Chapter fifteen - A Quantitative Method for Measuring Phototoxicity of a Live Cell Imaging Microscope
Introduction
In our experience, running the imaging facilities at the Institut Pasteur in Paris (www.imagopole.org) managing phototoxicity is critical to long-term live cell imaging studies on infectious processes. Host cell–pathogen interactions are especially challenging when it comes to their reconstitution within the context of meaningful experimental imaging paradigms, and phototoxic effects are an abundant source of problems. For example, approaches using multidimensional live cell imaging for studies on infection have become near routine as recourse to analyze subcellular dynamics (Frischknecht and Shorte, 2009, Shorte and Frischknecht, 2008). The difficulty of such approaches comes from the need to maintain spatial and temporal resolution using protocols that assure over-sampling x, y, z, and t. To achieve this, automated, high-speed acquisition aims to sample x, y “stacks” as rapidly as possible to satisfy the requirement that 3D volumes are acquired in a snapshot. Further, the 3D stack must be repeatedly sampled over time at a frequency determined by the temporal dynamics of the process being recorded. Add to this the need for multiple wavelength channels acquired at any given moment, allowing to distinguish distinct targets, which must then be colocalized, it is not uncommon to require 50–150 images to be acquired at each time point. This can amount to the need for an elevated light budget. Overcoming the limitations imposed by this light budget can often be the key to successful imaging. In the context of a real study, for example, following fluorescently labeled HIV virus (Arhel et al., 2006), bacteria (Enninga et al., 2005), parasites (Amino et al., 2006, Amino et al., 2007, Thiberge et al., 2007), or prion protein (Gousset et al., 2009), the need for extensive light exposure can have substantial impact on the quality of the data, due to photobleaching that comprises the signal-to-noise ratio of the detectable signal, and phototoxicity that risks to perturb the processes under study.
A common misconception is to equate photobleaching with phototoxicity. Photobleaching is specific to fluorescence microscopy and arises due to the loss of fluorescent signal that occurs when fluorophores are excited into a state leading to an irreversible loss of signal. Phototoxicity, on the other hand, is a related phenomenon inasmuch as it may be precipitated by photobleaching of fluorophores, but not necessarily. It may also occur in the absence of fluorophore. Phototoxicity is a generalized term used as a catch-all to describe how exogenous light energy may interact with the tissue/cell metabolism (for detailed and extensive review, see Diaspro et al., 2006). The term certainly refers to all those diverse processes resulting in light-induced free-radical generation, for example, from fluorescent labels, and/or light-sensitive metabolites. However, it also describes indirect effects such as localized thermal flux generation (undesired light-induced heating effects); light-induced ionizing, polarizing, and/or trapping effects; and of course unintended light-induced activation of membrane conductances. In turn, phototoxicity may result in extreme phenotypes such as cataclysmic cell death by, for example, free radicals rupturing cell membranes, and collapsing chemical and ionic compartmentalization. Such behaviors are easy to detect and reject before further analysis is performed. On the other hand, and much more problematic, phototoxicity may cause subtle effects, which are difficult to detect, or even distinguish because they do not kill the tissue, but rather subvert its functions. In the case of quantitative light microscopy, there is no ground truth inasmuch as it is the experimental device itself, the microscope, which induces these effects meaning that even careful control experiments may not be sufficient. Thus, our only remaining recourse to managing phototoxicity is to measure it and minimize risks by experimental design. Unfortunately, this is not a trivial task.
Section snippets
The need for a quantitative, generic, and convenient measure of phototoxicity
While it is rather well known, and somewhat implicit, that the impact of phototoxicity will vary with the amount of light delivered to the sample, much less clear are its underlying mechanisms. For example, while every biologist using live cell microscopy techniques will have an opinion on the subject, it is hard to know how a single-point-scanning confocal microscopy may be better or worse than, say, a multi-point-array-scanning confocal or a wide-field microscope. This uncertainty is due
A live specimen-based metrology
In Life Sciences, microscopes are mainly used to gather information on live specimen. It is not surprising then that assessing the performance of these microscopes involve using a live sample, particularly when it comes to quantifying the impact of imaging on live specimen. Measuring other performance criteria may not require stepping in the complexity of dealing with live samples. The rate of photobleaching, for instance, focuses on a fluorophore and its environment. To measure it, one can
Conclusion
We present a method and standard providing a non-ambiguous and singular readout reporting the phototoxicity of any imaging microscope system. The method yields a phototoxicity threshold value, which can be used to compare configuration settings in the same modality or even other. The protocol was engineered to be portable and convenient, so that it can be used in any lab. Using this approach, we demonstrate spinning-disk confocal imaging to be characterized by a lower phototoxicity threshold
Acknowledgments
We thank Johan Henriksson for a stimulating discussion. This work was funded by the European Commission FP7 Health (project “LEISHDRUG”, www.leishdrug.org, SLS) and ICT (project “MEMI”, www.memi-fp7.org, SLS), the Conny-Maeva Foundation (USA), and the Institut Pasteur Paris. J.D. received a fellowship from the Pasteur-Foundation (New York).
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