Near-infrared co-illumination of fluorescent proteins reduces photobleaching and phototoxicity

Here we present a method to reduce the photobleaching of fluorescent proteins and the associated phototoxicity. It exploits a photophysical process known as reverse intersystem crossing, which we induce by near-infrared co-illumination during fluorophore excitation. This dual illumination method reduces photobleaching effects 1.5-9.2-fold, can be easily implemented on commercial microscopes and is effective in eukaryotic and prokaryotic cells with a wide range of fluorescent proteins.

Real-time visualization of mutations and their fitness effects in single bacteria

Mutations are the driving force of evolution and the source of important pathologies. The characterization of the dynamics and effects of mutations on fitness is therefore central to our understanding of evolution and to human health. This protocol describes how to implement two methods that we recently developed: mutation visualization (MV) and microfluidic mutation accumulation (µMA), which allow the occurrence of mutations created by DNA replication errors (MV) and the evolution of cell fitness during MA (µMA) to be followed directly in individual cells of Escherichia coli. MV provides a quantitative characterization of the dynamics of mutation occurrences, and µMA allows precise estimation of the distribution of fitness effects (DFEs) of mutations. Both methods use microfluidics and time-lapse microscopy, and a fluorescent mismatch repair (MMR) MutL protein is used as a marker for nascent mutations. Here, we present a single protocol describing how to implement the MV and µMA methods, including detailed procedures for microfluidic setup installation, data acquisition and data analysis and interpretation. Using this procedure, the microfluidic setup installation can be completed within 1 d, and automated data acquisition takes 2-4 d.

High-throughput detection and tracking of cells and intracellular spots in mother machine experiments

The analysis of bacteria at the single-cell level is essential to characterization of processes in which cellular heterogeneity plays an important role. BACMMAN (bacteria mother machine analysis) is a software allowing fast and reliable automated image analysis of high-throughput 2D or 3D time-series images from experiments using the 'mother machine', a very popular microfluidic device allowing biological processes in bacteria to be investigated at the single-cell level. Here, we describe how to use some of the BACMMAN features, including (i) segmentation and tracking of bacteria and intracellular fluorescent spots, (ii) visualization and editing of the results, (iii) configuration of the image-processing pipeline for different datasets and (iv) BACMMAN coupling to data analysis software for visualization and analysis of data subsets with specific properties. Among software specifically dedicated to the analysis of mother machine data, only BACMMAN allows segmentation and tracking of both bacteria and intracellular spots. For a single position, single channel with 1,000 frames (2-GB dataset), image processing takes ~6 min on a regular computer. Numerous implemented algorithms, easy configuration and high modularity ensure wide applicability of the BACMMAN software.

Proliferation-dependent positioning of individual centromeres in the interphase nucleus of human lymphoblastoid cell lines

Centromeres are not randomly distributed in interphase nuclei. High-throughput imaging provides an accurate characterization of how their organization varies as a function of the proliferation state in human lymphoblastoid cells. The results suggest the existence of mechanisms that drive the nuclear positioning of centromeres.

The cell nucleus is a highly organized structure and plays an important role in gene regulation. Understanding the mechanisms that sustain this organization is therefore essential for understanding genome function. Centromeric regions (CRs) of chromosomes have been known for years to adopt specific nuclear positioning patterns, but the significance of this observation is not yet completely understood. Here, using a combination of fluorescence in situ hybridization and immunochemistry on fixed human cells and high-throughput imaging, we directly and quantitatively investigated the nuclear positioning of specific human CRs. We observe differential attraction of individual CRs toward both the nuclear border and the nucleoli, the former being enhanced in nonproliferating cells and the latter being enhanced in proliferating cells. Similar positioning patterns are observed in two different lymphoblastoid cell lines. Moreover, the positioning of CRs differs from that of noncentromeric regions, and CRs display specific orientations within chromosome territories. These results suggest the existence of not-yet-characterized mechanisms that drive the nuclear positioning of CRs and therefore pave the way toward a better understanding of how CRs affect nuclear organization.

Analysis of nuclear organization with TANGO, software for high-throughput quantitative analysis of 3D fluorescence microscopy images

The cell nucleus is a highly organized cellular organelle that contains the genome. An important step to understand the relationships between genome positioning and genome functions is to extract quantitative data from three-dimensional (3D) fluorescence imaging. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here we present a practical approach using TANGO (Tools for Analysis of Nuclear Genome Organization), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a generic tool able to process large sets of images, allowing quantitative study of nuclear organization. In this chapter a practical description of the software is drawn in order to give an overview of its different concepts and functionalities. This description is illustrated with a precise example that can be performed step-by-step on experimental data provided on the website http://biophysique.mnhn.fr/tango/HomePage.

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization

Motivation: The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images.

Results: Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization.

Availability: TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence.

Contact:thomas.boudier@snv.jussieu.fr

Supplementary information:Supplementary data are available at Bioinformatics online.