7 applied similar FISH-based genotyping to cells grown within a continuous culturing device, greatly extending the duration of time-lapse imaging and expanding the range of measurable dynamic phenotypes. This powerful method enabled screening based on brief time-lapse imaging with comprehensive genotype-to-phenotype correspondence. 6 recently tagged a pooled library with barcodes that could be detected with fluorescence in situ hybridization (FISH). Recognizing the need to expand image-based screens to unstructured pooled libraries, Emanuel et al. Well-based microscopy assays are frequently employed for libraries of limited size, particularly for structured libraries (that is, where known mutants belong to addressable compartments) 5. Technologies based on microscopy allow for a wider variety of phenotypes to be quantified and screened, and often at much higher accuracy than even the best imaging flow cytometers 4. Droplet fluidics can in principle allow for time-lapse monitoring 3, but tracking individual growing cells remains problematic, and low-resolution images fail to accurately capture important phenotypic features, such as localization patterns, segregation at division, cell-cycle effects and expression dynamics. Specifically, because mutants of interest tend to be rare, it is often the case that many hits in cytometry-based screens are false positives arising from phenotypic outliers. Furthermore, because each cell is probed only once, cytometers struggle to distinguish genetically stable properties from transient phenotypic heterogeneity 2. However, these methods only provide endpoint snapshots, and therefore offer little information about growth, intracellular dynamics and responses to environmental changes 1. Their power depends on the size and complexity of the mutant libraries that can be considered, the types of properties that can be measured, the ability to control growth conditions while ensuring spatiotemporal uniformity, and-because many mutations only change the distribution of phenotypes-on how reliably those distributions are sampled for each mutant.įlow cytometry is the cornerstone of ultrahigh-throughput single-cell screening technologies. Genetic screens play a fundamental role in biology by identifying which genes or parts of genes determine phenotypic properties. This revealed novel design principles in synthetic biology and demonstrated the power of SIFT to reliably screen diverse dynamic phenotypes. We applied SIFT to identify a set of ultraprecise synthetic gene oscillators, with circuit variants spanning a 30-fold range of average periods. This platform can characterize tens of thousands of cell lineages per day, making it possible to accurately screen complex phenotypes without the need for barcoding or genetic modifications. After imaging and tracking individual bacteria for tens of consecutive generations under tightly controlled growth conditions, cells of interest are isolated and propagated for downstream analysis, free of contamination and without genetic or physiological perturbations. Here we introduce SIFT, single-cell isolation following time-lapse imaging, to address these limitations. Single-cell genetic screens can be incredibly powerful, but current high-throughput platforms do not track dynamic processes, and even for non-dynamic properties they struggle to separate mutants of interest from phenotypic outliers of the wild-type population.
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