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Single-Cell Biophysics: Measurement, Modulation, and Modeling
Poster Abstracts
68
47-POS
Board 24
Single-Cell Time-Series Measurements of a Library of Strains with Single Molecule
Sensitivity
Michael J. Lawson
, Daniel Camsund, Jimmy Larsson, Ozden Baltekin, David Fange, Johan Elf.
Uppsala University, Uppsala, Sweden.
We have developed a method to perform sensitive, time-lapse imaging at the single-cell level for
many different strains simultaneously. The method has three components. The first is library
generation. We have created a library of plasmids, each with a constitutively expressed sgRNA
and a uniquely associated barcode RNA (driven by an inducible and orthogonal expression
system). We transform these plasmids into Escherichia coli containing chromosomally expressed
dCas9 to allow for knockdown of the sgRNA-targeted gene.
The second component is single-cell phenotyping. We load the library of strains into a
microfluidic device, which is mounted on a microscope. Here we can observe growth of isogenic
microcolonies of every strain in the library over many generations, as well as count and localize
single molecules and quantify any other phenotype discernable via microscopy.
The third and final step is to genetically identify each strain. The chip design allows for
observing thousands of strains in one experiment, however the loading is random. We have
developed a multiple round oligo-paint based approach to make an encoding between two
fluorescently labeled primers (Cy3 and Cy5) and the unique barcode RNAs. In every round a
probe with one of the fluorescent markers hybridizes to each barcode, thus providing a binary
readout. After successive rounds, the cells in each trap have an associated binary word that
uniquely identifies the strain. The encoding from fluorescent primers to barcode RNA sequence
is achieved via template oligos, which are amplified by hybridization-round specific primers
from an oligo pool.
As a proof of principle, we implemented a library of three strains with different levels of LacY-
Ypet expression. Our method could differentiate between a strain with one molecule every
second generation and a strain with one molecule every fifth generation.