Plasmonic Nanosensors Reveal a Height Dependence of MinDE

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Plasmonic Nanosensors Reveal a Height Dependence of MinDE Protein Oscillations on Membrane Features Weixiang Ye, Sirin Celiksoy, Arpad Jakab, Alena Khmelinskaia, Tamara Heermann, Ana Raso, Seraphine V. Wegner, Germán Rivas, Petra Schwille, Rubén Ahijado-Guzmán, and Carsten Sönnichsen J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.8b07759 • Publication Date (Web): 27 Nov 2018 Downloaded from http://pubs.acs.org on December 1, 2018

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Journal of the American Chemical Society

Plasmonic Nanosensors Reveal a Height Dependence of MinDE Protein Oscillations on Membrane Features Weixiang Ye1,2, Sirin Celiksoy1, Arpad Jakab1, Alena Khmelinskaia3, Tamara Heermann3, Ana Raso3,4, Seraphine V. Wegner5, Germán Rivas4, Petra Schwille3, Rubén Ahijado-Guzmán1*and Carsten Sönnichsen1* Institute of Physical Chemistry, University of Mainz, Duesbergweg 10-14, 55128 Mainz, Germany Graduate School of Materials Science in Mainz, Staudinger Weg 9, 55128 Mainz, Germany 3 Department of Cellular and Molecular Biophysics, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany 4 Centro de Investigaciones Biológicas-CSIC, c/Ramiro de Maeztu 9, 28040, Madrid, Spain 5 Max-Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany 1 2

Optical dark-field spectroscopy, plasmonic nanosensors, Min protein oscillations, membrane curvature, cardiolipin, axial resolution ABSTRACT: Single-particle plasmon spectroscopy has become a standard technique to detect and quantify the presence of unlabeled macromolecules. Here, we extend this method to determine their exact distance from the plasmon sensors with subnanometer resolution by systematically varying the sensing range into the surrounding by adjusting the size of the plasmonic nanoparticles. We improved current single-particle plasmon spectroscopy to record continuously for hours the particle spectra of thousands of nanoparticles of different sizes simultaneously within two seconds. We apply this technique to study the interaction dynamics of bacterial Min proteins with supported lipid membranes of different composition. Our experiments reveal a surprisingly flexible operating mode of the Min proteins: In the presence of cardiolipin (CL) and membrane curvature induced by nanoparticles, the protein oscillation occurs on top of a stationary MinD patch. Our results reveal the need to consider membrane composition and local curvature as important parameters to quantitatively understand the Min protein system and could be extrapolated to other macromolecular systems. Our label-free method is generally easily implementable and well suited to measure distances of interacting biological macromolecules.

INTRODUCTION The plasmon resonance of gold nanoparticles is sensitive to the local adsorption, desorption, binding and dynamics of macromolecules within the nanoparticle’s sensing volume. The sensing volume or plasmonic penetration depth depends on the nanoparticle dimensions.1-5 Here, we systematically change the plasmonic penetration depth to resolve with sub-nanometer resolution the height of a dynamic protein assembly taking place on a supported membrane. In this work, we introduce our new method by investigating Min protein oscillations. The Min protein oscillations, defining the spatial positioning of the cell division site in E.coli, are one of the best examples of dynamical long range pattern formation.6-8 Understanding the underlying features of this self-organizing

system provides a general framework for creating long-range patterns in chemical systems.9 Despite the many quantitative studies of the Min protein system in vitro, mostly on flat supported bilayers, some details of the molecular processes on the nanoscale are still insufficiently understood. For instance, an earlier plasmon sensor study suggested an immobile protein layer on the membrane that was never observed in fluorescence-based studies.10 In this work, we show how single-particle plasmon spectroscopy (NanoSPR)11 can determine details on the exact axial location of the dynamics taking place during the Min cycle on membranes covering the nanoparticles. Our experiments reveal a surprisingly flexible operating mode of the Min wave – the Min cycle not only occurs directly on top of a lipid membrane but can also occur over a stationary MinD protein patch. This stationary MinD patch forms on cardiolipin (CL) containing membranes covering highly curved nanoparticles. The Min protein wave needs a minimum of two proteins, MinD and MinE.8 MinD self-assembles on the bacterial inner membrane forming continuous patches. MinE is concentrating at the edges of these patches and releases MinD back to the cytoplasm. Once a standing MinDE protein wave forms, the mid-cell oscillation node defines the starting point for the formation of the division ring.12,13 There are several models describing the Min protein cycle and its kinetics in considerable detail.8,12-19 However, for most of these theoretical models it is challenging to take the membrane composition and curvature into consideration. Most of what is known about the details of the Min protein cycle in vitro was studied using fluorescently labeled MinD, MinE and/or MinC proteins on supported lipid membranes. On such ‘infinite’, flat membranes, the Min proteins form traveling waves with wavelengths in the tens of micrometers and oscillation periods in the minute timescale.8,10,13 Whereas fluorescence microscopy permits to resolve accurately the lateral distribution of proteins in these oscillations, it is not possible to resolve the axial location of dynamic protein interaction events and sometimes it is necessary to account for perturbations of the dynamics by the fluorescent label.10 Recently, high-speed atomic force microscopy has been used recently to resolve the axial location of dynamic MinDE oscillations on membrane patches bellow µm size diameter.18

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NanoSPR is a novel label-free alternative technique to measure local interactions of macromolecules with sub-nanometer spatial resolution, with the advantage of being a contact-free method and observation times limited only by the lifetime of the biological system.1,10,11 RESULTS AND DISCUSSION In NanoSPR, changes in the plasmon resonance wavelength  of single noble metal nanoparticles are observed as the local refractive index changes n around the particles (Figure 1a). To study the transient absorption of Min proteins on lipid bilayers, we used gold nanorods as sensors due to their better sensing properties compared, for instance, with spheres.20 The gold nanorods were immobilized on one side of a microfluidic flow chamber and covered by a lipid membrane. The membrane deposition induced a notable plasmon wavelength shift  (Figure 1b).21 After addition of the Min proteins (MinD, MinE in buffer containing ATP), a patterned oscillation or wave forms on top of the lipid bilayer. The local protein coverage translates into an oscillatory plasmon shift (Figure 1b, green line). The oscillation amplitude * characterizes the amount of change in refractive index during the Min cycle.

Figure 1. Principle of measurement. a. We determine the plasmon resonance wavelength res of each nanoparticle before (blue line) and after the adsorption of molecules (pink line). The plasmon shift res is an indication of the refractive index change n in the vicinity of the nanoparticle. b. We continuously monitor res of every nanoparticle as a function of time, starting in buffer (blue line). We observe the formation of a supported membrane over the particles (pink line, center inset) and the transient adsorption of the MinDE protein system (green line, inset right side with MinD in green, MinE in red, the lipid membrane in gray, and the particles in gold). The wave amplitude * (dashed lines) is extracted for further analysis. c. We systematically change the sensing distance dS of our nanoparticle sensor by varying their size. The oscillation amplitude * shows a maximum when the sensor’s sensing distance dS matches the thickness of the oscillating (dA) and static (dB) layers on top of the particle (inset center). If the particles’ sensing distance (symbolized by the blue area) is smaller/larger than dA+dB, the observed oscillation amplitude * is reduced (inset left/right, respectively).

Interestingly, our NanoSPR study showed an offset of the oscillation minimum compared to the situation of protein free membrane (Figure 1b), which suggested a static layer on the membrane. This static layer, with a size compatible to a monolayer of proteins, is consistently observed in NanoSPR but absent in previous fluorescence-based studies.10 To investigate this effect further and to pinpoint the exact thickness of the oscillatory and static layers on top of the membrane covering the nanoparticles, we designed a novel plasmonic sensing scheme that utilizes a unique ability of plasmonic nanosensors: the possibility to tune the sensing range into the surrounding by adjusting the size of the sensor itself. Once the sensing range matches the thickness of the sum of the static and oscillatory protein layer, the oscillation amplitude should exhibit a maximum (Figure 1c, center). If the sensing range is too small, the oscillation will occur outside of the most sensitive range, reducing the amplitude of the signal (Figure 1c, left). If the sensing range is too large, extending further into the solution, the oscillation is fully measured but the signal is ‘diluted’ (Figure 1c, right). Effectively, we used a systematic change of the sensing distance dS as a way to elucidate the position and thickness of the transient and the static Min protein layers. We believe this is the first time that the sensing distance dS of plasmonic nanosensors is used as a systematic variable in a NanoSPR measurement to obtain information about the distances of dynamic protein interactions.


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Figure 2. a. Real-color image of our encoded substrate viewed under dark-field illumination. The red spots are the scattered light of individual nanoparticles. Our software groups particles according to the 8 batches, indicated here by differently colored circles around the spots. 3 groups as example. 20x12 µm. b. The microscope setup allows to follow the dynamics of the plasmon resonance wavelength for each nanoparticle. Here we show three representative timetraces out of the more than 1000 obtained in a single experiment. c. We use histograms from the timetraces to extract the wave amplitude * for each individual particle.

The sensing distance dS of plasmonic nanoparticles is mainly a function of their volume.2-5,22 For this study, we used 8 different nanoparticle batches with the same plasmon resonance wavelength (670 nm) but with a strongly different average diameter, ranging from 19 nm to 50 nm (detailed characterization is included in the Supporting Information, Figures S1-S6 and Table S1). These particles showed sensing distances between 8 nm and 20 nm, which we estimated by simulations and experimentally confirmed by layer by layer assembly (see Supporting Information, Figure S4). The 8 groups of nanoparticles with different sizes were sequentially deposited in a flowcell. We recorded the positions within the field of view of a dark-field microscope in each deposition step to create a position-encoded nanosensor chip (Figure 2a).11 Each group of nanoparticles contained around 200 nanoparticles, totaling in approximately 1000–2000 within the field of view (approximately 328 µm x 328 µm). As a major technical improvement to earlier studies, where the time evolution of the plasmon resonance of only one particle (or at most a few particles) at a time, we now used spectral imaging to record the plasmon resonance of all the particles within the field of view in about 2 s (see Supporting Information, Figure S7). This new spectral imaging setup allows us to follow the Min protein oscillation at the membrane above every particle in the field of view simultaneously (Figure 2b). From each of the resulting 1000-2000 time-traces, we extracted the oscillation amplitude * using the characteristic peaks in a histogram of the plasmon resonance wavelength (Figure 2c). It is remarkable, that the nanoparticles do not influence the MinDE oscillation period (Figure S8).

function of sensing distance, should show a maximum value depending on the position and thickness of the oscillatory layer as explained in Figure 1c. The data in Figure 3 clearly confirms this general trend. In a more quantitative model, the exact shape of this curve is described by two parameters dA and dB (dynamic protein layer and static layer thicknesses, respectively) according to: * = S n exp(- dB/dS)(1-exp(- dA/dS)).22 This model describes the observed trends accurately and allows to extract the thickness of the static and dynamic layer of the Min protein oscillation with subnanometer axial resolution on top of the nanosensors.

To correlate this oscillation amplitude * with the sensing distance, we began with estimating the individual volume Vi of each particle using the measured maximum intensity Ii, and the plasmon resonance linewidth i through the relationship Vi2 ~ Ii·i2 (see Supporting Information, Figures S5 and S6 for details on the normalization).2-5 This particle volume Vi was then converted into an individual sensing distance dS,i using dS = 0.37·V1/3. The resulting data of such experiments are shown in Figure 3. Each dot represents one individual nanoparticle sensor, color-coded to the 8 different batches of particles (Note that there is some overlap between different particle batches). The oscillation amplitudes as a



Figure 3. Wave amplitudes * as function of the sensors’ sensing distance dS for three different membrane lipid compositions. Each dot corresponds to a single nanoparticle with the color corresponding to the eight nanoparticle batches (see Figure S2 and Table S1 for the color code and sizes). The lipid composition of the supported bilayer are: a. E. coli lipids (PE/PG/CL) b. DOPC/DOPG lipids in (70:30) ratio c. DOPC/DOPG/CL lipids in (70/25/5) ratio. The data follow the relationship * = S n exp(- dB/dS)(1-exp(- dA/dS)). Lines with the best fit to the data are shown in black. The corresponding parameters dA and dB are given on the side of the insets. In all three cases, the transient layer is around 5 nm in thickness, whereas the immobile layer extends about 10 nm on top of the gold nanoparticles only for membranes containing CL. The insets show the likely molecular model of the proteins wave (MinD green, MinE red, lipid membrane gray, particles gold).

layer dB of around 10 nm thickness. This value of 10 nm roughly corresponds to the thickness of the lipid membrane (about 5 nm) and a MinD monolayer patch (with a thickness of about 5 nm) on top of the curved membrane above the nanosensors. In all three cases, the dynamic layer dA (the MinDE proteins attaching and detaching during the cycle) had a thickness of approximately 5 nm as expected.18 All the obtained distances from three independent sets of experiments are summarized in the Supporting Information Table S2 and Figure S9. The observed differences in the Min protein wave dynamics on this special case of supported membranes with different composition above our nanosensors show a remarkable robustness of the Min system to the molecular details of the interaction. In the simplest cycle, the MinD attaches to the membrane (in its ATPbound dimeric state) forming a more or less continuous layer of MinD proteins (see zoomed areas of the membrane on the nanosensors schematically represented in Figure 4a and 4b). MinE is primarily recruited to the edges of this MinD layer, thereby forming a MinE rich area, releasing MinDE complexes, and slowly diffusing along the surface (see Figure 4a).13-18 In the light of our experiments, we propose to complement this model with a Min protein wave cycle that happens on top of a continuous MinD monolayer patch bound to membrane regions rich in CL near the curvature induced by nanoparticles below the membrane (see Figure 4b). Here, MinD from solution attaches to and detaches from membrane bound MinD (with the help of MinE). This model is in agreement with the MinD transfer and MinE sequestration model14 which showed that the wave forms whenever there is a concentration gradient of the surface-bound MinD. Our experimental results confirm the idea that the Min cycle does not require the removal of all MinD from the membrane but also forms on top of a MinD monolayer patch, which stabilizes on membranes containing CL in the vicinity of the perturbation induced by the nanoparticles below the membrane. It is important to note that our proposed model (Figure 4b) implies that MinE weakens the interaction of MinD to other MinD, not necessarily involving the MinD’s membrane targeting sequence, which is an important aspect to take into account for the development of a detailed molecular interaction model. Our results suggest that the MinD protein interacts electrostatically with membranes lacking CL (Figure 4c), but is able to insert its membrane targeting sequence into the membrane (Figure 4d) at local perturbations caused by CL at places with local curvature, induced for example by nanoparticles below. In the latter, the membrane targeting sequence rotates to allow its hydrophobic residues to interact with the lipid acyl chains,24,27-29 making the MinD-membrane interaction strong enough to resist MinD detachment via MinE-induced ATP hydrolysis.

Since the nanoparticles induce a local perturbation or bending of the membrane,23 this observed height variation could be connected to membrane curvature and/or membrane composition. MinD strongly binds to cardiolipin (CL), a lipid which induces negative curvature.24-26 To test the two hypotheses, we used three different membranes for our experiment: E. coli polar extract (PE/PG/CL) (Figure 3a) and mixtures from purified lipids DOPC/DOPG (70:30 molar ratio mixture) (Figure 3b) and DOPC/DOPG/CL (70:25:5 molar ratio mixture) (Figure 3c). Indeed, we observed a remarkable difference: On membranes lacking CL, the shape of the *(dS) curve was notably different, with a maximum shifted to much smaller values of sensing distance dS (Figure 3b). The values extracted for the static and dynamic layers in the other two cases (E. coli polar extract and CL containing membrane) reveal a static


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Journal of the American Chemical Society We have performed two sets of control experiments to verify our model of a permanently bound MinD monolayer patch near the nanoparticle-induced curvature: continuous NanoSPR measurements and Quartz Crystal Microbalance (QCM) experiments. In the former, we added MinD to NanoSPR substrates covered by the supported membranes (E. coli lipids, DOPC/DOPG or DOPC/DOPG/CL mixtures) while continuously monitoring the NanoSPR signals. The NanoSPR signal (res) showed a rapid attachment of MinD proteins to each of the membranes (see Supporting Information Figure S10). The subsequent rinsing with buffer removed some of the MinD, but an offset remained on the membranes containing CL. These permanently bound MinD patches also remained on the membrane after the addition of MinE. However, for the membrane lacking CL, it was possible to remove all of the MinD proteins within a couple of minutes (Figure S10b). QCM detects the total mass of adsorbed macromolecules on top of the entire centimeter sized surface area of the crystal – in contrast to NanoSPR, which is sensitive only to a small area around the nanoparticles. In the QCM experiment, we varied the nanoparticle surface density under a lipid membrane DOPC/DOPG/CL (70:25:5 molar ratio mixture). The amount of permanently membrane-bound MinD increased with particle densities (see Supporting Information Figure S11). This observation confirms that both CL and the local membrane curvature enhance the MinD membrane-affinity and apparently form permanently bound MinD monolayer patches. With regards to the novel method shown in this manuscript – to deduce the axial distance between molecular attachments and the nanoparticles by systematically varying the sensing distance - we performed a control experiment using a well described proteinprotein-membrane interacting system: the proteins FtsZ and ZipA.30-31 The experimental results recover the geometry expected from known protein dimensions (see Figure S6). We also confirmed the coverage of the nanoparticles with a lipid membrane by QCM and atomic force microscopy (Figure S12 and S13) in connection with results from plasmon spectroscopy, fluoresce microscopy, atomic force microscopy and fluorescence recovery after photobleaching (FRAP) found in previous works.10,21-23, 32 Our results are compatible with previous reports of enhanced affinity of MinD to liposomes containing CL, and the tendency of MinD to accumulate on curved membrane regions, and the suppression MinD’s ATPase activity.18,24-26 The insertion of the membrane targeting sequence into the membrane is also used by some GTPase proteins to modulate their functions.27-29

Figure 4. Interaction model for the Min protein wave. Schematic representation of the membrane-coated nanosensor lacking (a) or containing (b) cardiolipin CL. The wave forms by MinD dimers attaching to the membrane (a) or other MinD proteins (b) (left side). MinE proteins are recruited to this MinD layer and start to remove MinD by facilitating ATP hydrolysis, primarily at the edges of the MinD layer (right side). In these representations, MinD is shown in green, MinE in red, the lipid membrane in gray and CL in orange. c. Our model for the MinD interaction with lipid membranes lacking CL: The membrane targeting sequence’s (MTS) positively charged residues interact with the negatively charged membrane surface. d. In membranes containing CL, the lipid polar heads are packed more loosely and favor the insertion of the MTS. In this case, hydrophobic amino acids directly interact with the lipid acyl chains while the cationic residues interact with the polar head groups ‘from below’.

CONCLUSION Taken together, our results show the strong effect that CL and membrane perturbations have on the local dynamics of MinD attachment to lipid membranes. The novel use of NanoSPR with the systematic variation of the particle size allowed us to resolve the axial location of the dynamic protein interactions on the membrane with sub-nanometer axial resolution and showed the robustness of the MinDE system. We observed a strong influence of cardiolipin (CL) together with local membrane curvature on the Min oscillation mechanism, which is surprisingly robust even in the presence of a permanently bound MinD monolayer patch. How Min protein waves depend on lipid composition/local curvature and how Min waves affect the local arrangement of lipids remains an important topic for further studies. We envision that our new labelfree method could help to resolve the axial distances and reveal the molecular mechanism of many other protein-membrane systems as the sensing distances of the nanosensors can be tuned up to match most of biological molecular systems of interest. ASSOCIATED CONTENT



Supporting Information. TEM images, optical characterization of the nanoparticles, simulations, estimation of sensing distances and volume of the nanoparticles, microscope setup description and control experiments. This material is available free of charge via the Internet at http://pubs.acs.org. AUTHOR INFORMATION The authors declare no competing financial interests. Corresponding Authors *[email protected] *[email protected] Author Contributions The manuscript was written through contributions of all authors. All authors approved the final version of the manuscript. ACKNOWLEDGMENT This work was financially supported by the ERC grant 259640 (SingleSense).WY is funded by the Graduate School of Excellence Materials Science in Mainz (GSC 266). AK thanks the Graduate School of Quantitative Biosciences Munich (QBM) for funding and support. We thank Christina Lambertz, Jacob Halatek, Erwin Frei, Karl Wandner, Eva Wächtersbach and Henri G. Franquelim for fruitful discussions and technical assistance.

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Plasmonic Nanosensors Reveal a Height Dependence of MinDE

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