Systems Biology


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0 Q&A 645 Views Jan 20, 2023

Genome-wide CRISPR-based screening is a powerful tool in forward genetics, enabling biologic discovery by linking a desired phenotype to a specific genetic perturbation. However, hits from a genome-wide screen require individual validation to reproduce and accurately quantify their effects outside of a pooled experiment. Here, we describe a step-by-step protocol to rapidly assess the effects of individual sgRNAs from CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) systems. All steps, including cloning, lentivirus generation, cell transduction, and phenotypic readout, can be performed entirely in 96-well plates. The system is highly flexible in both cell type and selection system, requiring only that the phenotype(s) of interest be read out via flow cytometry. We expect that this protocol will provide researchers with a rapid way to sift through potential screening hits, and prioritize them for deeper analysis in more complex in vitro or even in vivo systems.

Graphical abstract

0 Q&A 3289 Views Oct 20, 2019
Understanding the translation of genetic variation to phenotypic variation is a fundamental problem in genetics and evolutionary biology. The introduction of new genetic variation through mutation can lead to new adaptive phenotypes, but the complexity of the genotype-to-phenotype map makes it challenging to predict the phenotypic effects of mutation. Metabolic models, in conjunction with flux balance analysis, have been used to predict evolutionary optimality. These methods however rely on large scale models of metabolism, describe a limited set of phenotypes, and assume that selection for growth rate is the prime evolutionary driver.

Here we describe a method for computing the relative likelihood that mutational change will translate into a phenotypic change between two molecular pathways. The interactions of molecular components in the pathways are modeled with ordinary differential equations. Unknown parameters are offset by probability distributions that describe the concentrations of molecular components, the reaction rates for different molecular processes, and the effects of mutations. Finally, the likelihood that mutations in a pathway will yield phenotypic change is estimated with stochastic simulations.

One advantage of this method is that only basic knowledge of the interaction network underlying a phenotype is required. However, it can also incorporate available information about concentrations and reaction rates as well as mutational biases and mutational robustness of molecular components. The method estimates the relative probabilities that different pathways produce phenotypic change, which can be combined with fitness models to predict evolutionary outcomes.
0 Q&A 8032 Views Jul 5, 2018
High-throughput screening of a DNA library expressed in a bacterial population for identifying potentially rare members displaying a property of interest is a crucial step for success in many experiments such as directed evolution of proteins and synthetic circuits and deep mutational scanning to identify gain- or loss-of-function mutants.

Here, I describe a protocol for high-throughput screening of bacterial (E. coli) microcolonies in gel beads. Single cells are encapsulated into monodisperse water-in-oil emulsion droplets produced with a microfluidic device. The aqueous solution also contains agarose that gelates upon cooling on ice, so that solid gel beads form inside the droplets. During incubation of the emulsion, the cells grow into monoclonal microcolonies inside the beads. After isolation of the gel beads from the emulsion and their sorting by fluorescence activated cell sorting (FACS), the bacteria are recovered from the gel beads and are then ready for a further round of sorting, mutagenesis or analysis. In order to sort by FACS, this protocol requires a fluorescent readout, such as the expression of a fluorescent reporter protein. Measuring the average fluorescent signals of microcolonies reduces the influence of high phenotypic cell-to-cell variability and increases the sensitivity compared to the sorting of single cells. We applied this method to sort a pBAD promoter library at ON and OFF states (Duarte et al., 2017).

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