![]() ![]() They enable high molecular specificity via direct fusion to proteins of interest using molecular cloning techniques. Genetically encoded fluorescent proteins overcome this tradeoff. Even PCR, which is highly sequence-specific and can be performed in single cells ( Bengtsson et al 2005, Peixoto et al 2004), requires that cells be lysed, preventing sequential sampling from the same cell over time. Southern, northern, and western blots are similarly compromised: they have high molecular specificity but lack spatial resolution since they measure molecular abundance at the population level, not the single-cell level. For instance, electron micrographs have extremely high spatial resolution, but they generally cannot image specific molecules, and the temporal dimension is lost since sample preparation requires fixation. In many standard biological assays there is a tradeoff among molecular specificity, spatial resolution, and temporal sampling. Finally, we describe recent advances in imaging technology, focusing especially on platforms that allow the simultaneous perturbation and quantitative monitoring of biological systems. Additionally, we discuss studies where quantitative microscopy facilitates the assembly of detailed 4D lineages in developing organisms. We highlight examples where single-cell analysis provides unique mechanistic insights into cellular processes that cannot be otherwise resolved in bulk assays. Here we review studies that combine time-lapse fluorescence microscopy and automated image analysis to investigate dynamic events at the single-cell level. Computational image analysis has catalyzed this evolution, enabling rapid and automated processing of large datasets. ![]() Though initially used to make largely qualitative assessments of protein levels and localizations, fluorescence microscopy has since evolved to become highly quantitative and high-throughput. ![]() The cloning of GFP 15 years ago revolutionized cell biology by permitting visualization of a wide range of molecular mechanisms within living cells. ![]()
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