to discover new factors.
    PLoS Genetics 06/2011; 7(6):e1002123. DOI:10.1371/journal.pgen.1002123 · 7.53 Impact Factor
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    • "Most of the singlecell gene expression studies in bacteria have been performed at the protein level (Elowitz et al., 2002; Lahav et al., 2004; Cai et al., 2006; Suel et al., 2006; Yu et al., 2006). Recent reviews provide a comprehensive picture of the state-of-the-art in this area (Levsky and Singer, 2003; Miyashiro and Goulian, 2007; Fraser and Kaern, 2009; Larson et al., 2009) including different aspects of fluorescence microscopy in microbiology (Gitai, 2009; Fero and Pogliano, 2010). "
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    ABSTRACT: Studies of gene expression at the single cell level in live bacterial cells represent a new and fertile area of research providing real-time, spatially specified information that cannot be obtained by techniques relying on large cell populations. Before recently, most single-cell studies have been concerned with gene expression at the protein level and explored the spatiotemporal localization and dynamics of different bacterial proteins. However, to fully understand the complex process of gene expression, it is necessary to visualize and quantify RNA molecules in the cellular environment. The first studies analysing the kinetics of RNA transcription and the distribution of RNA in single bacterial cells in real time have recently been reported. Here, I discuss the methods allowing RNA detection in living bacterial cells, the results on RNA kinetics and RNA localization, and the challenges for future research in this area.
    Molecular Microbiology 04/2011; 80(5):1137-47. DOI:10.1111/j.1365-2958.2011.07652.x · 4.42 Impact Factor
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    • "[cs.CV] 18 Jan 2011 cessing pipeline are due to the low resolution of the image stacks, due to movements of the cells over time, due to other obscuring cells and structures, and due to the low contrast between the DNA damage and the surrounding nucleus. An overview of current methods for the analysis of fluorescent microscopy images can be found in [7] and references therein. "
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    ABSTRACT: The efficient repair of cellular DNA is essential for the maintenance and inheritance of genomic information. In order to cope with the high frequency of spontaneous and induced DNA damage, a multitude of repair mechanisms have evolved. These are enabled by a wide range of protein factors specifically recognizing different types of lesions and finally restoring the normal DNA sequence. This work focuses on the repair factor XPC (xeroderma pigmentosum complementation group C), which identifies bulky DNA lesions and initiates their removal via the nucleotide excision repair pathway. The binding of XPC to damaged DNA can be visualized in living cells by following the accumulation of a fluorescent XPC fusion at lesions induced by laser microirradiation in a fluorescence microscope. In this work, an automated image processing pipeline is presented which allows to identify and quantify the accumulation reaction without any user interaction. The image processing pipeline comprises a preprocessing stage where the image stack data is filtered and the nucleus of interest is segmented. Afterwards, the images are registered to each other in order to account for movements of the cell, and then a bounding box enclosing the XPC-specific signal is automatically determined. Finally, the time-dependent relocation of XPC is evaluated by analyzing the intensity change within this box. Comparison of the automated processing results with the manual evaluation yields qualitatively similar results. However, the automated analysis provides more accurate, reproducible data with smaller standard errors. The image processing pipeline presented in this work allows for an efficient analysis of large amounts of experimental data with no user interaction required.
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