Kinetics of dCas9 target search in Escherichia coli.

How fast can a cell locate a specific chromosomal DNA sequence specified by a single-stranded oligonucleotide? To address this question, we investigate the intracellular search processes of the Cas9 protein, which can be programmed by a guide RNA to bind essentially any DNA sequence. This targeting flexibility requires Cas9 to unwind the DNA double helix to test for correct base pairing to the guide RNA. Here we study the search mechanisms of the catalytically inactive Cas9 (dCas9) in living Escherichia coli by combining single-molecule fluorescence microscopy and bulk restriction-protection assays. We find that it takes a single fluorescently labeled dCas9 6 hours to find the correct target sequence, which implies that each potential target is bound for less than 30 milliseconds. Once bound, dCas9 remains associated until replication. To achieve fast targeting, both Cas9 and its guide RNA have to be present at high concentrations.

Pointwise error estimates in localization microscopy.

Pointwise localization of individual fluorophores is a critical step in super-resolution localization microscopy and single particle tracking. Although the methods are limited by the localization errors of individual fluorophores, the pointwise localization precision has so far been estimated using theoretical best case approximations that disregard, for example, motion blur, defocus effects and variations in fluorescence intensity. Here, we show that pointwise localization precision can be accurately estimated directly from imaging data using the Bayesian posterior density constrained by simple microscope properties. We further demonstrate that the estimated localization precision can be used to improve downstream quantitative analysis, such as estimation of diffusion constants and detection of changes in molecular motion patterns. Finally, the quality of actual point localizations in live cell super-resolution microscopy can be improved beyond the information theoretic lower bound for localization errors in individual images, by modelling the movement of fluorophores and accounting for their pointwise localization uncertainty.

Application of Noncanonical Amino Acids for Protein Labeling in a Genomically Recoded Escherichia coli.

Small synthetic fluorophores are in many ways superior to fluorescent proteins as labels for imaging. A major challenge is to use them for a protein-specific labeling in living cells. Here, we report on our use of noncanonical amino acids that are genetically encoded via the pyrrolysyl-tRNA/pyrrolysyl-RNA synthetase pair at artificially introduced TAG codons in a recoded E. coli strain. The strain is lacking endogenous TAG codons and the TAG-specific release factor RF1. The amino acids contain bioorthogonal groups that can be clicked to externally supplied dyes, thus enabling protein-specific labeling in live cells. We find that the noncanonical amino acid incorporation into the target protein is robust for diverse amino acids and that the usefulness of the recoded E. coli strain mainly derives from the absence of release factor RF1. However, the membrane permeable dyes display high nonspecific binding in intracellular environment and the electroporation of hydrophilic nonmembrane permeable dyes severely impairs growth of the recoded strain. In contrast, proteins exposed on the outer membrane of E. coli can be labeled with hydrophilic dyes with a high specificity as demonstrated by labeling of the osmoporin OmpC. Here, labeling can be made sufficiently specific to enable single molecule studies as exemplified by OmpC single particle tracking.

Simulated single molecule microscopy with SMeagol.

UNLABELLED: SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data. AVAILABILITY AND IMPLEMENTATION: SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction-diffusion simulations. Documentation, source code and binaries for Mac OS, Windows and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net CONTACT: johan.elf@icm.uu.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.