Time resolution in cryo-EM using a PDMS-based microfluidic chip assembly and its application to the study of HflX-mediated ribosome recycling

Sayan Bhattacharjee; Xiangsong Feng; Suvrajit Maji; Prikshat Dadhwal; Zhening Zhang; Zuben P Brown; Joachim Frank

doi:10.1016/j.cell.2023.12.027

. Author manuscript; available in PMC: 2025 Feb 1.

Published in final edited form as: Cell. 2024 Jan 19;187(3):782–796.e23. doi: 10.1016/j.cell.2023.12.027

Time resolution in cryo-EM using a PDMS-based microfluidic chip assembly and its application to the study of HflX-mediated ribosome recycling

Sayan Bhattacharjee ^1,^#, Xiangsong Feng ^1,^#,^*, Suvrajit Maji ¹, Prikshat Dadhwal ², Zhening Zhang ¹, Zuben P Brown ^1,³, Joachim Frank ^1,^2,^*,^†

PMCID: PMC10872292 NIHMSID: NIHMS1955310 PMID: 38244547

Abstract

The rapid kinetics of biological processes and associated short-lived conformational changes pose a significant challenge in attempts to structurally visualize biomolecules during a reaction in real time. Conventionally, on-pathway intermediates have been trapped using chemical modifications or reduced temperature, giving limited insights. Here we introduce a time-resolved cryo-EM method using a reusable PDMS-based microfluidic chip assembly with high reactant mixing efficiency. Coating of PDMS walls with ${S i O}_{2}$ virtually eliminates non-specific sample adsorption and ensures maintenance of the stoichiometry of the reaction, rendering it highly reproducible. In an operating range from 10 to 1000 ms, the device allows us to follow in vitro reactions of biological molecules at resolution levels in the range of 3 Å. By employing this method, we show the mechanism of progressive HlfX-mediated splitting of the 70S E. coli ribosome in the presence of the GTP, via capture of three high-resolution reaction intermediates within 140 ms.

IN BRIEF

A microfluidics based method for time-resolved mixing and freezing of cryo-EM samples, at a tens of milliseconds scale, enables capturing of on-pathway intermediates during HflX-mediated ribosome recycling, revealing a progressive splitting of the ribosome.

Graphical Abstract

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Introduction

To comprehend the fundamentals of any biological process, one requires insights into the underlying molecular mechanisms. It is often possible to study a reaction in vitro, outside the context of the cell. However, interactions among reactants and concurrent conformational changes of the molecules are too fast to be captured structurally using standard methods of biophysical imaging. In single-particle cryo-EM, the conventional pipetting-blotting method of sample deposition on the grid requires several seconds at least -- too long to capture reaction intermediates of molecular machines, which are in the range of tens or hundreds of milliseconds. In the past, some of such intermediates have been trapped by the use of non-hydrolysable analogs (such as GMP-PNP^1,2, antibiotics³, or cross-linking⁴), but the insights gained in this way are limited and often burdened with presumptions.

Time-resolved cryo-EM (TRCEM) opens a way for obtaining structural and kinetic information on reaction systems that are not in equilibrium but change over time until equilibrium is reached⁵. In TRCEM studies, the biological reaction is started by mixing reactants, then stopped at a selected time point by fast-freezing, and the so-trapped reaction intermediates are visualized by single-particle cryo-EM. By means of multiple experiments with different time points, TRCEM is able to capture the time course of a reaction, leading to a ‘movie’ of intermediates on the path to the state in equilibrium⁶.

Over the years, a variety of TRCEM methods have been developed^7–19 showing the potential for obtaining key insights into the mechanism of action of molecules and molecular machines on the time scale of tens to hundreds of milliseconds. These methods can be divided into two categories: spraying/mixing¹⁵ and mixing/spraying¹⁰. In the first category, a specialized sprayer¹⁵ or dispenser system⁷ is employed to deposit one reactant onto a grid already covered with another reactant. Both mixing and reacting occur on the grid immediately prior to vitrification. Questions have been raised over the uniformity of a diffusion-dependent reaction on the grid⁶. In addition, electron tomography has shown that molecules are frequently observed to congregate at the top and bottom of the ice layer²⁰, raising concerns about artifacts stemming from their extended exposure to the air-water interface in spraying/mixing or dispensing/mixing methods. In the second category, a microfluidic chip is used for mixing and reacting two reactants and for subsequent rapid spraying to deposit the reaction product onto the grid, followed immediately by plunging of the grid into the cryogen^{8–10,12–14,16}. In that case, mixing and reacting can be efficiently controlled, and the time during which the reaction product is exposed to the air-water interface is kept minimal.

There are still some key issues among the existing methods which need to be resolved. One problem is sample adsorption on the walls of the chip. Polymers such as PDMS, IP-S, IP-Q are now commonly used as a cost-effective material to fabricate microfluidic chips^12,13,18,19, but as a rule, the surfaces of these materials are intrinsically hydrophobic and adsorb a substantial amount of protein. In this case, the contact between the sample and the polymer microchannel can degrade the quality of the reaction, casting doubt over the accuracy of the kinetic information. This problem is avoided with silicon-based microfluidic chips^16,17 which are by nature hydrophilic, but they are quite impractical as it takes several weeks and on average hundreds of dollars to manufacture a chip of a specific design (i.e., in multiple copies; with production steps including the etching and dicing of a silicon wafer and bonding it with glass). Another problem is insufficient initiation of a reaction, which may result from ineffective mixing of fluids due to limited micromixer performance^12,14 in the laminar flow regime.

In the following we describe our TRCEM setup utilizing a PDMS-based microfluidics chip assembly that overcomes these problems, as it efficiently mixes the reactants for uniform initiation of a reaction, conducts a controlled reaction virtually unimpeded by protein adsorption, and sprays the reaction product in a uniform three-dimensional cone onto the EM grid. We have used this device successfully in several studies on translation. Here we present the study of HflX-mediated recycling in detail to demonstrate the efficacy of the TR device, and its capability to yield biologically significant information.

High frequency of lysogenization X (HflX) is a universally conserved protein for prokaryotes, a GTPase which acts as a ribosome-splitting factor in response to heat shock or antibiotics^2,21–23. E. coli HflX consists of four domains: N-terminal domain (NTD), GTP binding domain (GBD), C-terminal domain (CTD), and helical linker domain (HLD)^2,24. The cryo-EM structure of the HflX-50S complex stalled in the presence of GMP-PNP, a non-hydrolysable GTP analog, revealed that the HLD and NTD of HflX bind to the peptidyl-transferase center, presumably causing rupture of the intersubunit bridge B2a (h44:H69), thereby promoting the dissociation of the 70S ribosome². However, the molecular mechanism of these events and particularly the interaction between HflX and 70S have remained elusive. Using TRCEM, we were able to capture three short-lived intermediate states, at resolutions in the 3-Å range, by starting the reaction between HflX and the E. coli 70S ribosome in the presence of GTP and stopping it at 10, 25, 140 and 900 ms. Atomic models of these states allowed us to elucidate the mechanism of this process in great detail.

Results

A microfluidic chip assembly for TRCEM

The complete setup for TRCEM grid preparation, originally based on an apparatus built by Howard White²⁵, is depicted in Figures S1A and B. The heart of the TR apparatus is the microfluidic chip assembly mounted next to the plunger (Figure 1A), which are both accommodated in an environmental chamber that maintains the temperature and humidity at controllable levels. The plunger, which is pneumatically operated, holds the tweezers on which the EM grid is mounted for fast plunging into liquid ethane after passing the spray cone. In addition, the apparatus contains the pumping system for introducing the solutions into the micromixer and the nitrogen gas into the gas inlets of the microsprayer. Finally, it also houses the computer for controlling both the pumping system and the plunger.

We designed and successfully tested the modular TR chip assembly shown in Figure 1B, which is composed of three elements/modules: 1) a ${S i O}_{2}$ -coated, PDMS-based splitting-and-recombination (SAR) micromixer with 3D self-crossing channels (Figure 1C), which is able to mix the solutions with the effectiveness of > 90% at working flowrate of 6 μL/s (Figures 1E, S1H, S1I, and STAR Methods); 2) a microcapillary glass tubing serving as the microreactor for stable (i.e., unchanged under conditions of high pressure drop) reaction time control (Figure S1J and STAR Methods); 3) a PDMS-based microsprayer with inner capillary tubing for spraying out the reaction product under the action of pressurized nitrogen gas (Figure 1F, STAR Methods, and Video S1).

To prevent adsorption of molecules, plasma-enhanced chemical vapor deposition (PECVD) is used to coat the inside walls of the PDMS micromixer channels with a thin ${S i O}_{2}$ layer. We tested the sample adsorption with the E. coli 70S ribosome to compare chips without coating to those with DDM or ${S i O}_{2}$ coating. The sample concentration in buffer is measured before and after passing the devices with different types of coatings by our Nanodrop UV-Vis Spectrophotometer (STAR Methods). In this experiment, 94% of the initial concentration was retained using the ${S i O}_{2}$ -coated chip (Figure 1H and Table S2), while only 54% and 60% were retained after the sample was passed through the chip assembly without coating or with DDM coating, respectively. These findings demonstrate that the ${S i O}_{2}$ coating can effectively mitigate the sample adsorption for ribosomes. After one month, the ${S i O}_{2}$ -coated chip assembly was tested again with 70S ribosome and HflX protein, and 92% of the 70S and 93% of HflX were shown to be still retained, respectively (Figure 1I). These results demonstrate that the hydrophilicity of the internal surface is virtually undiminished after a substantial period of time.

Thus, it is apparent that the solutions introduced from the glass-capillary liquid inlets will pass through the entire microfluidic device ( ${S i O}_{2}$ -coated micromixer, glass-capillary microreactor and glass-capillary inner tubing of the microsprayer) without contact with any hydrophobic surface, a fact of high importance for preserving the stoichiometry of a reaction and guaranteeing its reproducibility.

Based on these initial test results, we fabricated a set of microfluidic chips (Figure 1G) to conduct a set of biological experiments. The relevant materials and parameters for the fabrication of the chip assemblies are listed in Table S1. An estimation of reaction times achieved using this TRCEM method in the application to HflX-mediated ribosome recycling is given in STAR Methods. Four microfluidic chip assemblies were used, with reaction times estimated to be 10, 25, 140, and 900 ms, respectively.

Exposure-targeting strategy in data collection for droplets-based cryo-grids

For grids obtained by the conventional blotting method, data collection is usually done automatically after the template is set up for targeting both the holes and exposures. But for grids prepared by the mixing-spraying method, it is not easy to use automation, since every collectible square possesses droplets of different sizes and thicknesses²⁶. Hence time-consuming manual exposure targeting is still required. However, some observations on typical particle distributions in the HflX experiment, to be detailed below, and other experiments have led us to develop an effective strategy for exposure targeting in data collection on droplet-based grids.

There are two types of situations: one is where the droplet has no contact with the grid bar (marked red in Figure S3A); and the other where it does have contact with the grid bar (marked green in Figure S3A). In the former, the ice is observed to be thick and unsuitable for data collection, while in the latter, there is always some part of the region near the grid bar with an ice thickness suitable for data collection. All our exposure targets are therefore focused on the second type of droplets, as detailed below.

In the beginning, as shown in Figure 2A, we tried to collect data on as many holes as possible for droplets of the second category, i.e., touching or partially covering the grid bar, and found that typically there are four regions with different behaviors, following a trend: (i) very close to the grid bar, as in the area marked blue, the ice is not vitrified very well but particles are still visible; (ii) in the area marked cyan, particles are clearly visible; (iii) further on, in the area marked yellow, the number of the particles has significantly decreased; until, (iv) in the area marked red, there are almost no particles left (Figure 2A). We speculate that when the droplet is spreading, the particles tend to flow from the thin to the thick area (that is, from the yellow to blue regions), and that the particles in the thin film of solution are more likely attracted to the air-water interface or the carbon film. In the present instance of data collection, only 170 out of 580 micrographs, or 29%, were left for data processing.

In line with these observations, we developed the exposure-targeting strategy shown in Figure 2B: we collect only along two or three lines of holes which are near and parallel to the grid bar, in the areas of type (i), (ii) and (iii). As a result, in our example, we obtained 3433 good micrographs out of a 4458 total, which means about 77% could be used in this case for data processing. We therefore adopted this strategy for all our data collection on grids prepared by TRCEM.

Time-resolved experiments on HflX-mediated ribosome recycling from 10 to 900 ms

HflX acts on the 70S ribosome in a nucleotide-dependent way, and light scattering analysis revealed that the rate of ribosome splitting by HflX-GTP (0.002 s⁻¹) is very similar to the rate of ribosome dissociation by the combined action of RRF and EF-G-GTP (0.005 s⁻¹)^22,27. The fraction of ribosomes split into subunits at room temperature within a reaction time of 140 ms is close to 50%, according to our earlier TRCEM experiment on E. coli ribosome recycling in the presence of RRF, EF-G, and GTP⁹. In view of these findings, we anchored our TRCEM study at a 140 ms reaction time point and added two shorter time points (10 ms and 25 ms) and one longer one (900 ms) toward the reaction’s completion. We mixed 70S ribosomes with the HflX-GTP complex in our mixing-spraying TRCEM apparatus (Figures S1A and B) using different microfluidic chips of the PDMS-based design (Figure 1G and STAR Methods). As in our previous TRCEM studies^9,10, 3D classification was performed on the entire, pooled dataset across all four time points. The 3D classification produced seven distinct classes, which we characterized by examining the corresponding reconstructed density maps (note: “rotated” and “nonrotated” refers in the following to the presence or absence of intersubunit rotation²⁸): (1) rotated 70S without HflX (r70S_noHflX); (2) non-rotated 70S without HflX (nr70S_noHflX); (3) 70S-like intermediate-I with HflX (i70S_HflX-I); (4) 70S like-intermediate-II with HflX (i70S_HflX-II); (5) 70S-like intermediate-III with HflX (i70S_HflX-III); (6) 50S with HflX (50S_HflX); and (7) 30S (Figure S4D and STAR Methods).

The splitting reaction kinetics of the 70S ribosome, as evaluated by counting the numbers of particles obtained upon 3D classifications from 10 ms to 900 ms, is found to follow a similar, roughly exponential behavior as reported from dissociation kinetics measured by light scattering² (Figure 3M). Furthermore, we noticed a rapid increase in the number of free 30S subunit particles from 140 ms to 900 ms, which leads us to conclude that the final separation of the subunits commences not earlier than with state i70S_HflX-III (Figure 3M).

Figure 3. — (A) Superimposition of reconstructions to show the opening of the 30S subunit from apo-70S (yellow) to i70S_HflX-I (red) to accommodate HflX. The green line represents the initial axis of 30S rotation, Axis I. (B) and (C), Reconstructions of second and third intermediates overlapped with first intermediate, showing the stepwise splitting of the 70S by HflX by rotation of the 30S subunit around Axis II (green line). The corresponding rotation angles and direction of 30S rotation are shown in cartoon book representations. (D), Reconstruction of the 50S-HflX complex after the departure of the 30S subunit, overlapped with the first 70S intermediate. In (A) through (D), all reconstructions are aligned on the 50S subunit. (E) to (H) are the high-resolution densities of control 70S at 900 ms and three intermediates obtained within 140 ms, showing the stepwise rotation of 30S subunit during recycling with respect to the 50S subunit (gray). (I) and (J) are the zoomed views of Coulomb densities in yellow for apo-70S and red for i70S_HflX-I, respectively, and corresponding atomic models (gray) showing the rearrangement of the protein uL2 of the 50S subunit and bS6 of the 30S subunit to accommodate HflX. (K) and (L), Coulomb densities, and corresponding ribbon models of helix H69 from apo-70S (yellow), and i70S_HflX-I (red), respectively, showing the very first movement of H69. HflX is shown in magenta. (M) Kinetics of the splitting reaction in terms of the number of particles per class as a function of time, obtained by 3D classification. The connecting lines between the data points are added for clarity to show the increases and decreases of subpopulation counts.

Intermediate states of HflX-mediated recycling and their interpretation

The three classes of HflX-containing intermediates and class 50S_HflX -- four of the seven 3D classes we found -- were selected for additional structural analysis (Figure S4D and STAR Methods). Furthermore, focused 3D classification and subsequent reconstruction of HflX-binding regions from each of the resulting class reconstructions yielded high-resolution density maps for four states of HflX: (1) HflX-I, (2) HflX-II, (3) HflX-III, and (4) HflX-IV (Figure S4D). Refinement on the three i70S_HflX class reconstructions yielded high-resolution on-pathway intermediates i70S_HflX-I, i70S_HflX-II, and i70S_HflX-III (Figures 3A–H), and their resolutions are indicated in Figure S5 and Table S3. The kinetics of the reaction can be followed from the histogram of particle counts in the respective classes (Figure 3M). The intermediates i70S_HflX-I, i70S_HflX-II, and i70S_HflX-III are each dominant in the 10 ms, 25 ms, and 140 ms time points, respectively, but are always intermixed with the other intermediates, as well as with apo-70S and the 50S-HflX end product.

In all three intermediates, the CTD of HflX is found anchored to uL11 of the 50S subunit at the bL12 stalk base. Overall, a comparison of the intermediates shows a gradual clamshell-like opening of the 70S ribosome (see Video S2).

Structurally, the intermediates are distinguished by (i) the degree of the clamshell-like opening, (ii) the position of helix H69 (in two steps, from i70S_HflX-I to -III), (iii) the position of helix H71 (from i70S_HflX-I to -II), and (iv) the position of HflX with respect to the 50S subunit (from i70S_HflX-I to -II, and reversed from -II to -III). In the final state observed, after the departure of the 30S subunit, HflX remains bound to the 50S subunit.

Comparison of the atomic models obtained for these intermediates with one another and with the apo-70S revealed that the opening and splitting of the 70S ribosome occurs in the following steps:

First, the ribosome opens slightly to accommodate the initial binding of HflX in i70S_HflX-I (Figures 3A, 3E–F). Using the tool of computational analysis previously developed²⁹ we find that in this first intermediate, the 30S subunit has rotated by 5.9° around an axis (Axis I) that passes through the intersubunit bridges B1b, B2a, B3, and B4 (Figures 6A, D, G, and 6J–K), and this rotation has moved protein bS6 of 30S into close vicinity to protein uL2 of the 50S subunit (Figures 3I–J). Apparently, the insertion of HflX along with the prying apart of the 70S ribosome and the rotation of the 30S subunit is driven by the increase in backbone entropy of uL2 in i70S_HflX-I compared to apo-70S since we find indications of disorder: the density of uL2 is not resolved well in i70S_HflX-I (Figure 3J) compared to all its other manifestations in apo-70S, i70S_HflX-II and i70S_HflX-III (Figures 3I–J). Comparison of the 50S subunit in i70S_HflX-I and apo-70S shows that H69 has shifted by 6.7 Å as a result of a steric clash between HflX and H69, which was observed in the attempt to fit the HflX model into apo-70S. This implies HflX-induced stabilization of certain 70S conformations that facilitate the splitting (Figures 3K–L). In i70S_HflX-I HflX is blurred, indicating motion-induced heterogeneity of the population in that class (Figure S4D).

Figure 6. — (A), (B), and (C), rotation of 30S subunit from Apo-70S (yellow) to i70S_HflX-I (red), i70S_HflX-I (red) to i70S_HflX-II (green), and i70S_HflX-I (red) to i70S_HflX-III (blue), respectively. **(D)**, **(E)**, and **(F),** characterization of the 30S subunit rotation, with the 50S subunit (cyan) fixed in space. The models show the rotated state of the 30S subunit in each case. For clarity, 30S subunits are represented with only their principal axes of inertia. Rotation axes (Axis I, Axis II) are shown as green arrows indicating the direction (right-hand thumb rule) of the rotation (black curled arrows). **(D)** Rotation by 5.9° of 30S subunit around Axis I from Apo-70S (yellow) to i70S_HflX-I (red). (E) and (F), Rotations by 7.9° and 16.1°, respectively, of 30S subunit around Axis II. **(G)**, **(H)**, and **(I)**, same representation as **(D)**, **(E)**, and **(F)** omitting the 30S subunit to show the axes clearly. (J) and (K), Intersubunit bridges through which Axes I and II pass in the 50S and 30S subunit, respectively. **(L)** Formulation of rigid body motion, along with location of the rotation axis. Initial and transformed positions are respectively denoted by A (position vector ${\vec{x}}_{0}$ ) and B (position vector ${\vec{x}}_{1}$ ). The shift from A to B is given by translation vector $\vec{t}$ . Points with dotted circles are on the plane perpendicular to the rotation axis $\hat{l}$ . Points $\vec{A_{p}}$ and $\vec{B_{p}}$ are projections of points A and B, respectively. ${\vec{t}}_{∥}$ and ${\vec{t}}_{⊥}$ are respectively the parallel and perpendicular components of the translation vector $\vec{t}$ . Axis $\hat{l}$ and angle $θ$ describes the rotation of the rigid body from point A to B. The rotation axis $\hat{l}$ passes through the point given by the position vector ${\vec{C}}_{⊥}$ . The solution for the position vector ${\vec{C}}_{⊥}$ is obtained by using the remaining vectors, as indicated in the derivation in STAR Methods “Determining the position vector of the unique point through which the rotation axis passes”.

Going from this first intermediate to i70S_HflX-II and i70S_HflX-III we observe stepwise rotations, by 7.9° and 8.2°, respectively, of the 30S subunit around a new axis (Axis II) passing through intersubunit bridges B3 and B7a, which are both located along helix h44 (Figures 3B–C, 3F–H, and 6B–C, 6E–F, 6H–I, and 6J–K). In the first step of rotation around this new axis, protein bS6 moves away from protein uL2 (Figures 3B, 3F–G, and 6B, 6E, 6H, and 6J–K). This movement is made possible by a 6.5-Å pull of C1965 of H71 as a result of HflX moving from its previous position on i70S_HflX-I to a new position on i70S_HflX-II and a subsequent shift of the loop-helix motif (G74-V100) associated with the NTD of HflX (Figures 4D–G). As a consequence, bridge B3 (h44:H71), as well as bridges B7b and B7bR, have become destabilized. While the conformation of the 30S subunit remains virtually the same from apo-70S to the first intermediate, the change from the first to second intermediate is accompanied by a rotation of the 30S subunit head by 2.1° around another axis, Axis III (Figures S8A–C).

Figure 4. — (A)and (B) Zoomed view of HflX and uS12 interactions with the 30S subunit in i70SHflX-I and i70SHflX-III states, respectively. Due to the stepwise separation of the 30S from the 50S subunit during splitting, there occurs a steric clash (red star) at 140 ms due to the subsequent shift of the whole uS12, which is not present at earlier states like10 ms, and this clash is the cause for the final separation of the 30S from the 50S subunit. (C) The same clash at 140 ms from i70SHflX-III is shown in the density map with a fitted model. (D) Pulling of H71 by the NTD of HflX, causing the disruption of intersubunit bridge B3 between H71 and h44. (E) Zoomed view showing the interacting residues of H71 and HflX. (F) shift of HflX during pulling of H71. (G) The same interaction is shown in the density map with a fitted model.

In the second step of the 30S subunit rotation around Axis II, from i70S_HflX-II to i70S_HflX-III, protein bS6 has continued to move away from protein uL2 (Figure 3C, 3F–H, and 6C, 6F, 6I, and 6J–K), and HflX has shifted back to its original position on the 70S ribosome in i70S_HflX-I. Bridges B7b and B7bR are now entirely disrupted, allowing the flexible loop (E323-G349) of HflX’s GTD to readily access the 30S subunit protein uS12, thus positioned to jettison the 30S subunit from the 70S ribosome (Figure 4A–C).

In the final step, the reconstruction of the stable 50S-HflX complex, at 3.6-Å resolution (Figures 3D, and S7A), no longer shows any trace of density from the 30S subunit (Figures S7A, and D). This class mainly contains particles from 900 ms (Figure 3M). The map agrees quite well with the map of HflX-50S-GNP-PNP² (Figures S7A–C).

For all three intermediates we computed local resolution estimates (Figures S6A–I and STAR Methods) in order to obtain insights into their dynamic behaviors. In i70S_HflX-II, the 50S subunit displays a drop in local resolution, apparently as a result of HflX-mediated conformational changes. In i70S_HflX-III, the 30S subunit head also exhibits a decrease in local resolution, probably as a consequence of the disruption of several intersubunit bridges.

We found the local resolution map helpful in answering the question whether the rotation of the 30S subunit during the clamshell-like opening of the 70S subunit is continuous or truly stepwise. As the density maps of the three intermediates correspond to the three classes obtained by maximum likelihood classification by RELION, some amount of spread in state space can be expected for each class. For significant rotation of the 30S within its class, there should be a progressive deterioration of local resolution for the subunit body as we go with increasing radius in the normal direction from the tilt axis (I or II) to the periphery. Instead, we find that the resolution remains solid at ~3Å, except for minor changes at the very periphery. (As noted above, the 30S subunit head undergoes a separate movement and should not be considered here). From this analysis we conclude that the rotation of the 30S subunit during 70S splitting is stepwise and not continuous.

Dynamics of HflX and GTP hydrolysis-independent splitting

A comparison of the atomic models built for the three intermediate states reveals that HflX changes its position on the ribosome and undergoes major conformational changes, specifically in its CTD, HLD, and NTD. The domain movements of CTD and HLD match quite well with the dynamics of apo-HflX predicted from 1000 ns of molecular dynamics simulations (Figures S8D–F and STAR Methods). Interestingly, the loop-helix motif (G74-V100) of NTD makes stable contact with H71 of the 50S subunit in i70S_HflX-II (Figures 4D–F).

We built the atomic model of GTP into the corresponding densities of the nucleotide sites in HflX-III and HflX-IV, considering the fact that 70S splitting by HflX has been reported to be independent of GTP hydrolysis, and that HflX can split the 70S in the presence of non-hydrolysable GTP analogues². At 25 ms, with the exception of their NTDs, the densities of HflX and associated nucleotides in states HflX-I and HflX-II are not resolved as well as they are for the other two states, indicating mobility (Figure S4D). If apo-HflX can split the 70S ribosome, albeit at a slower rate, the ultimate separation of the 30S from the 50S subunit of i70S_HflX-III would result from the steric clash between HflX and uS12 of the 30S subunit in the transition from i70S_HflX-II to i70S_HflX-III.

Time-dependent rupturing of intersubunit bridges

As the direct observation of the state of bridges from the cryo-EM map is not conclusive due to resolution limitations, we proceeded with a geometric calculation to estimate the sequence in which intersubunit bridges are ruptured. With the axes and angles of the 30S subunit rotation known, as well as the locations of all bridges relative to the axes, we were able to determine the distances between constituent residues of all intersubunit bridges. From these distances and known ranges of chemical bond lengths we were able to estimate at which time points the intersubunit bridges are likely disrupted and broken (Figure 5D). According to these calculations, bridges B1a, B1b, B2a, and B2b are already disrupted at 10 ms. Bridges B5, B6, B7b, and B7bR are disrupted between 10 and 25 ms. All these bridges are found to be broken within 140 ms. Finally, bridges B3 and B7a, which form the hinges of Axis II, give way at some time point between 140 ms and 900 ms. Bridge B4 (H34:uS15) which lies off the Axis II presents an interesting case as it behaves like a spring: its 50S subunit constituent H34 is initially compressed in the step from apo-70S to i70S_HflX-I, as HflX is accommodated within the first 10 ms, but in the next two steps (10 ms to 25 ms to 140 ms) it is extended (Figure 5C). This bridge finally breaks along with B3 and B7a after 140 ms and, in 50S_HflX, helix H34 has returned to its original position as in apo-70S.

Figure 5. — (A) Refined density map of i70S_HflX-III (in mesh) with an atomic model fitted in with the zoomed view of i70S_HflX-III with the fitted model of GTP. (B) Refined density map of 50S_HflX (in mesh) with atomic model fitted in, along with the zoomed view of 50S_HflX with the fitted model of GTP. (C) Superimposition of atomic models of apo-70S and three intermediates with the zoomed view of H34 showing its spring-like behavior. Corresponding colors are indicated. (D) Tabulation of molecular events during the 70S splitting by HflX.

Discussion

Here, we present a method for preparing time-resolved cryo-EM grids to capture intermediates on the ~10- to 1,000-ms timescale. Different in design from those by Lu et al.^16,17, Mäeotset al.¹³, and Kontziampasis et al.¹⁴, the microfluidic chip assembly comprises three replaceable modules: (1) a PDMS-based internally ${S i O}_{2}$ -coated micromixer of the splitting-and-recombination (SAR) type, for efficiently mixing two samples without encountering significant problems from protein adsorption; (2) a glass capillary microreactor for defining the reaction time, and (3) a PDMS-based microsprayer for depositing the reaction product onto the EM-grid. The sample is subsequently vitrified by fast plunging of the grid into the cryogen so that the TR cryo-grid can be well prepared.

As we observed, high-quality images can be collected only in sub-regions of droplets that touch the grid bar. For efficiency, larger droplets of more uniform ice thickness are needed, and in the future we will use some specialized EM-grids, such as self-wicking or nanowire grids³⁰, ultraflat graphene EM-grids³¹, or some types of grids with specialized layout of grid bars³², to facilitate the spreading of droplets on the grid, and thus enlarge the collectible area.

In recent years, several deep-learning based programs^33–35 have been developed to automate the data collection, which promise to provide a solution for collecting data from droplet-sprayed EM-grids. We believe, some programs, such as Ptolemy³³ will be very helpful in effective detection and classification of squares and hole, especially if they can be upgraded to a version that can dynamically update their models with high adaptability during the data collection on droplet-sprayed EM-grid.

In our application to the study of HflX-mediated ribosome recycling, a bacterial defense response to stress, we have demonstrated that our method is able to capture, on-the-fly, high-resolution structures of intermediates that represent snapshots of an unfolding complex molecular mechanism. Based on our cumulative observations from the examination of three short-lived reaction intermediates, we propose that the initial binding of HflX within 10 ms is followed by a stepwise clamshell-like opening of the ribosome around an axis that closely aligns with helix 44 of the 30S subunit, and that the rupture of the last three remaining intersubunit bridges, B3, B4 and B7a, occurs after 140 ms. Following accommodation of HflX, we observe an opening of the intersubunit space in i70S_HflX-I compared to apo-70S, which is produced by a 5.9° tilt of the 30S ribosome around Axis I, quite similar to the small subunit “rolling” observed in both prokaryotes^36,37 and eukaryotes³⁸. Additionally, when comparing i70S_HflX-II with i70S_HflX-I, we see a 2.1° rotation of the 30S subunit head around axis III (Figures S8A–C), a state which resembles the conformation adopted by the 30S subunit of a 70S ribosome stalled at the UAA stop codon and loaded with P- and E-site tRNAs and RF2³⁹. While these motions are known from the literature of the elongation cycle, the clamshell-like opening of the 70S ribosome in the course of HflX-mediated recycling is distinct.

Further applications of time-resolved cryo-EM in the study of functional dynamics

Our study will spur interest in the community for extending these studies to recycling in the 80S ribosome by protein factors such as ABCE1 to structurally reveal an evolutionarily conserved mechanism. We believe, moreover, that the quantitative description of our results on a dynamic process – employing tensor analysis to determine the tilt axis and rotation of subunits, and quantifying the timing of intersubunit breakage – as well as the application of this microfluidic device will open a new direction in the characterization of molecular events by cryo-EM and will stimulate interest and draw considerable attention among a wide audience of structural biologists, microbiologists, and pharmacologists. Ultimately, it may help in the design of a class of broad-spectrum antibiotics that are able to overcome antibiotic resistance.

Limitations of the Study

1. Our method of TRCEM has been proven powerful for capturing structural intermediates for HflX-mediated ribosome recycling and other processes of translation, but there are many other interesting biochemical processes awaiting visualization by this method. Those involving motions of large domains of macromolecules are excellent candidates. Signaling, activation and gating mechanisms of receptors and transporters^40–42 come to mind, as well, but in many cases the characteristic times of motions are much shorter than 10 ms, the minimum reached by our method of mixing-spraying-plunging. In this time domain, entirely different technologies have to be considered^15,19,43,44. 2. As we pointed out before¹⁰, TRCEM, in addition to furnishing the high-resolution structures of reaction intermediates, has at least in principle the capacity to give kinetic information, as well, since the numbers of particles in each structural class are known. However, this information is currently not very accurate since it depends on the vagaries of particle picking and classification strategies. Investment in a search for quantitative, reproducible strategies would therefore be of enormous value. 3. Data collection on droplet-covered TRCEM grids remains quite time-consuming even with the proposed strategy to target certain regions close to the grid bar, since it still relies on visual/manual selection. There is clearly a need for sophisticated automatic targeting tools on grids prepared by spraying with sample droplets. 4. Compared with conventional blotting method, the TRCEM method requires a substantially bigger volume of sample (~10 μL versus 3 μL) for each grid, which is the minimum quantity of fluid required to reside in the whole microfluidic system for ensuring a stabilized spray. However, much of the spray is wasted in the present setup with a single EM grid as target, and an obvious next step is the development of a plunger with multiple pairs of tweezers or a specially designed tweezer-manifold to hold several grids at once. 5. Our TRCEM analysis about the interaction between HflX and 70S ribosome leaves open the question of how HflX recognizes the stalled state of the ribosome. Here our observation of 30S subunit head rotation from apo-70S to i70S_HflX-I may offer a clue. Puromycin-treated polysomes, having deacylated tRNA in the P site, display greatly enhanced HflX splitting activity, and this state was proposed as the natural substrate for HflX². In this state, the ribosome is known to undergo spontaneous intersubunit rotation⁴⁵, which goes hand in hand with 30S subunit head ‘swivel’ rotation⁴⁶. This would suggest that HflX initially binds to the ribosome in its rotated conformation and forces it into the unrotated conformation observed in i70S_HflX-I, with residual 30S subunit head rotation still retained. But to answer these questions more extensive studies with similar tools are required. 6. A related question is to what extent our results, obtained with apo-70S lacking tRNA instead with the termination complex containing deacylated tRNA at the P site, is relevant for describing the action of HflX in the cell. If we examine the unrotated conformation of a ribosome containing P-site tRNA⁴⁷ [pdb: 4V5D] and introduce HflX in the position we observe after its binding to apo-70S, we observe a hard clash of 2Å with HLD (G139-T162) and a clash with HflX NTD loop-helix motif (G74-V100) of 9 Å. However, our analysis shows that the hard clash is avoided with a slightly rotated form of this complex reported in the literature⁴⁸ [pdb: 4V9D] with intersubunit 30S body rotation of 0.5° and head swivel of 2.1°. This conformation of the 70S ribosome happens to be virtually identical with the one observed in our intermediate state i70S_HflX-II (Figures S8G–J).

STAR★Methods

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Joachim Frank (jf2192@cumc.columbia.edu).

Materials availability

All unique resources generated in this study are available from the lead contact upon reasonable request with a completed Materials Transfer Agreement.

Data and code availability

The EM maps and corresponding atomic models are deposited on EMDB and PDB and will be publicly available as of the date of publication. Accession numbers are listed in the key resources table.
This paper does not report original code.
Any additional information required to reanalyze the data reported in this work paper is available from the lead contact upon request.

KEY RESOURCES TABLE.

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Bacterial and virus strains
E. coli BL21 Star^™(DE3)pLysS cells	Invitrogen	Cat# C602003
Chemicals, peptides, and recombinant proteins
Tris Base	Fisher Scientific	Cat# BP152–1
Magnesium acetate	Sigma-Aldrich	Cat# M5661
Ammonium chloride	Sigma-Aldrich	Cat# 09718
2-Mercaptoethanol	Sigma-Aldrich	Cat# M6250
Isopropyl β-D-1 -thiogalactopyranoside	Sigma-Aldrich	Cat# I5502
Sodium hydroxide	Sigma-Aldrich	Cat# S5881
Imidazole	Sigma-Aldrich	Cat# 288324
Sodium chloride	Thermo Scientific	Cat# 447302500
Sucrose	Sigma-Aldrich	Cat# S0389
GTP	Invitrogen	Cat# 18332015
Photoresist (SU-8 2075)	MicroChem	Y111074
Polydimethylsiloxane (PDMS)	Dow Corning	DCC000001477
n-Dodecyl β-D-maltoside (DDM)	Sigma-Aldrich	Cat# 69227–93-6
Dimethylsiloxane-(60–70% ethylene oxide) block copolymer, 20 cSt	Gelest	CAS# 27306–78-1
Deposited data
control apo-70S (without salt-wash) at 900ms	This paper	EMD-29681; PDB: 8G2U
i70SHflX-I	This paper	EMD-29688; PDB: 8G34
i70SHflX-II	This paper	EMD-29687; PDB: 8G31
i70SHflX-III	This paper	EMD-29689; PDB: 8G38
consensus i70SHflX-I, 30S focused	This paper	EMD-29833
i70SHflX-I, 50S focused and 30S subtracted	This paper	EMD-29834
consensus i70SHflX-II, 30S focused	This paper	EMD-29724
i70SHflX-II, 50S focused and 30S subtracted	This paper	EMD-29844
consensus i70SHflX-III, 30S focused	This paper	EMD-29723
i70SHflX-III, 50S focused and 30S subtracted	This paper	EMD-29842
Recombinant DNA
pET28a-HflX	This paper	Gift (from Peking University, China)
Software and algorithms
DomainMotionInertiaTensor	Maji, S. et al. ²⁹	https://github.com/suvraiitm/DomainMotionInertiaTensor
FreeCAD	Falck, et al. ⁵⁶	https://www.freecad.ora/
Gmsh	Geuzaine C. and Remacle JF. ⁵⁷	https://gmsh.info/
OpenFoam	Niels G. J. et al. ⁵⁸	https://openfoam.org/
MotionCor2	Zheng et al. ⁷¹	httos://emcore.ucsf.edu/ucsf-software
RELION	Scheres, S.H. ⁷²	https://www3.mrc-lmb.cam.ac.uk/relion//index.nhn/Main_Page
CryoSPARC	Punjani, A., et al. ⁷³	https://crvosnarc.com/
CTFFIND4	Rohou and Grigorieff ⁷⁴	https://ariaoriefflab.umassmed.edu/ctffind4
Topaz	Bepler, T. et al. ⁷⁵	http://cb.csail.mit.edu/cb/tonaz/
DeepEMhancer	Sanchez-Garcia, R. et al. ⁷⁶	https://aithub.com/rsanchezaarc/deepEMhancer
ResMap	Kucukelbir et al. ⁷⁸	http://resman.sourceforae.net/
PHENIX	Liebschner et al. ⁸³	https://www.phenix-online.org/
COOT	Emsley, P. and Cowtan, K. ⁸⁴	https://www2.mrc-lmb.cam.ac.uk/personal/pemslev/coot/
UCSF ChimeraX	Goddard et al. ⁸⁵	https://www.rbvi.ucsf.edu/chimerax/
Other
Ni Sepharose	GE Healthcare	Cat# 04003272-EE
Quantifoil R 0.6/1 holey carbon copper grid	TED PELLA, INC.	Cat# 657–300-CU
Amicon^® Ultra-4 Centrifugal Filter Unit	MilliporeSigma	Cat# UFC8010
Time-resolved apparatus	Dr. Howard White, Eastern Virginia Medical School	N/A
Capillary tubing	Polymicro Technologies	https://www.molex.com/en-us/products/part-detail/1068150018

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EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

Bacterial cell culture

Cells were incubated at 37°C and 16 °C as per requirements.

METHOD DETAILS

Protein purification

The pET28a-hflX plasmid (gift from Professor Ning Gao, Peking University, China) was transformed into E. coli BL21 Star^™ (DE3)pLysS cells (Invitrogen) for HflX expression. Cells were incubated at 37°C until OD600 reached 0.6 and then induced with 0.6 mM isopropyl-β-D-thiogalactopyranoside (IPTG) (Sigma-Aldrich) for 12 hr at 16 °C. Cells were harvested and lysed in buffer 20 mM Tris-HCl, pH 7.6, 500 mM NaCl, 10 mM imidazole, 5 mM β-mercaptoethanol (βME), and 1 mM PMSF by ultrasonication. After centrifugation at 12,000 r.p.m. of cell lysates, supernatants were loaded onto a HisTrap HP Ni-NTA column (GE Healthcare) and eluted with buffer 20 mM Tris-HCl, pH 8.0, 500 mM NaCl, and 250 mM imidazole. HflX-containing fractions were pooled and concentrated using Amicon^™ Ultra-4 Centrifugal Filter Units (MWCO 10kDa, MilliporeSigma^™). TEV enzyme digestion was done to remove the histidine tag. Untagged HflX was further purified, and buffer exchanged using a gel-filtration column of Superdex 75 10/300GL (GE Healthcare) pre-equilibrated with buffer 20 mM Tris-HCl, pH 7.6, 500 mM NaCl, and 5 mM βME.

Isolation and purification of E. coli 70S ribosomes

Log-phase E. coli MRE600 cells were harvested and washed with 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 100 mM NH₄Cl, and 5 mM βME buffer. Re-suspended cells in the same buffer were lysed with ultrasonication and centrifuged at 12,000 r.p.m. to remove cell debris. The supernatant containing crude ribosome was placed on the top of a 30% sucrose cushion (in 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 30 mM NH₄Cl, 5 mM βME) and pelleted down using Beckman 50.2 Ti rotor at 100,000 × g for 16 hr at 4°C. Clear ribosome pellet was re-suspended in 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 30 mM NH₄Cl, and 5 mM βME and homogenized for 1 hr in presence of 1 M NH₄Cl, after which the ribosomal preparation was centrifuged multiple times at 16,000 g and at 4 °C for 20 min to remove all the non-specific proteins associated with ribosome. The supernatant containing ribosome was placed on the top of a 30% sucrose cushion (in 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 30 mM NH₄Cl, 5 mM βME) and pelleted down using Beckman 50.2 Ti rotor at 100,000 × g for 16 hr at 4°C. The pellet was dissolved in 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 30 mM NH₄Cl, and 5 mM βME and loaded on top of a 10%–40% linear sucrose gradient in 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 30 mM NH₄Cl, 5 mM βME buffer and centrifuged using Beckman swing-out SW 28 Ti rotor 28,000 r.p.m., 4 °C, 1 hr 45 min. Fractions were collected using Gilson FC203B automated fraction collector. The 70S containing fractions were collected and sucrose was removed by exchanging with 20 mM Tris-HCl, pH 7.5, 10 mM Mg(OAc)₂, 30 mM NH₄Cl, and 5 mM βME buffer and concentrated to the desired amount using Amicon^™ Ultra-4 Centrifugal Filter Units (MWCO 100 kDa, MilliporeSigma^™). See Figure S4A.

Splitting assay

1 μM 70S subunits were mixed with 1 μM HflX and 1mM GTP in 20 mM Tris-HCl, pH 7.5, 100 mM NH4Cl, 10 mM Mg(OAc)2, and 4 mM βME mixing buffer, and the reaction mixture was incubated at room temperature for 45 min. The mixtures were loaded onto a 10–40% (w/v) sucrose cushion (prepared in mixing buffer) and centrifuged at 35,000 r.p.m. for 1 hr 15 min at 4 °C with an MLA-130 rotor (Beckman Coulter, Brea, California, USA). As a control, identical procedures were performed with the 70S and the same volume of mixing buffer; see Figure S4B.

Co-sedimentation assay

1 μM 70S subunits were mixed with 1 μM HflX and 1mM GTP in 20 mM Tris-HCl, pH 7.5, 100 mM NH4Cl, 10 mM Mg(OAc)2, and 4 mM βME mixing buffer, and the reaction mixtures were incubated at room temperature for 5 min. The mixtures were loaded onto a 30% (w/v) sucrose cushion (prepared in mixing buffer) and centrifuged at 85,000 r.p.m. for 1 hr at 4 °C with an MLA-130 rotor (Beckman Coulter). As a control, identical procedures were performed with 70S and same volume of mixing buffer. Supernatants were carefully removed, and pellets were resuspended in mixing buffer and analyzed by 12% SDS-PAGE. See Figure S4C.

The apparatus for Time-resolved (TR) cryo-EM sample preparation

The apparatus for accommodating and controlling the microfluidic chip (Figures S1A and B) was built by Dr. Howard White^25,49, but some features were added as follows: an environmental chamber for maintaining the temperature and humidity²⁶, and a microfluidic chip assembly for depositing time-resolved reaction product on the EM-grid. In addition, we now use two separate gas pumping systems to control the plunger and microsprayer, thereby producing more stable plunging motion and solution atomization, respectively, compared to the original apparatus with a single gas pumping system.

The chip is mounted in the environmental chamber, with the nozzle of the microsprayer facing the cryo-EM grid. Two solutions of interest are fed into the micromixer of the microfluidic chip through 1/16-inch polyetheretherketone (PEEK) capillary tubing (125 μm inner diameter) and 2.0-μm PEEK microfilters, controlled by a computer-assisted liquid-pumping and grid-plunging apparatus designed by H. White and co-workers^25,49. Each EM grid to be tested is mounted on sharp-tip tweezers. The other end of the tweezers is mounted on a pneumatic motor, which is controlled by computer. For detailed information on the plunging machine, see the work by White et al.⁴⁹. As cryogen, liquid ethane is used. The averaged plunging speed can be controlled by the gas pressure, and 40 psi was used in this study to generate a plunging velocity of 1.9 m/s. The distance from the sprayer nozzle to the surface of the liquid ethane surface can be adjusted down to a minimum value of 10 mm. The horizontal distance sprayer-grid was fixed at 3.5 mm. The ambient conditions in the environmental chamber can be maintained in the ranges of 22°C–25°C temperature and 85%–95% relative humidity. Compared with our previous design²⁶, the newly-designed micro-sprayer works better even at the lower pressure of 8 psi without producing the previously observed dripping problem²⁶. In this work, we used 8 psi as the working gas pressure throughout, which ensures stable, reproducible spray.

High-efficiency SAR PDMS-based micromixer

To efficiently and fast mix the solutions of interest, we used the 3D SAR PDMS-based micromixer⁵⁰ (or 3D crossing micromixer), which is superior to the planar micromixer (for example, the planar butterfly-type micromixer used in Lu et al.’s design¹⁶ adopted in our previous work^8–11,51).

To measure the mixing efficiency of this micromixer, we conducted experiments by injecting DI water and fluorescent water into its two separate inlets. The mixing efficiency E can be quantitatively evaluated⁵² as $E = (1 - \sqrt{1 / n \sum {(I_{i} - I_{a v})}^{2}} / I_{a v}) \times 100 %$ , where $I_{i}$ is the fluorescent intensity in pixel $i, n$ is the total number of pixels, and $I_{a v}$ is the average intensity of $n$ pixels. For unmixed fluids, $E = 0$ , and for completely mixed fluids, $E = 1$ . Usually, $E > 90 %$ is taken to indicate excellent mixing performance.

The results of our mixing experiments are shown in Figure 1D. We observed that when the flowrate was increased from 2 to 6 μL/s, more striations appeared at the mixer outlet because of the strong rotation and splitting of the contact surface between two fluids, indicating that the mixing efficiency was greatly enhanced. Based on the good agreement between experimental and simulation results, we find that in the whole range of total flowrates from 2 to 6 μL/s, the mixing efficiency at the outlet exceeds 90%. From this range, 6 μL/s was chosen as the working flowrate for this study to achieve both the shortest mixing time and efficient mixing performance. In the following we address the question to what extent the fluorescent dye experiment reports on the mixing efficiency of HflX and ribosomes.

Despite the fact that the diffusion coefficients of fluorescent dye, HflX and ribosome span four orders of magnitude (D= 4.2×10⁻¹⁰, 1.0×10⁻¹⁰, and 4.0×10⁻¹⁴ m²/s, respectively)^53–55, their mixing efficiency is virtually the same under the conditions of our experiments (working flowrate of 6 μL/s, mean velocity of 3.75 m/s, and thus very high Reynolds number (150)). This is the consequence of the large dominance of convection over diffusion in the convection-diffusion equation $\partial c / \partial t = \nabla \cdot (D \nabla c) - \nabla (v c)$ ( $c$ = species concentration of the solution, $v$ velocity vector) under those conditions.

The diffusion independence is borne out by our simulation of the mixing process for all three molecules. For the simulation work, we used the open source software FreeCAD⁵⁶ for 3D parametric modelling, Gmsh⁵⁷ for generating the three-dimensional finite element mesh system, and OpenFoam⁵⁸ for simulating the fluid flow and the mixing process. A tetrahedral mesh system with an element number of 1.01×10⁶ to ensure the accuracy of the simulation. In order to save computing time in the simulation, we simulated the mixing performance using the first five mixing units only. For the boundary condition setup, we followed the previous studies^50,59. We obtained the result summarized in Figures S1H and I: when the total flowrate ranges between 2 to 6 μL/s, the mixing efficiency, after passing five mixing units, always remains higher than 90%. This working range of flow-rates cannot be achieved with the butterfly-type micromixer of Lu, et al.’s design¹⁶, whose performance at low flowrate is limited.

For these reasons the experimental results obtained for fluorescent dye (Fig. 1D) can be taken as a measure for the conditions of our HflX/ribosome experiment, as well, and can in fact be extended to any biological molecules with sizes similar to the ribosome.

SiO2-coating inside the micromixer for mitigating protein adsorption

${S i O}_{2}$ coating was performed inside the PDMS micromixer channel to prevent proteins of the sample from sticking to the PDMS plastic. The measurements show that up to 50% of the protein is lost without coating. Adverse effects of this problem include uncontrolled changes in concentration of the two mixing components during the use of the micromixer, which alter the stoichiometry of the reaction, rendering the results of time-resolved study invalid.

Following protocols in the literature, we tried PDMS-PEG⁶⁰, and found that PDMS-PEG surface cannot be bonded with PDMS-PEG or glass surfaces very well, producing leakage in the micromixer under the high working flowrate of 6 μL/s. While the Zwitterionic Polymer (pCBMA)⁶¹ is potentially another good choice for hydrophilic material, the coating process is quite lengthy and complicated, as it requires oxidation of PDMS surface, immobilization of the ATRP trichlorosilane initiator, cross-linking of the surface silanes, neutralization of the surface, initiation of polymerization using copper catalyst solution, and then polymerization. For all these reasons, the ${S i O}_{2}$ coating is a better choice for our application.

For ${S i O}_{2}$ coating, plasma-enhanced chemical vapor deposition (PECVD) was performed to deposit a thin ${S i O}_{2}$ layer onto the interior PDMS micromixer channel walls using the PlasmaPro^®NGP80 system (Oxford Instruments, Abingdon, UK). High radio frequency (RF) power (50W) was used to create plasma inside the process chamber. During plasma treatment, the source gases used for plasma were $N_{2} O$ (710 sccm) and ${SiH}_{4}$ (170 sccm), the vacuum pressure was 200 mTorr, the substrate temperature was 300 °C, and the coating strike lasted for 20 min. The ${S i O}_{2}$ layer is around 1.9 μm in thickness, as measured on Filmetrics F20. The reaction formula is as below for ${S i O}_{2}$ layer formation under plasma conditions:

2 N_{2} O + {S i H}_{4} = {S i O}_{2} + 2 N_{2} + 2 H_{2}

(1)

Protein adsorption assessment with E. coli 70S ribosome was performed to compare the properties of differently treated chip assemblies: without coating, coated with n-dodecyl-β-D-maltoside (DDM) coating, or coated with ${S i O}_{2}$ . DDM is an alkyl polyglucoside, a very mild non-ionic surfactant which can be used for improving the hydrophilicity of the surface of PDMS. We followed the experimental procedure from B. Huang and coworkers’ work⁶² for the DDM coating. A solution containing 20 mM Hepes, 100 mM NaCl, and 0.1% DDM at pH 7.5 was introduced in the microfluidic chip assembly for incubation for 5 minutes. Then the assembly was washed with constant flow (1 mL/h) to prepare it for protein adsorption testing.

For each type of treatment, we performed a test of the chip by passing through it a sample of 70S ribosomes at least six times, then spraying it out and collecting it for concentration measurement by spectrophotometric analysis using NanoDrop^® (Thermo Fisher Scientific, Waltham, MA, USA). The absorbance values at 260 nm ( $A_{260}$ ) for the initial concentration as control was 0.966 on average (where $A_{260} = 1 = 20 n M$ ). The $A_{260}$ values for the samples using chips with different coating methods are shown in Table S2. The measurements of ribosome concentration after passing the sample through the chips show (Figure 1H) that 94% of the initial concentration is retained using the ${S i O}_{2}$ -coated chip, while only 54% and 60% of the initial concentration are retained without coating or with DDM coating, respectively, demonstrating that the ${S i O}_{2}$ coating can effectively mitigate the problem of protein adsorption.

Choice of microcapillary tubing as the reactor for stable reaction time control

In this study, we are using micro-capillary tubing with circular transverse section as micro-reactor. In principle, the fluid flow is subject to the no-slip boundary condition at the walls. The hydrodynamic entrance length is 0.05ReD, where Re is the Reynolds number and D is the diameter of the tubing. After passing the micro-capillary over a distance equal to the hydrodynamic entrance length, the velocity profile of the fluid flow is fully developed into a parabolic profile. So, a fully developed velocity profile (FDVP) for a circular tubing can be expressed in the following equation⁶³,

V (y, z) = 2 \bar{V} (1 - \frac{(y - A)^{2} + (z - B)^{2}}{r^{2}})

(2)

where $\bar{V}$ is the mean velocity, $(A, B)$ are the coordinates of the center of the inlet, and $r$ is the inner radius of micro-reactor. The mean velocity is determined by the volume of the tubing and the volumetric flowrate. For a tubing with $r = 75 μ m$ , the hydrodynamic entrance length is 0.38 mm, which means that the fluid flow can be easily developed to be stable after 1 ms based on the parabolic profile (Figure S1J)

Redesign of the microsprayer

In our previous work²⁶, the microsprayer (Figures S1C–E) was designed and fabricated to generate a three-dimensional cone plume of sprayed droplets. This microsprayer contains mainly an inner tubing serving as a liquid injector and an outer tubing as gas nozzle, which are both accommodated in the PDMS slab. Orifices of inner and outer tubing were not aligned in that design. Subsequently, in practical experiments, we found out that part of the solution was dripping from the orifice when lower gas pressure was used. To solve this dripping problem, we aligned the orifices of the inner and outer tubings on the same plane and also centered them precisely, as shown in Figure 5S. After this redesign, the micro-sprayer generated a cone of droplets at gas pressure of 8 psi and flowrate of 6 μL/s without exhibiting the dripping problem. With this microsprayer, the spray is found to be stable and reproducible, at pressure conditions low enough to prevent damage to the EM grid.

Assembly and disassembly of the TR chip

For the fabrication of the entire chip assembly, we developed a modular strategy such that it can be customized for individual experiments by assembling it from three modules (mixer, reaction channel, sprayer), allowing each of its parts to be reused after disassembly (Figures S1F and G). The advantage of the modular design is that any of the three elements of the chip that is found not functioning can be readily replaced by a new one. This is also convenient for cleaning the microreactor channel through oxygen plasma treatment before each new reaction experiment. Normally, the microfluidic chip assembly is used for a duration of one month.

Estimation of reaction time achieved using the TR method

As in our previous mixing/plunging method¹⁶, the total reaction time consists of the mixing time in the micromixer, the reaction time in the micro-capillary reactor, the spraying time, the plunging time, and the reaction time during the vitrification process. For our current method, each time is separately calculated below.

The mixing time in the micromixer, $t_{m}$ . The mixing time is estimated by the equation⁶⁴: $t_{m} = V_{m} / U_{f}, V_{m}$ is the volume of micromixer, $U_{f}$ is the total flowrate of the solutions introduced into the micromixer. As measured in the 3D modelling software FreeCAD, $V_{m}$ is 280 nL, and $U_{f}$ is 6 μL/s, so the mixing time is estimated to be ~0.47 ms.
The reaction time in the microcapillary reactor, $t_{r}$ . Because of the parabolic profile of velocity distribution in the capillary tubing, the real residence time for the reaction is in a time range. To simplify, we estimate the reaction time in the tubing based on the mean velocity and the volume of the tubing: $t_{r} = L_{r} / \bar{V}$ , where $L_{r}$ is the length of the microcapillary reactor, $\bar{V}$ is the mean velocity of the fluid, which is equivalent to $U_{f} / S$ , and $S$ is the transversal area of the micro-capillary.
The flying time of the droplets from the micro-sprayer orifice to the EM grid, $t_{f}$ . The Sauter mean diameter (SMD) as the average of the droplets can be estimated by the following expression^65,66,
$S M D = 0.95 [\frac{{(σ_{l} {\dot{m}}_{l})}^{0.33}}{V_{r} ρ_{l}^{0.37} ρ_{g}^{0.30}}] {[1 + \frac{{\dot{m}}_{l}}{{\dot{m}}_{g}}]}^{1.70} + 0.13 μ_{l} {[\frac{D}{σ_{l} ρ_{l}}]}^{0.5} {[1 + \frac{{\dot{m}}_{l}}{{\dot{m}}_{g}}]}^{1.70}$ (3)
where $\dot{m}$ is the mass flow rate, and subscripts $g$ and $l$ denote gas and liquid. Suppose that water is used for atomization, for which viscosity $μ_{l}$ , surface tension $σ_{l}$ , density $ρ_{l}$ are 0.89×10⁻³ Pa·s, 0.072 N/m, 1×10³ kg/m³, respectively. $D$ is diameter of the inner tubing of the micro-sprayer, which is 75 μm. For our study, the flow rate of the liquid is 6 μL/s and the mass flow rate ${\dot{m}}_{l}$ of liquid is 0.0216 kg/h. The liquid velocity at the micro-sprayer orifice⁶⁷ is $16 {\dot{m}}_{l} / 5 ρ_{l} π D^{2}$ , which is 1.1 m/s. At 8 psi, the volumetric flow rate measured is ~0.2 L/min, and the density $ρ_{g}$ of $N_{2}$ is 1.71 kg/m³ at room temperature, so the mass flow rate ${\dot{m}}_{g}$ of $N_{2}$ gas is 0.02 kg/h and the gas velocity is $V_{g} = \sim 31.6 m / s . V_{r}$ is the relative velocity between the gas and liquid, $V_{r} = V_{g} - V_{l}$ ; for estimation, we use the liquid velocity at the microsprayer orifice as $V_{l}$ . We also have the Weber number based on the SMD,
$W e_{S M D} = \frac{ρ_{l} V_{l}^{2} S M D}{σ_{l}}$ (4)

The velocity of the droplet depends on the ratio of dynamic force to surface tension force, and it is governed by the following relation⁶⁸,
$W e_{c} = \frac{ρ_{g} {(V_{g} - V_{d})}^{2} S M D}{σ_{l}} \approx W e_{S M D}$ (5)

Then the averaged velocity of the droplets $V_{d}$ can be estimated, which is around 6.4 m/s, so that we can estimate the mean flying time of the droplets to be $t_{f} = D_{f} / V_{d}$ , where $D_{f}$ is the distance from the micro-sprayer orifice to the EM grid, fixed at 3.5 mm for our implementation, and thus we obtain a mean droplet flying time of ~0.55 ms.
The plunging time, $t_{p}$ . The plunger is pneumatic, and the plunging speed $V_{p} = 1.9 m / s$ at $N_{2}$ gas pressure of 40 psi. So, the plunging time $t_{p} = H_{p} / V_{p}$ , where $H_{p}$ is the plunging height from the micro-sprayer orifice to the liquid ethane surface.
The reaction time during the vitrification process, $t_{v}$ . We assume that at 0°C (273.15K) the reaction is slow, and the reaction time can be neglected when the temperature is going down to below 0°C during the vitrification process. And we have the critical cooling rate (CCR)⁶⁹ which is ~10⁵ K/s. So, we can estimate the reaction time in the vitrification process is $t_{v} = (T_{room} - 273.15) / C C R$ , which amounts to ~0.23 ms.

Thus in total, the reaction time can be estimated as $t = t_{m} + t_{r} + t_{f} + t_{p} + t_{v}$ . In practice, the shortest reaction time we are able to achieve is ~10 ms, when the microreactor tubing is 5 mm in length and 75 μm in diameter, and the plunging height is 10 mm. By varying the microreactor tubing length, the reaction time can be tuned from 10 to 1000 ms. For the application in the HflX study we implemented only tubings for four reaction time points, and all the parameters about the chip assemblies are listed in Table S1. Based on the above-mentioned time estimates, the reaction times in the HflX experiment could be set at 10, 25, 141, and 899 ms, respectively (For simplification, we use rounded figures of 140 and 900 ms in the following).

Preparation of the time-resolved cryo-grids using the TR chip

Quantifoil Cu R0.6/1 grids with 300 mesh size were subjected to glow discharge with air for 30 s using a PELCO easiGlow cleaning system set to a plasma current of 15 mA, to make the carbon film surface negatively charged (hydrophilic), which allows aqueous solutions to spread easily. During the experiment, the microfluidic chip was mounted in an environmental chamber⁸, in which the temperature and humidity were kept at 22 °C ~24 °C and 90%~95%, respectively. For each of the four time points (10 ms, 25 ms, 140 ms, 900 ms) and the control experiment, the 70S, HflX, and GTP were diluted to 1 μM, 5 μM, and 1 mM, respectively, with 20 mM Tris-HCl, pH 7.5, 100 mM NH₄Cl, 10 mM Mg(OAc)₂, and 4 mM βME mixing buffer. Solution A: 1 μM 70S in mixing buffer, and Solution B: 5 μM of HflX with 1 mM GTP in the same buffer were introduced into the different microfluidic chips at a flow rate of 3 μL/s for each, such that they were mixed efficiently and sprayed onto a plasma-treated grid. The resulting concentrations of the 70S ribosome and HflX after effective mixing in our microfluidic chip were around 0.5 μM and 2.5 μM, respectively (Concentrations were measured separately for each component after collection from the chip.) After the reaction product was sprayed onto the grid, the latter was immediately plunged into liquid ethane for the vitrification of the sample. Based on our previous study²⁶, the gas pressure for atomization was controlled at 8 psi to generate properly sized droplets for data collection. Each grid was stored in liquid nitrogen dewar until it was ready for imaging. In this study, after screening for quality checks, around 2 grids on average per time point were used for data collection. For data collection, we used 3, 1, 2, 1, and 1 grid(s) for 10 ms, 25 ms, 140 ms, 900 ms, and control, respectively.

Preparation of EM grids for control experiment for Apo-70S using the TR chip

1 μM 70S (without salt-wash) in mixing buffer (Solution A) and mixing buffer (Solution B) were introduced into the 900 ms microfluidic chip. The next steps were the same as described above.

TR cryo-EM data collection

All the data from both the TR and control experiments were collected using a 300 kV Titan Krios (Thermo Fisher Scientific, Waltham, MA) equipped with a K3 direct detector camera (Gatan, Pleasanton, CA). For the blotted grids from the control experiment, the data collection followed our previous procedure^8–11, and was done automatically using the Leginon software⁷⁰. For the TR-grids, on the square targeting, the positions of collectible droplets need to be picked up from the atlas based on our previous work^9,10, and on the hole targeting, the thick-ice area needs to be avoided based on the intensity on the hole images as shown in Figure S2, so these two steps can be finished manually. Focusing was performed on the carbon foil before each exposure. After focusing twice, an exposure was immediately taken with an image shift producing a beam-tilt smaller than 0.005 mrad. For TR grids, in the exposure mode, the movie stacks were recorded within a defocus range of 1.0 to 2.5 μm on a Gatan K3 Summit direct detector camera combined with the Gatan Bioquantum energy filter (slit width of 20 eV), operating in counting mode with a nominal magnification of 105,000×, equivalent to 0.83 Å per pixel. Images were composed of 50 frames that were exposed for a total of 2.5 s, corresponding to a total dose of 58 e⁻/Å². Some representative micrographs from TR grids are shown in Figure S3B.

Cryo-EM data processing

A flow-chart of the data processing containing the steps is shown in Figure S4D. 3452, 3598, 3530, and 3603 good micrographs were selected from TR experiments at 10, 25, 140, and 900 ms, respectively, for further data processing. The beam-induced motion of the sample was corrected using the MotionCor2 program⁷¹ in Relion-4.0⁷² or CryoSPARC v3.3.1⁷³. The contrast transfer function (CTF) of each micrograph was estimated using the CTFFIND4⁷⁴. Particle picking was performed using Topaz⁷⁵. Good particles were selected by 2D classification and trained using 20,000 particles. Autopicking using the trained topaz model yielded 1,001,596 particles from all combined good micrographs (total: 14,183). Particles picked by Topaz were subjected to 2D classification for a further selection of good particles, which yielded 802,562 particles. All particles were pooled together and used for 3D initial model generation followed by 3D auto-refinement, applying C1 symmetry in Relion-4.0⁷². CTF refinements were done to correct for magnification anisotropy, fourth-order aberrations, per-particle defocus, and per-particle astigmatism, followed by another 3D auto-refinement. Then 3D classification was performed on the entire pooled dataset^9,10 without alignment, using the angular information from the previous refinement step. The 3D classification produced seven distinct classes, which we named (1) rotated 70S without HflX (r70S_noHflX, 56,894 particles); (2) non-rotated 70S without HflX (nr70S_noHflX, 96,898 particles); (3) 70S like intermediate-I with HflX (i70S_HflX-I, 140,682 particles); (4) 70S like intermediate-II with HflX (i70S_HflX-II, 138,296 particles); (5) 70S like intermediate-III with HflX (i70S_HflX-III, 113,038 particles); (6) 50S with HflX (50S_HflX, 62,558 particles); and (7) 30S (58,952 particles) with total 667,318 particles. To calculate the classification errors for the pooled particles, three separate 3D classifications with different seeds were performed¹⁰. Percentages of particles falling into each class with respect to the total of 667,318 are shown in Figure 3M. In the pooled dataset, each picked particle was labeled by the time point of the micrograph it originated from. The entire pooled dataset was then subjected to 3D classification. A mixture of particle populations with a time range of 10–900 ms exists in each class, with each particle identifiable by time stamp. Particles from the 50S_HflX class were further subjected to 3D auto-refinement, and the post-processing was done with Relion-4.0 and DeepEMhancer⁷⁶. The detector pixel size was 0.83 Å, and for final data processing we binned the datasets to 1.03 Å. The angular distributions of projections for each of the reconstructions are shown in Figures S6J–M. For the intermediate states, from the 3D classes (Figure S4D) the 30S portion was first separated by masking and focused refinement was performed, then the projected density corresponding to the 30S subunit was subtracted from the refined particles, and focused refinement was done on the 50S subunit part. All the FSC resolution estimates are contained in Figure S5. For the refinement of the HflX density region, particles from each intermediate state and the 50S_HflX subunit were individually masked and 3D classification was performed on the masked-out HflX density without alignment. Further, Ewald sphere correction⁷⁷ was performed on the two resulting half-maps using relion_reconstruct. In the control TR experiment for Apo-70S, the same above-mentioned processing steps were followed with 140,338 particles. The corresponding particle numbers for non-rotated and rotated apo-70S were 75,552 and 64,786, respectively. Here we found only the 70S state, so for the purpose of the particle percentage calculation, it was considered as a 100% population. Local resolutions were estimated using ResMap⁷⁸. To build models for the 70S ribosome class reconstructions and HflX, the pdb id:6XE0⁷⁹ for 30S, pdb id:6XZ7⁸⁰ for 50S, pdb id: 4PYG⁸¹ for GTP, pdb id: 1GIT⁸² for GDP-Pi, and pdb id: 5ADY² for HflX were selected as starting models. Models were first refined using Phenix real-space refinement⁸³. Residues that did not fit correctly into the map were manually placed using COOT⁸⁴. Further model validations were done using Phenix Comprehensive Validation (cryo-EM) and tabulated in Table S3. Figures 3–5 were generated using UCSF ChimeraX⁸⁵.

Determining the position vector of the unique point through which the rotation axis passes

The tool we previously developed²⁹ for determining the rotation axis, using the absolute orientation method produces a closed-form solution of the coordinate axis transformation in the form of a unit quaternion. A description of the algorithm and details of implementation are provided in our previous work²⁹. The unit quaternion encodes the rotation axis and rotation angle, which can be obtained using the angle-axis form of the unit quaternion. However, although the translation from the initial to the transformed centroids can be computed easily, the unit quaternion representing the rotation does not contain the position vector of the unique point ${\vec{C}}_{⊥}$ (Figure 6L) through which the rotation axis $\hat{l}$ passes. For determining ${\vec{C}}_{⊥}$ , we use the theory of screw axis of spatial displacement^86–89 which has also been used in a few other applications in the literature^90–92. Here we provide a formulation of the rigid-body motion along with the derivation of ${\vec{C}}_{⊥}$ (Figure 6L) below.

We use the position vectors of the start and the end position of the rigid body center of mass as depicted in Figure 6L. Let ${\vec{t}}_{∥}$ and ${\vec{t}}_{⊥}$ be the components of the translation $\vec{t}$ , that are parallel and perpendicular respectively to the rotation axis $\hat{l}$ . Then we have,

{\vec{t}}_{∥} = (\hat{l} \cdot \vec{t}) \hat{l}

(6)

\Rightarrow {\vec{t}}_{⊥} = \vec{t} - {\vec{t}}_{∥} = \vec{t} - (\hat{l} \cdot \vec{t}) \hat{l}

(7)

Now,

{\hat{y}}_{b} = \frac{{\vec{t}}_{⊥} \times \hat{l}}{∥ {\vec{t}}_{⊥} \times \hat{l} ∥} = \frac{{\vec{t}}_{⊥} \times \hat{l}}{∥ {\vec{t}}_{⊥} ∥ ∥ \hat{l} ∥ |s i n (\frac{π}{2})|} = \frac{{\vec{t}}_{⊥} \times \hat{l}}{∥ {\vec{t}}_{⊥} ∥ \cdot 1 \cdot 1} = \frac{{\vec{t}}_{⊥} \times \hat{l}}{∥ {\vec{t}}_{⊥} ∥}

(8)

Also from Figure 6,

\frac{\frac{1}{2} ∥{\vec{t}}_{⊥}∥}{∥ {\vec{y}}_{b} ∥} = t a n \frac{θ}{2} \Rightarrow ∥ {\vec{y}}_{b} ∥ = \frac{1}{2} c o t \frac{θ}{2} ∥{\vec{t}}_{⊥}∥

(9)

Then we have from equations (8) and (9),

{\vec{y}}_{b} = ∥ {\vec{y}}_{b} ∥ {\hat{y}}_{b} = \frac{1}{2} c o t \frac{θ}{2} ∥ {\vec{t}}_{⊥} ∥ \frac{{\vec{t}}_{⊥} \times \hat{l}}{∥{\vec{t}}_{⊥}∥} \Rightarrow {\vec{y}}_{b} = ∥ {\vec{y}}_{b} ∥ {\hat{y}}_{b} = \frac{1}{2} c o t \frac{θ}{2} {\vec{t}}_{⊥} \times \hat{l}

(10)

Now,

\vec{C A_{p}} + \frac{1}{2} {\vec{t}}_{⊥} = {\vec{y}}_{b} \Rightarrow \vec{C A_{p}} = {\vec{y}}_{b} - \frac{1}{2} {\vec{t}}_{⊥}

(11)

Next,

\vec{O A_{p}} = \vec{O C} + \vec{C A_{p}} \Rightarrow \vec{O C} = \vec{O A_{p}} - \vec{C A_{p}}

Then using equation (11),

\vec{O C} = \vec{O A_{p}} - ({\vec{y}}_{b} - \frac{1}{2} {\vec{t}}_{⊥})

(12)

Now,

\vec{O A_{p}} = \vec{O A} - \vec{A_{p} A}

(13)

Also, let the angle between $\vec{O A}$ and the plane be $α$ , so the angle between $\vec{O A}$ and $\hat{l}$ is $\frac{π}{2} - α$ , then we have:

\vec{O A} \cdot \hat{l} = ∥ \vec{O A} ∥ ∥ \hat{l} ∥ c o s (\frac{π}{2} - α) = ∥ \vec{O A} ∥ \cdot 1 \cdot s i n α = ∥ \vec{O A} ∥ s i n α

Also, we have $∥ \vec{O A} ∥ s i n α = ∥ \vec{A_{p} A} ∥$

\Rightarrow \vec{O A} \cdot \hat{l} = ∥ \vec{A_{p} A} ∥

(14)

Now, the vector,

\vec{A_{p} A} = ∥ \vec{A_{p} A} ∥ \hat{l}

Using equation (14)

\vec{A_{p} A} = (\vec{O A} \cdot \hat{l}) \hat{l}

(15)

Using equations (13) and (15), we have

\vec{O A_{p}} = \vec{O A} - \vec{A_{p} A} = \vec{O A} - (\vec{O A} \cdot \hat{l}) \hat{l}

(16)

Therefore, using equations (10), (12) and (16), we have

\vec{O C} = \vec{O A_{p}} - ({\vec{y}}_{b} - \frac{1}{2} {\vec{t}}_{⊥}) = \vec{O A} - (\vec{O A} \cdot \hat{l}) \hat{l} - (\frac{1}{2} c o t \frac{θ}{2} {\vec{t}}_{⊥} \times \hat{ı} - \frac{1}{2} {\vec{t}}_{⊥})

Now denoting $\vec{O C}$ by ${\vec{C}}_{⊥}, \vec{O A}$ by ${\vec{x}}_{0}, \vec{O B}$ by ${\vec{x}}_{1}$ we have,

{\vec{C}}_{⊥} = {\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{1}{2} [{\vec{t}}_{⊥} - c o t \frac{θ}{2} {\vec{t}}_{⊥} \times \hat{l}] \Rightarrow {\vec{C}}_{⊥} = {\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{1}{2} [{\vec{t}}_{⊥} + c o t \frac{θ}{2} \hat{l} \times {\vec{t}}_{⊥}]

(17)

Now from equation (2), we have

{\vec{t}}_{⊥} = \vec{t} - (\hat{l} \cdot \vec{t}) \hat{l} = \hat{l} \times (\vec{t} \times \hat{l})

and

\hat{l} \times {\vec{t}}_{⊥} = \hat{l} \times (\vec{t} - (\hat{l} \cdot \vec{t}) \hat{l}) = \hat{l} \times \vec{t} - (\hat{l} \cdot \vec{t}) \hat{l} \times \hat{l} = \hat{l} \times \vec{t} [as \hat{l} \times \hat{l} = 0]

Letting $\vec{b} = t a n \frac{θ}{2} \hat{l}$ we can rewrite,

{\vec{C}}_{⊥} = {\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{\vec{b} \times \vec{t} - \vec{b} \times (\vec{b} \times \vec{t})}{2 \vec{b} \cdot \vec{b}}

(17a)

Next also we have $\vec{t} = {\vec{x}}_{1} - {\vec{x}}_{0}$

Therefore, equation (17) can be re-written in terms of the position vectors ${\vec{x}}_{0} & {\vec{x}}_{1}$

{\vec{C}}_{⊥} = {\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{1}{2} [\vec{t} - (\hat{l} \cdot \vec{t}) \hat{l} + c o t \frac{θ}{2} \hat{l} \times \vec{t}] = {\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{1}{2} [({\vec{x}}_{1} - {\vec{x}}_{0}) - (\hat{l} \cdot ({\vec{x}}_{1} - {\vec{x}}_{0})) \hat{l} + c o t \frac{θ}{2} \hat{l} \times ({\vec{x}}_{1} - {\vec{x}}_{0})] = {\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{1}{2} [({\vec{x}}_{1} - {\vec{x}}_{0}) - (\hat{l} \cdot ({\vec{x}}_{1} - {\vec{x}}_{0})) \hat{l} + c o t \frac{θ}{2} \hat{l} \times ({\vec{x}}_{1} - {\vec{x}}_{0})] = [{\vec{x}}_{0} + \frac{1}{2} ({\vec{x}}_{1} - {\vec{x}}_{0})] - [({\vec{x}}_{0} \cdot \hat{l}) \hat{l} + \frac{1}{2} (\hat{l} \cdot ({\vec{x}}_{1} - {\vec{x}}_{0})) \hat{l}] + \frac{1}{2} c o t \frac{θ}{2} \hat{l} \times ({\vec{x}}_{1} - {\vec{x}}_{0}) \Rightarrow {\vec{C}}_{⊥} = \frac{({\vec{x}}_{1} + {\vec{x}}_{0})}{2} - (\hat{l} \cdot \frac{({\vec{x}}_{1} + {\vec{x}}_{0})}{2}) \hat{l} + \frac{1}{2} c o t \frac{θ}{2} \hat{l} \times ({\vec{x}}_{1} - {\vec{x}}_{0})

(18)

As we can see, the position vector ${\vec{C}}_{⊥}$ of the unique point on the rotation axis $\hat{l}$ can be expressed in terms of the initial and transformed position vectors ${\vec{x}}_{0} & {\vec{x}}_{1}$ , respectively, specifically in terms of the mid-point $({\vec{x}}_{0} + {\vec{x}}_{1}) / 2$ and the translation vector ${\vec{x}}_{1} - {\vec{x}}_{0}$ . This provides a precise location estimate of the unique point through which the screw axis passes.

We can obtain (derivation not shown here) the exact same expression for ${\vec{C}}_{⊥}$ as in equation (18) using the Rodrigues displacement equation^93–96 for the rigid body motion as described in Figure 6L.

Note that the expression for ${\vec{C}}_{⊥}$ in equations (17) and (17a) contains the extra term ${\vec{x}}_{0} - ({\vec{x}}_{0} \cdot \hat{l}) \hat{l} = \hat{l} \times ({\vec{x}}_{0} \times \hat{l})$ . This represents a generalized form, which allows the introduction of an arbitrary reference origin. The remaining terms in equations (17) and (17a) match with the previous derivation in the literature^97,98.

In this way we computed the rotation axis $\hat{l}$ and also the point with position vector ${\vec{C}}_{⊥}$ for the motion of the 30S subunit with respect to the large subunit of the ribosome (for Axis-I and -II). (Figure 6D–I). We have also computed the rotation axis for the 30S head rotation (Axis-III) with respect to the 30S subunit body (Figure S8C).

In these computations the first intermediate, i70S_HflX-I, posed a problem since the density of uL2 was poorly resolved due to disorder or positional heterogeneity. Leaving it out in the modelling was not an option since its absence would change the axes of inertia of the 50S subunit that enter the computation of hinge axes. Therefore, we placed and modelled uL2 in the same position as in i70S_HflX-II for the determination of the hinge axes.

Molecular Dynamics (MD) Simulation

MD simulation was performed on free HflX only, based on the method previously described^99,100. The HflX model was taken from pdb id: 5ADY. The length of the simulation was 1000 ns. For the determination of flexibility of HflX domains, order parameters $(S^{2})$ were calculated as described previously^99,100. Backbone N-H vectors were selected to calculate $S^{2}$ over the period of trajectory, which represents the dynamics of protein, with a value of 1 indicating complete rigidity and a value of 0 representing enhanced dynamics.

QUANTIFICATION AND STATISTICAL ANALYSIS

The details of experiments including the statistical tests used, estimation of the reaction time, determination of the rotation axis, are indicated in method details, figures, and figure legends. Microsoft Excel was used for statistical analyses if not specified.

Supplementary Material

Figure S1. Time-resolved (TR) cryo-EM apparatus for sample preparation, related to Figure 1. (A) Photograph of the setup, including computer, pumping system, pneumatic plunger, and environmental chamber. (B) Schematics of apparatus. (C), (D), and (E) 3D model of microsprayer in oblique, top, and side views. (F) Complete TR chip assembly. (G) Three separate modules of the TR chip assembly. (H) Mixing efficiency along the outflow direction under different total flowrates, where L = 0.92 mm represents the position of the outlet, based on the mixing simulation for the 3D SAR PDMS-based micromixer. (I) Mixing efficiency against the flowrate ranging from 2 to 6 μL/s (50 ⩽ Re ⩽150), based on the same mixing simulation in (H). (J) Numerically calculated parabolic velocity profile in capillary tubing along the horizontal (y-axis) and vertical (z-axis) centerline of the inlet channel at different coordinates x for the fully developed case, $\bar{V} = 0.34 m / s$ $(R e = 51)$ , and the dashed line represents the mean velocity.

NIHMS1955310-supplement-1.tif^{(19MB, tif)}

Figure S2. Data collection, related to Figure 2. (A), (B), (C), and (D) correspond to 10, 25, 140, and 900 ms, respectively. An atlas was screened for each grid at the different time points (left column); droplets found for square targeting (middle column); and thin ice areas on the droplet chosen for targeting of holes (right column).

NIHMS1955310-supplement-2.tif^{(20.3MB, tif)}

Figure S3. Representative examples for two types of droplets and micrographs from the TRCEM experiment, related to Figure 2. (A) Those without contact with the grid bar are marked red; and those contacting the grid bar are marked green. (B) High-resolution micrographs captured from the Krios cryo-electron microscope equipped with a Gatan K3 Summit camera.

NIHMS1955310-supplement-3.tif^{(16.1MB, tif)}

Figure S4. The sample of 70S and HflX used for TRCEM experiments and related data collection and processing, related to Figure 3. (A) Sucrose gradient profile of the 70S purified from MRE600. (B) Sucrose gradient profile of dissociated 50S and 30S from 70S in presence of HflX and GTP, and shown in black line. Control 70S without HflX and GTP is shown in the red line. (C) SDS PAGE gel profile of control 70S (1^st lane), 70S+HflX+GTP complex (3^rd lane), and standard protein marker (2^nd lane) representing the outcome of the co-sedimentation assay. (D) Flow chart of TRCEM data collection and processing, and the names of the different 3D class and the corresponding numbers of particles are noted under each class.

NIHMS1955310-supplement-4.tif^{(15.8MB, tif)}

Figure S5. Resolution estimation via FSC, related to Figure 3. (A), (C), (E), and (G), FSC plots and estimated resolutions for the 50S subunit of i70S_HflX-I, i70S_HflX-II, i70S_HflX-III, and for 50S_HflX itself, respectively. (B), (D), and (F), FSC plots and estimated resolutions for the 30S subunit of i70S_HflX-I, i70S_HflX-II, and i70S_HflX-III. The masks used and the corresponding maps are shown in the inset. (H), FSC plots and resolution for the 70S consensus refinement from 802,562 particles. All representations are raw reports obtained from Relion-4.0.

NIHMS1955310-supplement-5.tif^{(19.6MB, tif)}

Figure S6. Local resolution estimation of the three intermediates, related to Figures 3 and 6. The intersubunit regions are shown by hiding either the 30S subunit (for B, E, and H) or the 50S subunit (for C, F, and I). Hinge axes are shown by black lines. The absence of a gradient of resolution normal to the hinge axis of the 30S subunit indicates that the rotations of subunits in the three intermediates are sharply defined, and that the progression from one intermediate to the other is stepwise. (G-J) are the angular plots of particles for intermediates i70S_HflX-I, i70S_HflX-II, i70S_HflX-III, and 50S_HflX, respectively.

NIHMS1955310-supplement-6.tif^{(18.8MB, tif)}

Figure S7. Last step of 70S splitting – comparison with literature, related to Figure 3. (A) and (B) reconstructions of 50S_HflX (gray) and published structure of 50S-HflX-GNP-PNP (yellow, EMDB:3133). HflX in 50S_HflX is shown in magenta and 50S in gray. (C) Superimposition of 50S_HflX and 50S-HflX-GNP-PNP. (D) view (in ChimeraX) of refined 50S_HflX structure shown in (A) at lower threshold level, indicating that there is no clear visible density of the 30S subunit associated with 50S_HflX.

NIHMS1955310-supplement-7.tif^{(13MB, tif)}

Figure S8. 30S subunit head rotation during HflX-catalyzed ribosome splitting, and molecular dynamics of HflX, and potential clash between HflX and tRNA, related to Figures 3 and 4. (A) and (B) Superimposition of maps and atomic models of the 30S from i70S_HflX-I (red), and i70S_HflX-II (green), respectively. (C) The rotation of the 30S head is calculated with respect to the 30S body. The rotation of the 30S head of i70S_HflX-I by 2.1° around hinge Axis-III (green) to adopt the conformation of the 30S subunit in i70S_HflX-II. (D) Model of HflX showing its flexible region with residue numbers in various colors. (E) Superimposition of the three conformations extracted from 1000 ns MD simulation trajectory of free HflX. Conformations at 0 ns, 500 ns, and 1000 ns are shown in magenta, green, and blue, respectively. (F) Order parameters, calculated to characterize the flexible regions of HflX, and are indicated by residue zone keyed by color to HflX model in (D). (G) 30S of i70S_HflX-III. Superimposition of 30S of i70S_HflX-III with (H) 30S associated with P-site and (I) 30S associated with P/E hybrid tRNA. (J) is showing the steric clashes between the HflX and P-site tRNA, which are avoided by a slight intersubunit rotation.

NIHMS1955310-supplement-8.tif^{(15.8MB, tif)}

Table S1. Materials and parameters for the fabrication of the four chips used in this TR study, related to Figure 1.

Table S2. Absorbance values at 260 nm for the sample test using chips with different treatments, related to Figure 1.

Table S3. Model refinement statistics, related to Figures 3 and 4.

NIHMS1955310-supplement-9.pdf^{(317.5KB, pdf)}

Video S1. Spraying and plunging during the TR experiment, related to Figure 1.

Download video file^{(18.6MB, mov)}

Video S2. Clamshell-like splitting of the ribosome from Intermediate I over Intermediates II and III, ending with the 50S subunit (shown) and the 30S subunit (no longer associated; not shown), the end products of the recycling process, related to Figure 3.

Download video file^{(3.3MB, mp4)}

HIGHLIGHTS.

A PDMS-based microfluidic mixing-reacting-spraying method for time-resolved cryo-EM
Exposure-targeting for data collection from cryo-grids prepared by spraying droplets
Application of time-resolved cryo-EM to study HflX-mediated recycling of E. coli ribosome
Clamshell-like splitting of ribosome observed from three short-lived intermediate states

ACKNOWLEDGMENTS

This work was supported by a grant from the National Institutes of Health R35GM139453 (to J.F.). All data was collected at the Columbia University Cryo-Electron Microscopy Center (CEC). We thank Robert A. Grassucci, and Yen-Hong Kao for their help with the cryo-EM data collection. The microfluidic chips with ${S i O}_{2}$ coating were fabricated in Nanofabrication clean room facility in Columbia University.

INCLUSION AND DIVERSITY

We support inclusive, diverse, and equitable conduct of research.

Footnotes

DECLARATION OF INTERESTS

Columbia University has filed patent applications related to this work for which X.F. and J.F. are inventors.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

NIHMS1955310-supplement-1.tif^{(19MB, tif)}

NIHMS1955310-supplement-2.tif^{(20.3MB, tif)}

NIHMS1955310-supplement-3.tif^{(16.1MB, tif)}

NIHMS1955310-supplement-4.tif^{(15.8MB, tif)}

NIHMS1955310-supplement-5.tif^{(19.6MB, tif)}

NIHMS1955310-supplement-6.tif^{(18.8MB, tif)}

NIHMS1955310-supplement-7.tif^{(13MB, tif)}

NIHMS1955310-supplement-8.tif^{(15.8MB, tif)}

Table S1. Materials and parameters for the fabrication of the four chips used in this TR study, related to Figure 1.

Table S2. Absorbance values at 260 nm for the sample test using chips with different treatments, related to Figure 1.

Table S3. Model refinement statistics, related to Figures 3 and 4.

NIHMS1955310-supplement-9.pdf^{(317.5KB, pdf)}

Video S1. Spraying and plunging during the TR experiment, related to Figure 1.

Download video file^{(18.6MB, mov)}

Download video file^{(3.3MB, mp4)}

Data Availability Statement

The EM maps and corresponding atomic models are deposited on EMDB and PDB and will be publicly available as of the date of publication. Accession numbers are listed in the key resources table.
This paper does not report original code.
Any additional information required to reanalyze the data reported in this work paper is available from the lead contact upon request.

KEY RESOURCES TABLE.

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Bacterial and virus strains
E. coli BL21 Star^™(DE3)pLysS cells	Invitrogen	Cat# C602003
Chemicals, peptides, and recombinant proteins
Tris Base	Fisher Scientific	Cat# BP152–1
Magnesium acetate	Sigma-Aldrich	Cat# M5661
Ammonium chloride	Sigma-Aldrich	Cat# 09718
2-Mercaptoethanol	Sigma-Aldrich	Cat# M6250
Isopropyl β-D-1 -thiogalactopyranoside	Sigma-Aldrich	Cat# I5502
Sodium hydroxide	Sigma-Aldrich	Cat# S5881
Imidazole	Sigma-Aldrich	Cat# 288324
Sodium chloride	Thermo Scientific	Cat# 447302500
Sucrose	Sigma-Aldrich	Cat# S0389
GTP	Invitrogen	Cat# 18332015
Photoresist (SU-8 2075)	MicroChem	Y111074
Polydimethylsiloxane (PDMS)	Dow Corning	DCC000001477
n-Dodecyl β-D-maltoside (DDM)	Sigma-Aldrich	Cat# 69227–93-6
Dimethylsiloxane-(60–70% ethylene oxide) block copolymer, 20 cSt	Gelest	CAS# 27306–78-1
Deposited data
control apo-70S (without salt-wash) at 900ms	This paper	EMD-29681; PDB: 8G2U
i70SHflX-I	This paper	EMD-29688; PDB: 8G34
i70SHflX-II	This paper	EMD-29687; PDB: 8G31
i70SHflX-III	This paper	EMD-29689; PDB: 8G38
consensus i70SHflX-I, 30S focused	This paper	EMD-29833
i70SHflX-I, 50S focused and 30S subtracted	This paper	EMD-29834
consensus i70SHflX-II, 30S focused	This paper	EMD-29724
i70SHflX-II, 50S focused and 30S subtracted	This paper	EMD-29844
consensus i70SHflX-III, 30S focused	This paper	EMD-29723
i70SHflX-III, 50S focused and 30S subtracted	This paper	EMD-29842
Recombinant DNA
pET28a-HflX	This paper	Gift (from Peking University, China)
Software and algorithms
DomainMotionInertiaTensor	Maji, S. et al. ²⁹	https://github.com/suvraiitm/DomainMotionInertiaTensor
FreeCAD	Falck, et al. ⁵⁶	https://www.freecad.ora/
Gmsh	Geuzaine C. and Remacle JF. ⁵⁷	https://gmsh.info/
OpenFoam	Niels G. J. et al. ⁵⁸	https://openfoam.org/
MotionCor2	Zheng et al. ⁷¹	httos://emcore.ucsf.edu/ucsf-software
RELION	Scheres, S.H. ⁷²	https://www3.mrc-lmb.cam.ac.uk/relion//index.nhn/Main_Page
CryoSPARC	Punjani, A., et al. ⁷³	https://crvosnarc.com/
CTFFIND4	Rohou and Grigorieff ⁷⁴	https://ariaoriefflab.umassmed.edu/ctffind4
Topaz	Bepler, T. et al. ⁷⁵	http://cb.csail.mit.edu/cb/tonaz/
DeepEMhancer	Sanchez-Garcia, R. et al. ⁷⁶	https://aithub.com/rsanchezaarc/deepEMhancer
ResMap	Kucukelbir et al. ⁷⁸	http://resman.sourceforae.net/
PHENIX	Liebschner et al. ⁸³	https://www.phenix-online.org/
COOT	Emsley, P. and Cowtan, K. ⁸⁴	https://www2.mrc-lmb.cam.ac.uk/personal/pemslev/coot/
UCSF ChimeraX	Goddard et al. ⁸⁵	https://www.rbvi.ucsf.edu/chimerax/
Other
Ni Sepharose	GE Healthcare	Cat# 04003272-EE
Quantifoil R 0.6/1 holey carbon copper grid	TED PELLA, INC.	Cat# 657–300-CU
Amicon^® Ultra-4 Centrifugal Filter Unit	MilliporeSigma	Cat# UFC8010
Time-resolved apparatus	Dr. Howard White, Eastern Virginia Medical School	N/A
Capillary tubing	Polymicro Technologies	https://www.molex.com/en-us/products/part-detail/1068150018

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PERMALINK

Time resolution in cryo-EM using a PDMS-based microfluidic chip assembly and its application to the study of HflX-mediated ribosome recycling

Sayan Bhattacharjee

Xiangsong Feng

Suvrajit Maji

Prikshat Dadhwal

Zhening Zhang

Zuben P Brown

Joachim Frank

Abstract

IN BRIEF

Graphical Abstract

Introduction

Results

A microfluidic chip assembly for TRCEM

Figure 1. The modular PDMS-based microfluidic chip assembly for TRCEM sample preparation.

Exposure-targeting strategy in data collection for droplets-based cryo-grids

Figure 2. Data collection strategies on droplet-based cryo-grid prepared by mixing-spraying TRCEM method.

Time-resolved experiments on HflX-mediated ribosome recycling from 10 to 900 ms

Figure 3. Molecular details of subunit interface during the progressive opening of the 70S ribosome.

Intermediate states of HflX-mediated recycling and their interpretation

Figure 6. Axes of rotation of 30S subunit during splitting/recycling of the 70S ribosome:

Figure 4. Shift of uS12 toward HflX and involvement of HflX in splitting of 70S ribosome.

Dynamics of HflX and GTP hydrolysis-independent splitting

Time-dependent rupturing of intersubunit bridges

Figure 5. Fitting of GTP, spring-like nature of H34, and molecular events associated with HflX-mediated ribosome splitting.

Discussion

Further applications of time-resolved cryo-EM in the study of functional dynamics

Limitations of the Study

STAR★Methods

RESOURCE AVAILABILITY

Lead contact

Materials availability

Data and code availability

KEY RESOURCES TABLE.

EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

Bacterial cell culture

METHOD DETAILS

Protein purification

Isolation and purification of E. coli 70S ribosomes

Splitting assay

Co-sedimentation assay

The apparatus for Time-resolved (TR) cryo-EM sample preparation

High-efficiency SAR PDMS-based micromixer

SiO2-coating inside the micromixer for mitigating protein adsorption

Choice of microcapillary tubing as the reactor for stable reaction time control

Redesign of the microsprayer

Assembly and disassembly of the TR chip

Estimation of reaction time achieved using the TR method

Preparation of the time-resolved cryo-grids using the TR chip

Preparation of EM grids for control experiment for Apo-70S using the TR chip

TR cryo-EM data collection

Cryo-EM data processing

Determining the position vector of the unique point through which the rotation axis passes

Molecular Dynamics (MD) Simulation

QUANTIFICATION AND STATISTICAL ANALYSIS

Supplementary Material

HIGHLIGHTS.

ACKNOWLEDGMENTS

INCLUSION AND DIVERSITY

Footnotes

REFERENCES

Associated Data

Supplementary Materials

Data Availability Statement

KEY RESOURCES TABLE.

ACTIONS

PERMALINK

RESOURCES

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