Tracking single molecules in uncharted territory: A single-molecule method to study kinetics in live bacteria

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(1)Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1957. Tracking single molecules in uncharted territory A single-molecule method to study kinetics in live bacteria JAVIER AGUIRRE RIVERA. ACTA UNIVERSITATIS UPSALIENSIS UPPSALA 2020. ISSN 1651-6214 ISBN 978-91-513-0992-7 urn:nbn:se:uu:diva-417642.

(2) Dissertation presented at Uppsala University to be publicly examined in Room A1:111a, BMC, Husargatan 3, Uppsala, Friday, 9 October 2020 at 14:15 for the degree of Doctor of Philosophy. The examination will be conducted in English. Faculty examiner: Professor Dmitri N. Ermolenko (University of Rochester Medical Center). Abstract Aguirre Rivera, J. 2020. Tracking single molecules in uncharted territory. A single-molecule method to study kinetics in live bacteria. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1957. 60 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0992-7. The synthesis of proteins, also known as translation, is a fundamental process in every living organism. The steps in the translation of genetic information to functional proteins have been meticulously studied, mostly using in vitro techniques, yielding a detailed model of their mechanisms. However, the use of minimal cell-free systems allows for the possibility to miss interactions from absent components or that reactions are affected by the buffer composition. The work presented in this thesis opens a way to study the kinetics of complex molecular processes, like protein synthesis, directly inside live bacterial cells in real time. We developed and optimized a method to deliver dye-labeled macromolecules inside live cells and generate a kinetic model of the particle’s interactions based on its diffusion inside the cell. This method facilitated the study of translation elongation and initiation directly in live cells. Our measurements of reaction times of tRNA in the ribosome, agree with previous reports from in vitro techniques. We further applied the method to examine the effects of three aminoglycoside antibiotics and erythromycin directly in live cells. The aminoglycoside antibiotics slowed-down protein synthesis 2- to 4-fold, while the number of elongation cycles per initiation event decreased significantly. In the case of erythromycin, cells showed a 4-fold slower protein synthesis. Additionally, we measured the kinetics of sequence-specific effects of erythromycin: translational arrest, and peptidyl-tRNA drop-off; these in vivo measurements revealed a complex mechanism of action of the drug, in agreement with models suggested by previous experiments. Additionally, we applied the method to measure the effects, on the kinetics of protein synthesis, caused by modifications in the C-terminal tail of the S13 ribosomal protein. Our measurements showed that specific mutations led to different changes in the occupancy and dwell-time of labeled-tRNA in the ribosome. To summarize, the present work will guide the reader through the development of a method to study the kinetics of protein synthesis directly in live bacterial cells, as well as its application to characterize the effects of different antibiotics within the complex environment of a living organism. Keywords: single-molecule, protein synthesis, fluorescence microscopy, antibiotics, aminoglycosides, macrolides, apramycin, gentamicin, paromomycin, S13, translation, bacteria Javier Aguirre Rivera, Department of Cell and Molecular Biology, Molecular Systems Biology, Box 596, Uppsala University, SE-751 24 Uppsala, Sweden. © Javier Aguirre Rivera 2020 ISSN 1651-6214 ISBN 978-91-513-0992-7 urn:nbn:se:uu:diva-417642 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417642).

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(54) tribute to the discussion of this translation factor’s mechanism of action. However, currently, our measurements lack the temporal resolution to quantify the dwell-time of single EF-Tu bindings to the ribosome, taking into account previous estimates of its dwell-time in the ribosome, which are in the range of 23 ms53 as calculated from in vitro experiments. Experimental results First, we adopted a previously developed labeling scheme of the elongation factor, used for smFRET by introducing a cysteine in position 348–far from the tRNA binding site and the GTPase center–and reacting it with a Cy5-maleimide dye (GE Healthcare) as in54,55. We purified the C-terminal His-tagged EF-Tu (E348C mutant) expressed from a pET28a IPTG inducible plasmid in E. coli BL21(STAR) using a Ni-Sepharose HisTrap column (GE Healthcare). The eluted protein was treated with a TEV protease (Genscript) to cleave the His-tag and ran through a Ni-Sepharose HisTrap column. The whole purification process was done in buffer A [10 mM Tris-HCl pH 7.6, 5 mM MgCl2, 25 µM GDP, 6% glycerol] at 4°C. The Ni-Sepharose column was equilibrated with buffer A + 10 mM imidazole, and the protein was eluted with buffer A + 150 mM imidazole. After His-tag cleavage, the EF-Tu was reacted with ten times molar excess of TCEP, then mixed with a 1:1 molar ratio of Cy5-maleimide in dimethylformamide and left incubating overnight at 4°C. The reaction was quenched with 300 mM of 2-mercaptoethanol, and the unreacted dye was separated using a NAP-10 column (GE Healthcare). The [Cy5]EF-Tu was then further purified in a Superdex 200 Increase 10/300 GL (GE Healthcare) size exclusion column.. Figure 8. Electro mobility shift assay of EFTu wt and [Cy5]EF-Tu ± Phe-tRNAPhe. Binding of the negatively charged tRNA causes a faster migration of the complex. In the left panel the protein is coomasie-stained, and in the right panel is the 650 nm channel to observe Cy5 fluorescence. 29.

(55) The tRNA binding activity of the protein was tested by performing an electromobility shift assay. In this assay, pre-formed ternary complexes PhetRNAPhe•[Cy5]EF-Tu•GTP were ran through a native polyacrylamide gel, and their migration was compared with that of [Cy5]EF-Tu•GTP without tRNA. Our assayed labeled protein showed tRNA binding activity comparable to the unlabeled wild-type EF-Tu (Fig. 8). Further, to deliver the [Cy5]EF-Tu into E. coli DH5α, 10 pmol of the labeled protein were mixed with 20 µl of the cells and electroporated in the same way as labeled-tRNA (Fig. 5a), using 1.9 V (time constant of 5.8 ms). The cells were left to recover in rich defined media (RDM) for 30 min at 37 °C. After recovery, the cells were pelleted and washed three times with PBS + 100 mM NaCl + 0.005% Triton X100 as in10. Data acquisition and analysis were performed in the same way as described in the previous section though with a change in tracking parameters–particle search radius changed from 20 pixels to 8 pixels–in an attempt to reduce tracking artifacts. Based on the lowest AIC, the selected model showed seven diffusion states. We considered four of these states biologically relevant—state 1 with a diffusion constant (D) of ~0.001 μm2/s, state 2 with a D of ~0.08 μm2/s, state 3 with a D of ~1.2 μm2/s, and state 4 with a D of ~5 μm2/s—with the remaining three overlapping the other states (0.001 μm2/s, 0.08 μm2/s, and 5.5 μm2/s). Based on previous tracking of ribosomes6,44 and tRNA12,56 it is likely that the slowest diffusion states (~0.001 μm2/s, and ~0.08 μm2/s) correspond to [Cy5]EF-Tu interacting with the ribosome. In the case of the slowest state, potentially, EFTu could be forming part of a filamentous structure in complex with the protein MreB57. By coarse-graining the model using a threshold of 1 μm2/s, we estimated that the occupancy of [Cy5]EF-Tu was ~30% in the slow-state (ribosome-associated), and ~70% in the fast-state (free EF-Tu and in ternary complex with tRNA). Although our results conflict with the main conclusions in Mustafi et al.8, that 60% of the EF-Tu population is in a slow-diffusion state, they are in line with an alternative 3-state model,—showing ~20% of the EFTu in a state slower than 1 μm2/s—which was also generated in the same study and which had a similar statistical significance as the chosen model. The difference between our results and the estimates from the mentioned previous study8, could be due to inherent differences in how the models were built. While our model is estimated by measuring the transitions of the particle between different diffusion states, the model in the prior study was built by fitting the mean-square displacement distribution to discrete static diffusion states. Moreover, since EF-Tu interactions with the ribosome are faster than the camera frame rate used for the fluorescence data acquisition, the present analysis lacks the temporal resolution to address the dwell-times in the differ-. 30.

(56) ent diffusion-states. Therefore, I will not discuss them any further in this section. However, this work sets a foundation for other microscopy techniques, such as MINFLUX58, to address the fast kinetics of this process.. Figure 9. Spatial distribution of [Cy5]EF-Tu in E.coli DH5α cells, based on the coarse-grained two-state model (n=28918 steps). The panels on the left show plotted locations on normalized cell width (y, -1 to 1) and length (x, 0 to 1) coordinates. The panels on the right show the same data but excluding particles at the poles and center of the cell (within 0.2<x<0.4 or 0.6<x<0.8) projected on the short cell radial axis (solid lines). Dashed lines represent uniform distributions in the cytoplasm (orange) and nucleoid excluded regions (blue).. The spatial distribution of the tracked [Cy5]EF-Tu in the slow- and fast-state provides further information about the biological certainty of the diffusion states. In this work, the [Cy5]EF-Tu in the slow-state (slower than 1 μm2/s) is, apparently, nucleoid-excluded (Fig. 9), which agrees with the spatial distribution of tRNA in the slow state, and that of translating ribosomes6,44. On the other hand, the diffusion in the fast-state (faster than 1 μm2/s) takes place homogeneously within the cell (Fig. 9). As a control experiment, we proceeded to perturb the interaction of EF-Tu with the ribosome by performing the tracking of [Cy5]EF-Tu in cells exposed to the antibiotic kirromycin. This drug binds EF-Tu and “locks” the protein into a similar conformation to that adopted when bound to GTP, even when it is in fact bound to GDP, thus preventing the dissociation of the molecule from the ribosomal A-site after GTP hydrolysis (reviewed in37), and interfering with the arrival of the next ternary complex. The diffusion of the antibiotic into the cytoplasm of E. coli cells is rather limited with a reported MIC above 128 μg/ml59; therefore, to determine an adequate concentration of the antibiotic for the microscopy experiments, we tested the growth of E. coli DH5α cells exposed to the antibiotic. First, we conducted a growth experiment where we 31.

(57) added cells to increasing concentrations (0, 10, 100, 150, 250, 300, and 500 μg/ml) of the antibiotic in RDM and allowed them to grow for 20 h in a plate reader, at 37ºC and continuous orbital shaking. The antibiotic at concentrations over 100 μg/ml inhibited cell growth (Fig. 10).. Figure 10. Growth curves of E. coli DH5α with increasing concentrations of kirromycin. Measurements were taken every 5 min during 20 h at 37°C as technical triplicates.. Moreover, we performed a microfluidics growth experiment to characterize the effect of the antibiotic on growing cells. In this experiment, we loaded a “Mother Machine60” microfluidics chip with E. coli DH5α and let the cells grow for 1h in RDM to ensure normal growth. We then supplied half of the chip with RDM + 150 μg/ml of kirromycin, and the remaining half was kept on RDM as a control. The cells exposed to the antibiotic drastically reduced their growth rate and stopped dividing within 1h, compared to the cells in the control side, which grew normally. We then proceeded to perform microscopy experiments with [Cy5]EF-Tu in cells exposed to 150 μg/ml of kirromycin for 1 to 1.5h. The coarse-grained model obtained with the HMM analysis of [Cy5]EF-Tu in cells treated with kirromycin, showed an EF-Tu occupancy in the slow-state of ~50%, an increase of ~20% compared to the EF-Tu in untreated cells (Fig. 11). This increase in occupancy suggests that kirromycin traps a fraction of [Cy5]EF-Tu in the ribosome. Moreover, these results strengthen the certainty that the tracked fluorescent particle is indeed EF-Tu actively participating in translation elongation.. 32.

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