Screening for FRET sensor performance

Improvement of VAmPIRe`s dynamic range by rational engineering is limited by the lack of structural information. Molecular evolution by random mutagenesis has proven powerful for engineering of enzymes and fluorescent proteins (Goedhart et al. 2010) (Shaner et al. 2008) (Ai et al. 2006) (Bevis and Glick 2002). With the initial aim to increase VAmPIRe`s dynamic range, we established the first functional screen that allows high-throughput testing of fluorescent sensor variant libraries in bacterial colonies.

4.4.4.1 Bacterial FRET screen

With a major contribution of Julia Litzlbauer, we designed the first functional bacterial colony assay for the directed evolution of FRET sensors. Colony imaging during induction of aptamer transcription allows to detect the off and the on state of the biosensor. Selection criteria included both the initial FRET ratio and the dynamic range.

We tested different induction reagents including tetracycline (TC), doxycycline and anhydrotetracycline (aTC) in various concentrations and observed the best induction with aTC. aTC is known to be more stable and bind the Tet repressor more efficiently than TC

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(Gossen and Bujard 1993) (Oliva et al. 1992). In contrast to TC, aTC does not interfere with the bacterial translation apparatus. This would be advantageous for the screening of sensors detecting proteins.

As the FRET signal depends on many different aspects, the absolute FRET ratio is not comparable between different experiments. This variability was balanced by integration of a standard FRET sensor of known performance. Given a standardized experimental procedure including time point of imaging after transformation and plate medium thickness still colony size and starting ratios of control sensors showed fairly high variation. Technical improvements include uniforms plate illumination and standardized medium composition (Julia Litzlbauer).

Although using the same promoter and bacterial strain, sensor and aptamer expression levels were not reliable. Similar differences in RNA expression in different bacteria upon aTc induction has been observed in other studies (Valencia-Burton et al. 2009) (Yiu et al. 2011). Possible reasons include leakiness of the TetOn system, pH changes, bacterial growth and metabolism as well as subcellular RNA distribution. Previous studies show that RNA levels after induction can vary significantly between individual bacteria within the same population (Figure 70). Inter-experimental differences are even more pronounced (Figure 70B).

Figure 70 RNA induction in bacteria using the TetON system. (A) Schematic of a bacterium showing parameters that influence FRET readout in an RNA induction experiment. (B, C) RNA kinetics in single E. coli cells upon induction with aTC. Time course of total fluorescence in individual E. coli cells in two representative experiments. RNA levels were recorded using the split-GFP reporter (see 1.5.3.3). The t=0 time is defined as the moment of aTC addition to cells. Measurements are taken at 2-min intervals. (Valencia-Burton et al. 2009)

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One way to stabilize RNA induction is to assure stable aTC levels within the bacteria. The standard assumption emerging from population measurements has been that cells exposed to steady levels of inducer would produce a steady transcription activity. Conversely, real- time RNA profiling within single cells reveals that drug-inducible transcription leads to the pulsating, cell-cycle dependent generation of mRNAs (Le et al. 2005). We observed FRET fluctuations 1-3 h after aTC addition that are probably due to active, unspecific efflux pumping mechanisms (Nikaido 1996). Bacterial xenobiotic metabolism of aTC can be bypassed by host bacterial cells that lack efflux pumps (ΔacrAB) and presumably tolerate more aTC (Okusu et al. 1996) (Figure 71A). We already tested different efflux pump inhibitors (EPIs) including chloropromazine and cyanide m-chlorophenylhydrazone (Stavri et al. 2007) (Pagès and Amaral 2009). Combined EPI and aTC application didn`t have any effect on the induction experiment (data not shown).

Figure 71 Effect of acrAB efflux pumps on RNA induction by TC. (A)Structural organization of the tripartite efflux system, acrAB-TolC from E. coli. (www.mpexpharma.com/efflux.html) (B) Induced RNA expression in wild type E. coli with (dark grey) and without (light grey) 400 ng/mL TC and E. coli ΔacrAB (black) with TC. MS2-RNA concentration was determined in a cell population by fluorescence correlation spectroscopy (FCS). Cells were grown at constant density in M9 medium at 30°C. (Le et al. 2005)

The bacterial screen has proven suitable to increase the dynamic range of the RNA FRET sensor from 80 % to 160 % (Figure 43). Insertion of randomized linkers was more successful than random mutagenesis of the Rsg peptide itself. As nature and number of variants with

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better characteristics remains unpredictable, further rounds of screening have to follow. High throughput screening requires automated colony analysis. Elisabeth Hopp (Department Borst) developed a program (Matlab) that selects colonies according to fixed criteria. This program is also applied for the screening of Calcium sensors. Further optimization includes the format of high-throughput protein expression and in vitro test measurements which could be performed in 96-well plates.

It remains unclear if most of the variants bind without changing their FRET signal or if linker insertion also modulates peptide-aptamer affinity. In the latter case, an additional bacterial antitermination assay (see 4.3.1) could preselect for sensors that still interact with the RRE aptamer.

Evolutionary methods such as the one introduced and used here, although not exhaustively, may become increasingly important in optimizing performance of many biosensors relying on FRET between fluorescent proteins.

4.4.4.2 Cellular screening

Bacterial screening profits from ease of manipulation resulting in a big library size that can be screened. So far, we validated sensors from the bacterial screen first in vitro and afterwards in a cellular assay. Screening in mammalian cells is more expensive and allows a lower number of variants to be screened but would meet the demands of functionality for live cell imaging. Especially aptamer folding and affinity of reporter and RNA construct can vary in different systems. A recently introduced method combines generation and cellular analysis (Piljid et al. 2011) of a set of 36 different FRET reporters. The cloned variants were spotted on DNA arrays serving as a platform for reverse transfection of and subsequent semiautomated microscopy of HEK-293 cells.

There are several ways of testing cellular sensor performance. The first possibility requires a sensor library that is expressed transiently in a mammalian cell line expressing the aptamer under the control of an inducible promoter, similar to the bacterial screen. In another approach, a stable cell line permanently expressing the aptamer could be transiently transfected with the sensor library and stressed resulting in stress granule formation. A third way of testing library reporters consists of infection by viruses with an aptamer-tagged RNA

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genome. In each case FRET ratio changes are recorded and cellular DNA is isolated and sequenced. Viral infection was already tested using the Semliki Forest Virus (SFV) with the RRE aptamer repeats incorporated (data not shown). On one hand the virus titer was low probably due to the repetitive sequences that were introduced, on the other hand infection of HEK 293 T cells resulted in low cell survival.

Another possible selection procedure includes cell FACSing (fluorescence activated cell sorting) according to the FRET ratio (AW Nguyen and PS Daugherty 2005). Beyond the technical challenge this method would include selection and pooling of similar low FRET ratios before RRE expression and a second FACS step after coexpression of the aptamer thereby selecting for high FRET ratio.

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Figure 72 Workflow for the cellular screening of FRET sensors. A library was constructed by cloning a specific protein domain into different FRET scaffolds with variable linkers. For reverse transfection, library plasmid DNA was spotted on LabTek coverglass. Images were acquired by semiautomated microscopy and analyzed for high performance (Piljid et al. 2011).

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