Q) 2.97 Million based on FEA  simulation. The operating frequencies of these resonators are 188.55 MHz to 188.62 MHz. When the proposed SR (square rectangle) hole shaped one dimensional phononic crystal (1D PnC), and two dimensional phononic crystal (2D PnC) structure consist of very wide and complete band gaps is applied to novel design rings MEMS resonators, the quality factor (Q) further improved to 19.7 Million and 1750 Million, respectively, by using the finite element method. It is also observed that band gaps become closer by reducing the value of filling fraction, and proposed SR PnC gives extensive peak attenuation. Moreover, harmonic response of ring resonator is verified by the perfect match layers (PML) technique surrounded by resonators with varying width 1.5λ, and 3λ effectively reduce the vibration displacement.This paper presents a novel approach of annular concentric split rings microelectromechanical resonators with tether configuration to reduce anchor loss and gives very high-quality factor ( Nowadays, Micro-Electro-Mechanical-Systems (MEMS) components have been widely used in the field of engineering science, and technology because of their high efficiency, miniature in size, low power consumption, and low cost fabrication ,4,5,6,7.Q of microelectromechanical resonators. Several researchers ,14,15,16Q of the MEMS resonators has improved with phononic crystals extended to two dimension (2D). Many researcher employed phononic crystals with resonators’ body to improved quality of resonators, such as square shaped lattice PnC with hole employ with a resonator [To obtain the wide band gap, a lot of PnC structures have been designed ,23,24,25esonator  gives quesonator  gives thesonator  gives thThis work describes a design of novel SR (Square-Rectangle) hole shaped Phononic crystal, and this phononic crystal applied to novel annular concentric rings shaped Aluminium Nitride piezoelectric MEMS resonator. Q of resonator. In the end, we have investigated  displacement of resonator through FEA  simulation.At first, we have designed and simulated the unique silicon phononic crystal (PnC) structure of width 10 µm. we have also observed that reducing the value of filling fraction closer the band gaps. At second we have observed the band gaps generated by the 1D phononic crystal, and Eigen mode shapes of first 12 frequency bands. At third, we have observed the band gaps generated by the 2D phononic crystal, and Eigen mode shapes of first 12 frequency bands. At fourth, we have calculated transmission spectra through PnC for analyzing the band gaps, and leakage of energy. At fifth, we have designed and simulated the novel annular splits rings resonators with supporting tethers of width 4 µm to find the quality factor and investigated the displacement pattern and axes displacement of resonator, we have applied one dimensional phononic crystal (1D PnC) strips, and two dimensional phononic crystal (2D PnC) strips to annular splits rings resonators for further reduction of energy leakage and enhancement of the quality During the last few years, Phononic crystal (PnC) is being under discussion of researchers due to its potential application in the field of technologies ,29,30,31Phononic crystals can prevent energy leakage from resonators and control the elastic wave (acoustic wave) propagation inside the band ,36. It mk. The air SR shape means the holey square and holey rectangles in PnC unit cell. The geometrical dimension of unit cell is 18.6 µm × 18.6 µm with centered horizontal and centred vertical air rectangles 18 µm × 4 µm (rectangles hole) and centered air square of 9.2 µm (square hole) each side, as shown in The band gap in Phononic crystal (PnC) depends upon the properties of materials from which PnC made, density, and speed of sound in materials. Simply, we can say that band gap’s position with respect to frequency is the ratio of sound velocity to the size of periodic unit cell, and filling factor ,46. We hk parametric sweep fluctuates from 0 to 1. Where (0–1) indicate wave number of irreducible Brillouin zone (Γ–Χ). More generally, k swept from Γ to Χ (0 to π/a).We analyzed the above periodic unit cell to evaluate the frequency response for 1D phononic crystal. The k to its frequency as followsꞷ’ and ‘c’ are the angular frequency and wave velocity respectively.Moreover, the dispersion occurs when different wavelengths’ waves have different velocities of propagation. The dispersion relation associated with wave vector Particularly for phononic crystal the dispersion relation is complex and is represent by frequency band curves schematic as shown in It is worth mention that bandgap also depend upon the geometrical dimension, and inclusion filling factor in PnC by using the following relationAir is used as high acoustic impedance material, and Aluminum Nitride (AIN) is low acoustic impedance material. The filling fraction of this SR (square rectangles) hole PnC is 0.542.If the horizontal and vertical air rectangle is taken as 17 µm × 5 µm in size, and centered air square of 9 µm of each side, the band gap has reduced. We have observed that reducing the value of filling fraction closer the band gaps. The band gaps created into higher order modes due to smaller air inclusion area. The filling fractions and the band gap of phononic crystal obtained from different geometrical dimension, as shown in Table 1k parametric sweep fluctuates from 0 to 3. Where (0–1), (1–2), and (2–3) indicate wave number of irreducible Brillouin zone (Γ–Χ), (Χ–Μ), and (Μ–Γ) respectively. More generally k swept from Γ to Χ (0 to π/a), Χ to Μ (0 to π/a), and then Μ to Γ (π/a to 0).We have also analyzed the above periodic unit cell to evaluate the frequency response for 2D phononic crystal. In 2D PnC structure the ka/2π = 0.25 is shown in The red shaded, green shaded, and purple shaded area represents the deaf acoustic mode or deaf bandgap ,48, becaAs this PnC structure employed to resonator for further reduction of energy leakage, so we have calculated transmission spectra through PnC for analyzing the leakage of energy, because transmission of acoustic waves is forbidden in a bandgap. The transmission is defined as the ratio of transmitted waves to incident waves, and calculated as the difference of probe displacement and source displacement.y-direction and movement of Poisson coupling in x-, and z-directions. The x, y, and z excitations, as shown in As the phononic crystal is employed to resonator with supporting tether length 12 µm, and width 4 µm on both sides of resonator. The motion of resonator is in x and y excitation as well as for z excitation, and no dip in transmission as compared in band diagram of z excitation. Form We have calculated the transmission wave spectra through finite thickness of 10 µm Phononic crystals as shown in Annular concentric rings shaped Aluminum Nitride piezoelectric MEMS resonator is designed in this work, as shown in wT = 4 µm) without phononic crystal (PnC), and also with one dimensional phononic crystal (1D PnC), and two dimensional phononic crystal (2D PnC).The resonator is described with width of tether  are the first, and second kind of Bessel functions, and  are modified form of Bessel functions, R0, and iR are the outer and inner radius.λ = 2W, pE, ρ, and σ are width of resonator mode (wavelength), Young’s Modulus, Poisson’s ratio, and effective mass density of piezoelectric material, respectively. We have set the primary alignment of resonators structure to <110> frame of reference for silicon elasticity matrix [The Aluminum Nitride (AlN) as piezoelectric material is taken in ring shaped resonator, so the resonant frequency ,52 can by matrix  in  simulation. There are few energy loss mechanisms comprise the total Q-factor of the device [In this study we have also obtained high e device . Their lIn this study only anchor loss is considered (through FEA simulation), and the other losses are completely omitted. Due to nature of motion resonator it is not affected by air damping, and the material losses are difficult to predict, so the major loss is anchor loss ,55,56. TQ of proposed resonator without PnC, employed with 1D PnC, and with 2D PnC by the following summarized relation [We have analyzed the Quality relation ,61. sE and lE are the energy stored (vibration energy) and energy loss (energy dissipation per cycle of vibration) in resonator.λ’  (Qanchor is obtained by resonant frequency f0 over band width −3 dB [ꞷ’ is the desired mode’s eigen frequency of the resonator in FEA simulation.= 45 µm) . Elasticth −3 dB ,56,58 width approximately equal to 3λ, 3λ, respectively). These results show that Quality Q of resonator is the highest when 2D Phononic crystal structure is employed to resonators.Q further increased. Furthermore, band gap of designed PnC covers the operating frequency of designed resonators, and the design of this SR PnC will help to increase the quality of further designing of resonators in future.We see that, this unique design of resonators gives high quality, and when PnC is employed to resonator, the energy isolate from the resonator to substrate (reducing the loss of energy) as a result Q) 2.9 Million. These resonators were operating between the frequency 188.55 MHz and 188.62 MHz. In this works we have also proposed SR (square rectangle) hole shaped phononic crystal structure, which gives very wide and complete band gaps. When SR (square rectangle) shaped one dimensional phononic crystal (1D PnC), and two dimensional phononic crystal (2D PnC) is employed to novel design rings MEMS resonators the quality factor (Q) further improved to 19.7 Million and 1750 Million, respectively. We have concluded that value of filling fraction is reduced then band gaps become closer. It is observed that wider peak of attenuation makes broader desired operational frequencies of resonators.In this work, we have presented a new approach of annular concentric split rings microelectromechanical resonators with tether configuration to reduce anchor loss and gives very high-quality factor  technique surrounded to resonators with varying width 1.5


Inertial microfluidics utilizing passive hydrodynamic forces has been attracting significant attention in the field of precise microscale manipulation owing to its low cost, simplicity and high throughput. In this paper, we present a novel channel design with a series of reverse wavy channel structures for sheathless inertial particle focusing and cell sorting. A single wavy channel unit consists of four semicircular segments, which produce periodically reversed Dean secondary flow along the cross-section of the channel. The balance between the inertial lift force and the Dean drag force results in deterministic equilibrium focusing positions, which also depends on the size of the flow-through particles and cells. Six sizes of fluorescent microspheres  were used to study the size-dependent inertial focusing behavior. Our novel design with sharp-turning subunits could effectively focus particles as small as 3 μm, the average size of platelets, enabling the sorting of cancer cells from whole blood without the use of sheath flows. Utilizing an optimized channel design, we demonstrated the size-based sorting of MCF-7 breast cancer cells spiked in diluted whole blood samples without using sheath flows. A single sorting process was able to recover 89.72% of MCF-7 cells from the original mixture and enrich MCF-7 cells from an original purity of 5.3% to 68.9% with excellent cell viability. A technique for sorting tiny objects based on their size as they flow through narrow channels offers a simple system that could be used to separate cells and smaller bodies such as blood platelets. Separating different cells and other components of biological fluids is a vital aspect of medical research toward the development of new therapies. All existing methods have limitations, and improved techniques are eagerly sought. Ye Ai and colleagues at Singapore University of Technology and Design developed and tested a simple method based on the forces particles experience as they flow through channels with semi-circular sections linked in repeatedly reversing directions. The researchers demonstrated the general performance of their technique using fluorescent microspheres. They then successfully separated cancer cells from blood. The method could allow fast and efficient cell-sorting in many biomedical applications. However, the extensive utilization of active cell separation methods in practical applications is hampered owing to complicated device fabrication and integration and relatively low throughput, especially when the processing of a large sample volume, i.e., on the order of a few milliliter, is required to isolate extremely low-abundance biological particles. Passive cell sorting techniques mainly include size-based microfiltration15, deterministic lateral displacement (DLD)18 and inertial focusing. As far back as 1961, Segré and Silberberg19 first observed that particles would spontaneously form an annulus pattern along a cylindrical pipe in a laminar flow regime (tubular pinch effect), which arises from the balance between two opposing inertial lift forces. This lateral migration to deterministic equilibrium positions is known as the inertial focusing phenomenon. Inertial focusing has emerged as one of the most powerful and precise cell manipulation techniques in microfluidics since 200720 and has then gradually begun to attract great attention in the microfluidics research community because of its high throughput, low-energy consumption, simple device structure and friendly fabrication procedures23.Precise manipulation and separation of cells at the microscale are an essential technology for enabling biological studies and exhibit immense commercial potential in the bioengineering and pharmaceutical industries. In the past two decades, various microfluidic cell sorting technologies have been developed and can be classified as active and passive methods. Conventional active methods generally apply external acoustic27, curved/serpentine31, asymmetric curves33, spiral36 and contraction/expansion40, each of which exhibits different inertial focusing behavior21. Microfluidic channels with curvilinear or expansion-constriction features can produce a Dean secondary flow perpendicular to the main flow direction. The generation of the Dean flow results from the inertia mismatch of continuous flow in the center and near-wall regions, which is typically counter-rotating Dean vortices along the cross-section of the channel. The Dean secondary flow accordingly produces a Dean drag force that can be used to balance the inertial lift force and thus provides flexibility to control a particle’s equilibrium positions41. In particular, the Dean drag force and inertial lift force scale with the particle size very distinctively, which leads to distinct equilibrium positions of differently sized particles for particle sorting in continuous flows42. The secondary Dean flow also helps reduce the number of equilibrium positions, making sample collection more convenient.Inertial focusing is a passive microfluidic manipulation technology in which the size-selective manipulation highly depends on the channel geometry. Various channel geometries have been adopted to demonstrate inertial focusing, including straight43, size-dependent cell separation45, deformability-dependent cell separation46, rare cell separation47, bacteria isolation26, platelet separation29, plasma extraction48 and solution exchange49, among others. Notably, circulating tumor cells (CTCs) are malignant cancer cells shed from a primary tumor (or a tumor after metastasis) that undergo an epithelial–mesenchymal transition (EMT) and then intrude into the circulatory system. CTCs are considered a prerequisite of tumor metastasis, and the ability to capture and analyze CTCs enables the early diagnosis of cancer and systematic study of cancer metastasis. However, CTCs are extremely rare in the bloodstream ; therefore, to meet the demands of practical research and clinical use, CTC sorting technologies need to fulfill the requirements of high throughput, purity and capture rate. Since inertial focusing has the ability to process samples in a high-throughput manner, there has been an increasing interest in developing high-throughput inertial sorting or enrichment technology. For example, the spiral channel is a design that has been extensively studied and applied to inertial cell focusing and sorting, for example, rare cell isolation52 , specific cell type separation44 and single cell encapsulation53. Warkiani et al. achieved at least an 85% recovery rate of cancer cells spiked in lysed blood sample using a spiral inertial device combined with sheath flow54 and >80% recovery of cancer cells spiked in whole blood through a slanted spiral channel with sheath flow51. Sun et al. obtained an 88.5% recovery rate of cancer cells spiked into whole blood with a double spiral microchannel35.As a pluripotent microfluidic manipulation method, inertial focusing has been applied in multiple applications, such as sheathless alignment in flow cytometry56 and Li et al.57. Although multiple cross-section shapes, such as trapezoids44, circles, semicircles and triangles58, have been studied, we chose a classic rectangular cross-section design because of its simple fabrication process. The inertial focusing behavior of six fluorescent micron-sized particles  in three channel pattern designs was experimentally examined. It was found that the minimum particle size for effective inertial focusing is between 1 and 3 μm. On the basis of these experimental studies, we have identified an optimized channel design to fulfill our requirements of separating cancer cells from whole blood samples. To demonstrate the application potential of this novel device design, diluted whole blood samples spiked with breast cancer cells to mimic clinical CTC samples were used to test the sorting performance of our inertial microfluidic device. A single sorting process is able to recover ≥89% cancer cells and increase the purity of cancer cells by 13 times. Compared with previous inertial sorting devices, our novel design with extremely sharp-turning subunits can effectively focus cells as small as 3 μm and can thus effectively separate the three major blood cell types  from cancer cells without the use of sheath flows. In addition, the repeated wavy units are arrayed in a linear direction, which enables easier horizontal (2D) and vertical (3D) parallelization of multiple channels for handling large-volume samples.In this work, we present a novel geometric channel design, an asymmetric reverse wavy microchannel, for sheathless inertial particle focusing and cell sorting. The goal of using sheathless microfluidic devices is to minimize the use of fluid pumps, which inevitably cause increased power and buffer solution consumption, as well as to avoid the complicated procedure of sheath flow control. The advantages of sheathless microfluidics have been well demonstrated in previous studies involving the processing of viscoelastic solutions by Liu et al.Re > ~1), in addition to the viscous drag force exerted on the particle along the main flow direction, there are four types of inertial lift forces acting on the particle perpendicular to the main flow22: (i) the Magnus force due to particle slip-rotation; (ii) the Saffman force due to particle slip-shear; (iii) the shear gradient-induced lift force due to the curvature of the fluid velocity profile , and (iv) the wall-induced lift force due to interaction between the particle and wall . Among these forces, the Magnus force and Saffman force are typically much smaller than the other two lift forces and can usually be ignored in microfluidic sorting applications. The balance between the shear gradient- and wall-induced inertial lift forces results in the tubular pinch effect along a cylindrical pipe observed by Segré and Silberberg.19 According to Asmolov’s model59, the net inertial lift force consisting of the two major lift forces can be expressed as follows,When a solid particle is flowing along a bounded straight channel in an intermediate Reynolds number regime . The widths of the three outlet branches for all patterns are 80 μm, 45 μm and 80 μm, respectively. The diameter of the inlet and outlet reservoirs is 1.5 mm. Figure Figure The three different microchannels were fabricated using a standard polydimethylsiloxane (PDMS) soft-lithography process, in which the master molds for PDMS casting were fabricated with SU-8  on a silicon wafer. The PDMS microchannel layer and an ultrasonically cleaned glass slide were treated with air plasma  to generate hydroxyl functional groups on the surfaces. The treated surfaces were then brought into contact with each other to form a closed microchannel.www.comsol.com, USA). The model consists of three reverse wavy channel units with the same geometric dimensions and inlet flow rate as the experiments. The incompressible Navier-Stokes equation (Eq. c=40) was calculated, and the maximum Dean flow velocity was also obtained.A finite element method (FEM)-based numerical simulation was conducted using the laminar flow module with a steady-state study in COMSOL Multiphysics 5.0 .The MCF-7 breast cancer cell line was purchased from the American Type Culture Collection  and was cultured in Dulbecco’s modified Eagle’s medium (DMEM)  supplemented with 10% fetal bovine serum  to provide growth factors and antibiotics including penicillin and streptomycin  to prevent the growth of bacteria. The cells were subcultured every 2 to 3 days when the monolayer reached 80–90% confluence and maintained at 37 °C and 5% (v/v) CO6 particles per ml. A mixture of 15 μm, 10 μm and 3 μm particles suspended in DI water (with 0.6% F127) was used to demonstrate size-based particle sorting in continuous flow. Cancer cells (MCF-7) were stained with SYTO 9 fluorescent dye  and mixed with diluted whole blood . This cell mixture was used to demonstrate size-based sorting of MCF-7 cancer cells from blood cells using this wavy inertial focusing device.Fluorescent polystyrene microspheres  were purchased and used without any further modification . All these fluorescent polystyrene particles were diluted with deionized (DI) water containing 0.6% Pluronic F127  to avoid particle agglomeration and adhesion onto the channel wall. The typical particle concentration used in the following experiments was ~6×10c from 10 to 40) using a syringe pump. The trajectories of these fluorescent microparticles were recorded using a CCD camera on an inverted microscope  to capture the inertial focusing behavior. The motion of single cells in the trifurcated outlet was captured using a high-speed camera  to visualize the cell separation process. The cell contents in the samples before and after inertial sorting were analyzed by a commercial flow cytometer  to evaluate the sorting performance.Each individual experiment was conducted with a new microchannel device to avoid cross-contamination and possible clogging by residual particles or bubbles in the used devices. For each experiment, the prepared aqueous sample was continuously infused into the microchannel at flow rates from 49.41 μl/min to 197.60 μl/min (corresponding to Rec = 40). Figure c > ~1). In the middle region of the channel, the faster moving fluid along the main flow direction tends to move toward the outer wall along the cross-section direction. To conserve the fluid mass in the closed channel, the slower moving fluid near the top and bottom walls tends to move toward the inner wall, generating two symmetric counter-rotating vortices perpendicular to the main flow direction, which is called the Dean secondary flow.We first simulated the fluid flow in the three different channel designs and were in particular interested in the velocity profile along four cross-sections, A-D, as defined in Fig. R, the Dean secondary flow at cross-section B becomes much more pronounced than that at cross-section A. It is worth mentioning that from A to B, the outer wall is along the same channel side. From cross-section B to C, the fluid flows from the lower inner semicircle to the upper inner semicircle, undergoing the steepest flow turning. Although the two cross-sections have the same radius of curvature, the Dean secondary flow at cross-section C becomes even stronger than that at cross-section B. This result can be intuitively understood by considering that the variations in the radius of curvature from A to B and B to C are different, resulting in a considerable difference in the flow development at B and C. The maximum Dean flow velocities at the four cross-sections are listed in Table The first column in Fig. In contrast to channel pattern 1, patterns 2 and 3 introduce some degree of geometric asymmetry by increasing the radius of curvature of the lower outer semicircle with 100 and 200 μm, respectively. Generally, the Dean flows at cross-sections A, B, C and D show similar velocity profiles. Table c = 10, 20, 30 and 40, respectively. We first focused on the inertial focusing behavior in channel pattern 1 , the 15 and 10 μm particles revealed a tendency to focus along the centerline of the channel, whereas the 7, 5, and 3 μm particles tended to form two streaks near the two sidewalls of the channel. The smallest 1 μm particles showed no tendency to undergo inertial focusing. In the downstream . Another important parameter for evaluating the role of inertial lift force and Dean drag force is Rf = 0.354. In the following experiments, all the Rf values for the different particles were calculated using the radius of curvature along the outer wall of the inner semicircles (R = 175 μm). Rf = 0.354>0.08 implies that the inertial lift force dominates over the Dean drag force; as a result, the equilibrium focusing position of the 15 μm particles remained nearly along the centerline, similar to the inertial focusing along a straight channel with AR =  c = 10 and 20, the 15 μm microspheres eventually flowed into the middle outlet as expected. However, at Rec = 30 and 40, the focused 15 μm microspheres flowed into the upper outlet, indicating that their equilibrium focusing position was slightly shifted toward the upper outlet. We speculate that the Dean drag force increased faster than the inertial lift force for the 15 μm microspheres as the flow rate increased. Although the Dean drag force was weaker than the inertial lift force, it would mildly shift the particle equilibrium focusing position away from the centerline.We next investigated the inertial focusing behavior of differently sized microspheres  in the three different channel designs. These microspheres are fluorescent, which allowed us to clearly visualize the particle trajectories even at very high flow rates. Figures n 1 Fig. . In the n 1 Fig. , the sixn 1 Fig. , where ta/H = 0.165 > 0.07, Rf = 0.157>0.08) also focused into a single streak, with the inertial lift force dominating the focusing behavior. Additionally, the relatively weaker Dean drag force also shifted their equilibrium focusing position upward, and thus, the 10 μm microspheres flowed into the upper outlet. The inertial focusing behavior of the 7 μm microspheres, however, varied with the flow rates. a/H = 0.115 > 0.07 implies that they could be effectively focused. Rf = 0.077 is very close to the empirical value 0.08, indicating that the inertial lift force became comparable to the Dean drag force for the 7 μm microspheres. At Rec = 10 and 20, the 7 μm microspheres were focused into two streaks near the sidewalls, where the Dean drag force slightly dominated the inertial lift force. Since the Dean secondary flow periodically reversed along the repeated wavy channel units, the Dean drag force tended to drag particles toward the two sidewalls. The balance between the Dean drag force and the inertial lift force, particularly the wall-induced lift force, led to equilibrium positions near the sidewalls. However, at Rec = 30 and 40, the 7 μm microspheres were focused into a single streak shifted away from the centerline, revealing that the inertial lift force slightly dominated the Dean drag force. We speculate that 7 μm is at or very close to the threshold size at which the inertial lift force and Dean drag force became equally important. As the two forces varied with the flow rates in slightly different degree, the focusing behavior of the 7 μm microspheres could be readily switched between single streak focusing (shifted from the centerline) and double streak focusing . The two important parameters for the 5 μm microspheres are a/H = 0.083 > 0.07 and Rf =  0.039 < 0.08. Therefore, the 5 μm microspheres were predominantly affected by the Dean drag force and thus formed two streaks near the two sidewalls. For the 3 μm microspheres, although a/H = 0.049 < 0.07 (Rf = 0.014 < 0.08), they were still effectively focused into two streaks near the sidewalls. Note that this empirical parameter a/H = 0.07 for effective inertial focusing was obtained from a different channel design; thus, this threshold value may slightly deviate from 0.07 for different channel designs. For the 1 μm microspheres, the two important parameters are a/H = 0.016 < 0.07 and Rf = 0.002 < 0.08; therefore, they could evidently not achieve clear inertial focusing.The 10 μm microspheres . Figure c values. For the 7 μm particles, they switched from double streak focusing (Rec = 10 and 20) to single streak focusing (Rec = 30 and 40) in pattern 1, as discussed previously. As the Dean secondary flow was weakened in pattern 2 and 3, the 7 μm particles were not very effectively focused at Rec = 10 and 20. However, they exhibited single streak focusing at Rec = 30 and 40 in patterns 2 and 3. The focusing streak of the 7 μm particles in the three patterns at Rec = 30 and 40 were nearly identical, occupying 99.8–107.8 μm along the cross-section. The other three particles  behaved very similarly in the three channel patterns. The 5 μm particles displayed double streak focusing when Rec ≥ 20, occupying 101.8–108.8 μm (upper streak) and 21.2–29.3 μm (lower streak) of the cross-section. Similarly, the 3 μm particles exhibited double streak focusing when Rec ≥ 20, occupying 94.8–108.8 μm (upper streak) and 22–30.8 μm (lower streak). The 1 μm particles could not be effectively focused in any of the three channel patterns.Figures c = 40) was chosen for all the subsequent sorting experiments. Figure With knowledge of the inertial focusing behavior of individual particles with varying sizes in the three different patterns, we finally chose channel pattern 3 to demonstrate the sorting of a mixture of particles with multiple sizes. To achieve high throughput, a flow rate of 197.60 μl/min (Rec = 40) was used in order to achieve high throughput. According to the study of the inertial focusing of individual particles in Fig. We then used the pattern 3 inertial sorting device to separate breast cancer cells spiked in diluted whole blood samples in order to prove its potential clinical application in rare cell sorting. The whole blood sample was diluted 100 times using cell-free PBS buffer with a final concentration of 50 million cells per ml. The mixed cell samples, which contained ~5% fluorescently stained breast cancer cells , were evaluated based on the fluorescence signal in flow cytometric analyses. The rest of the cell populations in the cell mixture were mainly red blood cells , platelets (diameters of ~3  μm) and white blood cells . Figure The expected collection of different cell populations at the trifurcated outlets was verified through the sorting experiments presented in Fig. The original cell mixture and sorted samples collected from the three outputs were analyzed using a flow cytometer by counting at least 10,000 cells. Figures After a single sorting process, 89.72% MCF-7 cells could be recovered from the original input sample, as shown in Fig. 57 or other kinds of additional forces to facilitate particle focusing. Using the channel pattern 3 device, we demonstrated the separation of 15 μm particles from 10 and 3 μm particles. As the minimum particle size for effective inertial focusing is between 1 and 3 μm in channel pattern 3, we also demonstrated the separation of MCF-7 cancer cells from diluted whole blood samples without the use of sheath flows. We have found that a single sorting process was able to achieve an 89.72% recovery rate of MCF-7 cells from the original mixture and that the purity of MCF-7 cells was significantly increased from 5.3% to 68.9%. Sorted MCF-7 cells showed excellent viability and were able to proliferate. The linear array of these repeated wavy channel units enables easy horizontal (2D) and vertical (3D) parallelization of multiple channels, which provides great potential for high-throughput cell sorting in practical biomedical applications.In summary, we presented a new inertial focusing and sorting device with a series of reverse wavy channel structures that generate periodically reversed Dean secondary flow perpendicular to the main flow direction. The balance between two inertial effects, the inertial lift force and Dean secondary flow, produces size-dependent particle focusing across the channel. We experimentally studied the inertial focusing behavior of six particle sizes  in three channel designs with different degrees of geometric asymmetry. It was found that when the inertial lift force dominated the Dean drag force for 15 and 10 μm particles, they exhibit single streak focusing. However, the different degree of force dominance for the 15 and 10 μm particles still resulted in distinct particle focusing positions. As the particle size shrunk, the two forces became comparable for 7 μm particles, which could switch from single streak focusing to double streak focusing at varying flow rates. When the Dean drag force dominated the inertial lift force for 5 and 3 μm particles, they were focused into two tight streaks near the two sidewalls. To achieve effective inertial focusing of even smaller particles (~1 μm), feasible methods include shrinking the dimensions of the channel cross-section and introducing viscoelastic forceS1_video1S1_video2S1_video3


Synthetic gene oscillators have the potential to control timed functions and periodic gene expression in engineered cells. Such oscillators have been refined in bacteria in vitro, however, these systems have lacked the robustness and precision necessary for applications in complex in vivo environments, such as the mammalian gut. Here, we demonstrate the implementation of a synthetic oscillator capable of keeping robust time in the mouse gut over periods of days. The oscillations provide a marker of bacterial growth at a single-cell level enabling quantification of bacterial dynamics in response to inflammation and underlying variations in the gut microbiota. Our work directly detects increased bacterial growth heterogeneity during disease and differences between spatial niches in the gut, demonstrating the deployment of a precise engineered genetic oscillator in real-life settings. Synthetic gene oscillators can be used to control timed function and periodic expression of genes. Here the authors demonstrate in vivo implementation in the mammalian gut that can keep time over several days. Synthetic gene oscillators in bacterial cells have been developed and refined over past decades12, led by the development of the repressilator circuit—a simple negative feedback loop constructed from three transcriptional repressor proteins, which inhibit each other’s expression in turn 3. Engineered bacteria hold great promise for deployment as diagnostics and therapeutics in the clinic13. Oscillatory gene control could enable increasingly complex applications for engineered bacteria, for example controlling time-linked functionality or sophisticated recorders and counters.Oscillators are extensively utilized as clocks and timers in computation and biology14. Recently, several methods have been developed to estimate instantaneous, average bacterial growth rates using metagenomic sequencing data18. These methods have provided insights into spatial and temporal changes in comparative growth rate20. However, single-cell methods offer different advantages, in particular providing valuable information about growth variability across a population29. Such information is crucial to our understanding of bacterial growth in the gut, which includes a broad range of niches with different growth favorability for any given bacterial species, potentially limiting the interpretation of average growth measures. Similarly, methods that can quantify absolute, rather than relative, growth and that assess growth in aggregate30, rather than as instantaneous rates, are particularly important for developing a comprehensive understanding of growth in a non-invasive manner.Differential bacterial growth underlies colonization of the gut by commensal species during childhood, pathogenic infection, and the establishment of dysbiosis in the microbiota that has been linked to an increasing array of diseases5. During in vitro growth the circuit keeps phase in single cells for hundreds of bacterial generations, with an oscillation period that is growth-rate independent and linked to bacterial divisions5. The circuit’s low variance between cells, and independence from external feedback and entrainment cues make it an attractive timer for use in complex environments.The original repressilator was recently redesigned to afford a highly regular and robust oscillator with reduced error propagation and information losses, referred to herein as the repressilator 2.0 Fig. 5. DuringHere, we use the repressilator 2.0 to infer bacterial growth dynamics at a single-cell level. We develop and validate an imaging analysis pipeline to determine repressilator phase. In this way, we investigate bacterial population dynamics during colonization of, and growth within, the mammalian gut. Our results show increased growth variability under inflamed conditions, demonstrating the importance of single-cell methods for reliable bacterial growth analysis. We also reveal robust functionality and controllability of the repressilator 2.0 across diverse host and environmental contexts.31, synchronous repressilator 2.0 oscillations create stable macroscopic rings when fluorescent reporters are driven under repressilator 2.0 control  of the fluorescent rings in a colony are indicative of the phase of the bacterium that seeded the colony  . Because repressilator 2.0 progression is linked to bacterial growth5, the elapsed phase between two timepoints can be used to infer bacterial growth. Given the periodic nature of the oscillator, meaning that the circuit’s output is the same in any given period , adjusting the sampling frequency to ensure that less than a period elapses between timepoints allows unambiguous determination of growth.To utilize this behavior, we developed a workflow for bacterial colony image capture and processing, which we call GS) Fig. . The proE.coli LPT239 bacteria expressing the repressilator 2.0  and Salmonella enterica serovar Typhimurium (hereafter referred to as S. Typhimurium) (LT2-PAS716) strains    Fig. ; Table 1od) Fig. .Fig. 2RIPAS715 period length remained unperturbed during growth on extracted mouse cecum contents, used to simulate aspects of the gut environment    -treated animals as a model for inflammation, which promotes increased growth of e39 Fig. . Bacterie39 Fig. , as demo 4) Fig. . These r 4) Fig. . DSS (4% 4) Fig.  and reprInterestingly, despite all DSS-treated mice showing equivalent severity of inflammation, as measured by lipocalin 2 (LCN-2) levels Fig. , PAS715 Here we describe the activity of a synthetic gene oscillator, the repressilator 2.0, in the complex environs of the mammalian gut. We develop an image processing and analysis pipeline, RINGS, to follow repressilator activity on a single-cell level and thereby also understand growth dynamics at various stages of the colonization process. We demonstrate robust repressilator 2.0 functionality, control and circuit stability within the mouse gut over the course of several days. Using this method we detect increased growth variability under inflammatory conditions and between spatial niches within the gutThe repressilator 2.0 is ideally suited to periodic expression control within engineered bacteria for use in complex settings. The circuit’s independence from external signals allows for circuit function in a variety of environments, which is of particular utility in the gut where relative abundance of strains can vary widely on spatial and temporal scales, and between individuals. To this end, the ability to re-synchronize the repressilator 2.0 in situ within the gut, and its stability over extended periods of growth without antibiotic selection are particularly exciting.30, and fluorescent protein dilution which is capable of estimating up to ~10 divisions of single-cell growth21. Our analyses estimated E. coli MG1655 division times progressively increasing from ~35 min, when colonizing the recently streptomycin-treated gut, to ~20 h when more removed from the perturbation of the single dose of streptomycin and thus reflecting more physiological growth conditions. By comparison, a recent study used the accumulation of mutations in the E. coli genome to estimate a division time in humans of 15 h40.The RINGS method informs us of the integrated growth experience of a bacterium and its forebears. The repressilator 2.0’s periodicity allows for extend growth measurement in comparison to other comparable techniques, recent examples of which include a synthetic particle which allows mark-and-recapture analysis over ~14 generationsTogether, our results suggest that the aggregate bacterial experience is relatively consistent under most scenarios tested, with spatial dissection suggesting that the majority of growth in these mouse colonization models is occurring ‘upstream’ in the small intestine and/or cecum. We see that in most cases fecal sampling accurately reflected the overall growth profile of the mouse colon, including bacteria in the lumen and mucus layers, and within the cecum. The absence of colonies in fecal samples reflecting the differential growth observed in the ileum of the dissected DSS-treated mouse suggests that, in this case at least, the bacteria from the ileum either were not represented in feces or represent a small enough percentage of the population so as to remain below detection in our final analyses from this mouse.Overall, we determine that single-cell measurements are particularly important in disease conditions, such as inflammation, when variability of growth between niches is accentuated. In these cases methods that can only measure a population-wide average would not adequately represent the population’s diversity. The ability to increase the sampling frequency used would also allow this method to measure the emergence of subpopulations of differentially growing bacteria in finer detail.In sum, analysis of the repressilator at single-cell level can report on complex bacterial growth behaviors over time, and in particular, during disease conditions within the mammalian gut. In doing so, this work demonstrates the potential for one of the circuits that first stimulated the field of synthetic biology to revolutionize how we control gene expression within the gut.Details of strains —and triple fluorescent reporters—PR-mKate2 (including the first 11 amino acids of mCherry for improved translation efficiency as previously published5), PLtetO1–mVenus, PLlacO1–mSCFP3 (pLPT107)5. Previously published sponge plasmid variants5 were used as available from Addgene plasmid repository (see Data Availability Statement). Plasmids were isolated by miniprep (Qiagen) and were routinely transferred to new strains as a mixture by electroporation.The repressilator 2.0 plasmid variant with three fluorescent reporters (pLPT234) was constructed by isothermal assemblylacI and motA genes were knocked out of E. coli strains used before repressilator plasmids were transferred. For both genes, FRT-flanked gene disruption constructs were transferred by P1vir transduction42 from the relevant Keio collection strains43. Kanamycin resistance genes were then removed by electroporation and subsequent curing at 43 °C of pCP2044. Similarly, streptomycin resistance based on a rpsL lys42arg mutation was transferred by P1vir from a previously generated E. coli MG1655 strain35. Resistance to streptomycin was evolved in S. Typhimurium LT2 by serial passage in liquid culture with increasing concentrations of streptomycin sulfate (Sigma) . For PAS718, mKate2 (including the first 11 amino acids of mCherry for improved translation efficiency as previously published5) driven under the PRNA1 constitutive promoter was inserted into the genome using a Tn7 transposon45, and acted as a constitutive fluorescent marker for cell segmentation in mother-machine experiments.To avoid interruption of the repressilator and ensure clear ring development within colonies, Bacteria were routinely cultured in Luria broth (LB) supplemented with 300 μg/mL streptomycin (Sigma), 100μg/mL carbenicillin or ampicillin (Sigma) and 50μg/mL kanamycin (Sigma). For plating, bacteria were grown on selective LB agar plates supplemented with 100μg/mL carbenicillin (Sigma) and 50μg/mL kanamycin (Sigma). The plasmid retention test compared growth on streptomycin  to streptomycin+carbenicillin (retention of repressilator plasmid), streptomycin+kanamycin (retention of sponge plasmid), and streptomycin+carbenicillin+kanamycin (retention of both plasmids) at drug concentrations as above.To synchronize the phase of the repressilator across the population, bacteria were grown overnight in the presence of 1 mM Isopropyl β-D-1-thiogalactopyranoside (IPTG) (Sigma) or 100 nm anhydrotetracycline (aTc) (Sigma). Bacteria were back-diluted in fresh inducer-supplemented media by at least 1:20 to allow resumption of active growth in the presence of inducer, before being washed and utilized for downstream experiments.46. Images were taken at an aperture of f/2.8 and ISO200. Exposure times were typically between 0.05 and 2 s as experimentally determined to maximize dynamic range.Fluorescent and white light images of colonies were imaged using a custom-software controlled Canon T3i digital single lens reflex (DSLR) camera with a Canon EF-S 60 mm USM lens, combined with LEDs and filters for excitation and a Starlight express emission filter wheel A and B are the amplitude and offset of a sinusoidal oscillator, and the function, f(r), represents the radial phase profile of the colony. The form of f(r) is derived below using a simple model for the growth of the colonies.We extract the relative phase offset of each colony by fitting a generative model to the pattern of oscillations. This approach has the benefit of making use of all the information captured in the multi-channel images. We explored a family of generative models, based on the simple form:f(r), is related to the profile of generation number, g(r), as follows:T is the period of the oscillator in generations (≈ 15.5) and θ0 is the instantaneous phase of the oscillator at the time of plating. Thus, we derive the profile of generation number with respect to radius. We assume that growth is initially exponential, and then becomes restricted to an annulus with thickness D (≈30 μm at the edge of the colony40).The phase profile, Ab is the area of a single bacteriumAssuming uniform packing of bacteria in the colony (for both phases of growth), the generation number profile during exponential growth can be derived simply:Here we model the growth of the colony with each successive generation. With each generation the radius of the colony increases as follows:go is the generation number at the transition between the exponential and annular growth.Integrating this over the colony, we obtain the following expression for the generation number profile:r = D, with D = 30 μm. Notice that beyond r ≈ 100 μm the phase profile is approximately linear, and can be described by:Combining the two growth models yields a continuous growth curve . Colonies were identified by autothresholding (Yen method) of binarized CFP images. Separate YFP and CFP images were cropped and exported, centered on the YFP center of mass of each identified colony. Prior to final analyses, colony images from plates containing >130 bacterial colonies were excluded based on overcrowding leading to limited colony growth. Remaining colonies were visually inspected, and any doublet or severely malformed colonies were removed from the datasets to avoid spurious fitting. Colony removal was performed blinded to θ0 fit values. Where presented, average projections were taken through YFP images from all colonies identified in a given population.Centered colonies were cropped from whole-plate images using FIJIrmax = 1.3 mm  and the radial intensity profile was fit to a second order polynomial. This smooth polynomial decay, chosen as an even order with negative coefficient to ensure this process did not remove the oscillatory pattern, was then used to normalize the raw image in a pixel-wise fashion , the distance between each ring and therefore expected slope of the phase profile (‘expectedSlope’), the variation in slope between colonies (‘slopeTol’), and the offset between CFP and YFP rings (‘colorPhaseShift’). The method was found to be largely insensitive to specific parameter values with strain-specific optimal values likely caused by differences in oscillator and spatial colony growth characteristics. Optimal parameters for each strain in the study were determined to be as follows: .49.Statistical analyses were performed in MATLAB versions R2017a-2018a (Mathworks) or Prism v6-7 (Graphpad). Circular statistical tests, specifically circular mean and angular deviation, were performed using the CircStat for Matlab toolbox v2012aθ0 values are transformed to a resultant mean vector . We deemed this appropriate where the population remained relatively coherent around the circular mean—which we defined as having an angular deviation <1.2. Empirically, datasets with angular distribution >1.2 were routinely decoherent, were not accurately described by the circular mean , or contained considerable fractions of the population in regions neighboring the mean ± π divide, which reduced our confidence of accurately classifying these cells as being slower or faster growing  were normalized to the circular mean of the initial synchronized repressilator 2.0 population for that experiment, αsync. Elapsed phase was then calculated by addition/subtraction of multiples of 2π based upon the circular mean of a timepoint. When αn > αn-1 i.e., when growth had occurred but not, on average, passed the 2π/0 point, the adjustment factor remained unchanged. However, when αn < αn-1, i.e., growth on average passed the 2π/0 divide within the elapsed timepoint, an adjustment factor of 2π was made to each subsequent timepoint. When this method was applied to in vivo datasets, where sampling variability combined with slow growth rates could lead to spurious negative shifts, we further assumed that average growth rates would not exceed 2.5 generation per hour when interpreting if a population had grown through a full period. Individual θ0 values were then adjusted by addition of the calculated multiples of 2π. For adjustments, where θ0 = α − π to 0 were assumed to be one phase revolution  behind of those of 0 to α + π. Where α > π, colonies with θ0 = 0 to α − π were assumed to be one phase revolution ahead of values α − π to 0. Subsequent calculations treated the adjusted θ0 values as linear datasets.For elapsed phase calculations, individual phase values (tsync) on a single-cell basis. Because adjusted θ0 values had already been normalized to αsync = 0 and adjusted for multiple periods of growth where necessary, the mean estimated growth, μ, for each individual colony in the population, i, is described by:strain is the calculated mean periodicity of the relevant strain in generations/period.To calculate growth on a single-cell level we treated each colony separately, determining the distribution of probability for the generations of growth since the reference timepoint  were assumed to be normally distributed, which was appropriate based on visual inspection of Q–Q plots. Thus, the growth probability of each colony, i, is described by a normal distribution with error,σ:The distribution of probable growth can then be determined by a combination of the phase distribution of the population at tAn empirical probability density function and cumulative distribution function was then calculated as the sum of all individual distributions.Interpretations of growth data are informed by physiological limits. For example, we can assume that growth will not exceed known growth rates for a given species, and the repressilator can only progress in one direction based on growth. Of the possible outcomes, we report the most consistent growth trajectory across timepoints. An example of how these constraints are applied to a dataset is provided  mice of 8–14 weeks, (including >2 weeks acclimatization to the HMS mouse facility), were used in groups of 2–3 per experiment. Mice were routinely randomized between treatment groups in advance of experiments, where relevant. Mice were fed on a lactose-free chow  for at least 1 week prior to provision of repressilator bacteria to avoid any interruption of the repressilator by lactose. Streptomycin-treated mice were administered 5 mg USP-grade streptomycin sulfate (Gold Biotechnology) in 100 μL sterile PBS by oral gavage, or where specifically stated 0.5 g/L in drinking water supplemented with 5% sucrose overnight. PAS715 In situ synchronization was achieved by provision of USP-grade 10 mM IPTG (Sigma) or 0.1 mg/mL aTc (Sigma) in drinking water supplemented with 5% sucrose overnight.g for 20 min . The supernatant was then serially diluted and cultured on selective agar plates.Fresh fecal samples were collected by temporarily removing mice to small containers until at least 2–3 fecal pellets were produced. Fecal pellets were homogenized in PBS at 50 or 100 mg/mL in sterile PBS by vortexing for ~5 min in 1.5 mL Eppendorf tubes. To remove large debris, homogenized feces was then centrifuged either by briefly pulsing (~1 sec) on a benchtop minifuge , or by centrifugation at 4 × For inflammation experiments, mice were fed Dextran Sulfate Sodium  in drinking water supplemented with 5% sucrose for 3 days prior to bacterial administration. DSS water was exchanged every second day, and mice remained exposed throughout the course of the experiment.50 were quantified as previously36 using a Mouse lipocalin-2/NGAL DuoSet ELISA kit (R&D Systems). Fecal pellets were vortexed at 100 mg/mL in PBS+0.1% Tween20 for 20 min, then pelleted at 12,000 × g for 10 min at 4 °C. ELISA results were obtained on a BioTek Synergy H1 plate reader. Four hundred fifty nanometer absorbance corrected values were interpolated from a sigmoidal four parameter logistic standard curve using Prism 7 for Mac OSX software (GraphPad).LCN-2 biomarker levels15. Genomic DNA was extracted from flash-frozen fecal samples using a Qiagen DNEasy Blood & Tissue Kit. Genomic DNA from each sample was prepared for sequencing using a Kapa HyperPlus Kit and sequenced using an Illumina NextSeq at the Bauer Core Facility at Harvard University. Sequencing reads were trimmed for quality using Trimmomatic 0.3651 and each sample was aligned to the genome of interest using BWA mem 0.7.852. Sequencing coverage was obtained using bedtools 2.27.153. To calculate peak-to-trough ratio, mean coverage was computed for 10 kb bins across the genome and a segmented linear model was fit to the coverage using the R package segmented54.Peak-to-trough ratios were computed from metagenomic sequencing of mouse fecal samples as previously describedg) to remove large particulate matter and the supernatant removed and saved. Cecum matter was then washed a second time, centrifuged, and the supernatant pooled with the first wash. Pooled supernatant was centrifuged a second time, then passed sequentially through a 20 μm syringe filter (Millex-AP glass fiber 25 mm syringe filter) and then a 5 μm syringe filter . The filtered fluid was then used as an input for the mother machine.We performed time-lapse single-cell measurements to monitor and compare the dynamics of repressilator circuits in rich defined medium  and in cecum contents. Cecum contents were derived from fresh or frozen mouse cecum, diluted in PBS. 2–4 FVB (Charles River) or C57/Bl6 (Jackson) mice were sacrificed, their cecum dissected, and the cecum contents were extracted by scraping and washing off the tissue with PBS. When frozen, cecum contents were placed at −80 °C. The contents were then thawed, if necessary, and diluted in PBS, spun briefly in a benchtop centrifuge . To flow the cecum through the device, we used a mother-machine design where the dimensions of the flow channel has been optimized for flowing dense cultures and maintaining low pressure to allow low fluid flow-rates . Device fabrication used a wafer prepared using standard UV photolithography, with quartz-chrome photomasks (Toppan Inc) in a clean-room environment. Devices consisted of three independent layers: a Su8 ‘base’ coat, a featureless uniform layer of completely cured Su8; cell channels  placed in the orthogonal direction to the flow channels; and medium flow channels, of 150 μm width and 45 μm height.The filtered fluid from the cecum contents was loaded in 10 mL syringes and pumped through mother-machine devices2 pressure at 170 mTorr). Chips were incubated at 95 °C, >30 min to reinforce bonding before being cooled to room-temperature.The devices were constructed from the wafer using soft lithographic techniques in clean-room . Dimethyl siloxane monomer (Sylgard 184) was mixed with curing agent (10:1 ratio), defoamed, poured onto the silicon wafer, degassed (1 h) and cured at 65°C (1 h). Individual chips were cut and the inlets and outlets punched with a biopsy puncher. On the day of experiments, bonding to KOH-cleaned cover slips was done using oxygen plasma treatment  to ensure we could observe the dynamics of the cells for prolonged periods (>10 h) with the small volume of cecum contents (~3–5 mL). This ensured that we observed at least two peaks for repressilator signals in individual channels (YFP or CFP) for a majority of the cells, which is necessary to calculate the period of oscillation. To minimize phototoxicity the frequency of imaging was kept at 6 min/frame. This gives about 4–5 snapshots per generation time, which is enough to get a good estimate of growth rate and also a smooth intensity time-series. For E. coli PAS715 experiments imaging occurred at 10 min/frame.Cell channels were loaded with E. coli containing the repressilator circuit. In some experiments Images were acquired using a Nikon Ti inverted microscope equipped with a temperature-controlled incubator (OKO lab), a sCMOS camera (ANDOR), a 40X Plan Apo air objective , an automated xy-stage (Nikon) and light engine LED excitation source (Lumencor SpectraX). All experiments were performed at 37 °C. Microscope control was done with Nikon Elements software. We acquired time-lapse data from 40 fields of view, which allows us to track approximately 2000 cells simultaneously. The acquired data were analyzed using a hybrid analysis platform written in the Paulsson lab. In brief, images were segmented using a custom-designed FIJI plugin and then the extracted data were further processed to track cells in a custom-designed MATLAB script. Time-series of cell-size data calculated from the segmented images was used to compute generation times. The time-series of YFP channel intensity was used to calculate the period of repressilator in the cecum content.55.Figures were generated through Adobe Illustrator CC2018 and CC2019, Adobe InDesign CC2018 and CC2019, Prism v6-7 (Graphpad), and MATLAB versions R2017a-2018a (Mathworks). Many figures utilize color palettes based on research by Cynthia BrewerSupplementary InformationPeer Review FileSource Data


Messenger RNA (mRNA) has broad potential for application in biological systems. However, one fundamental limitation to its use is its relatively short half-life in biological systems. Here we develop exogenous circular RNA (circRNA) to extend the duration of protein expression from full-length RNA messages. First, we engineer a self-splicing intron to efficiently circularize a wide range of RNAs up to 5 kb in length in vitro by rationally designing ubiquitous accessory sequences that aid in splicing. We maximize translation of functional protein from these circRNAs in eukaryotic cells, and we find that engineered circRNA purified by high performance liquid chromatography displays exceptional protein production qualities in terms of both quantity of protein produced and stability of production. This study pioneers the use of exogenous circRNA for robust and stable protein expression in eukaryotic cells and demonstrates that circRNA is a promising alternative to linear mRNA. Circular RNAs have recently been shown to have protein-coding potential. Here the authors design a self-splicing RNA that, when circularized, provides for stable high-yield protein production. Most circRNAs found in nature are generated through backsplicing4 and appear to fulfill noncoding roles6. However, it has been demonstrated that some circRNAs endogenous to Drosophila and humans encode proteins8. In addition to having protein-coding potential, endogenous circRNAs lack the free ends necessary for exonuclease-mediated degradation, rendering them resistant to several mechanisms of RNA turnover and granting them extended lifespans as compared to their linear mRNA counterparts9. For this reason, circularization may allow for the stabilization of mRNAs that generally suffer from short half lives11 and may therefore improve the overall efficacy of exogenous mRNA in a variety of applications12.Circular RNAs (circRNAs) endogenous to eukaryotic cells have drawn increasing interest due to their prevalence and range of potential biological functions16, and thus alternative approaches to RNA stabilization, such as circularization, are desirable. However, the efficient circularization of long in vitro transcribed (IVT) RNA, the purification of circRNA, and the adequate expression of protein from circRNA are significant obstacles that must be overcome before their protein-coding potential can be realized. In this study, we present an engineering approach to generating exogenous circRNAs for potent and durable protein expression in eukaryotic cells.Previous efforts to increase mRNA stability include the use of untranslated regions such as those present in the native beta globin mRNA, methylguanosine cap analogs to protect mRNA from decapping enzymes, nucleoside modification, and codon optimization. These strategies have yielded modest improvements in RNA stability19. A ribozymatic method utilizing a permuted group I catalytic intron has been reported to be more applicable to long RNA circularization and requires only the addition of GTP and Mg2+ as cofactors17. This permuted intron-exon (PIE) splicing strategy consists of fused partial exons flanked by half-intron sequences20. In vitro, these constructs undergo the double transesterification reactions characteristic of group I catalytic introns, but because the exons are already fused they are excised as covalently 5′ to 3′ linked circles17  or 19 (strong) nucleotides in length placed at the 5′ and 3′ ends of the precursor RNA with the aim of bringing the 5′ and 3′ splice sites into proximity of one another  to be unstructured and non-homologous to the proximal intron and IRES sequences; (2) to separate intron and IRES secondary structures so that each element is able to fold and function independently of one another; and (3) to contain a region of spacer–spacer complementarity to promote the formation of a sheltered splicing bubble containing catalytic intronic sequences flanked by two regions of homology . Transfection of Gaussia or Firefly luciferase circRNA resulted in robust production of functional protein as measured by luminescence  was 1.5-fold more effective than the commonly adopted EMCV IRES in HEK293 cells  circRNA using gel extraction for small quantities and size exclusion HPLC for larger quantities of splicing reaction starting material  to equimolar quantities of a canonical unmodified 5′ methylguanosine-capped and 3′ polyA-tailed linear GLuc mRNA, as well as a commercially available nucleoside-modified  linear GLuc mRNA (Trilink). Protein production assessed by luminescence 24 h post-transfection revealed that circRNA produced 811.2% more protein than the unmodified linear mRNA at this early time point in HEK293 cells Fig. . Interes16. The possibility of adapting circular RNA for the purpose of stabilizing mRNA has been stifled by low circRNA production efficiency, difficulty of purification, and weak protein expression. Indeed, these obstacles must be overcome before the stability of protein production from circRNA can be fully assessed. Previously, the permuted group 1 catalytic intron-based system has been used to circularize a wide range of short RNA sequences in vitro, with circularization efficiencies reported to reach 90% for RNAs between 58 and 124 nt21. Longer RNAs (up to 1.5 kb) have recently been circularized using this method, but circRNA yields from these constructs have not been reported28. The engineered permuted group 1 catalytic intron-based system described herein permits the circularization of sequences up to 5 kb in length, significantly longer than previously reported. Moreover, we are able to obtain nearly 100% circularization efficiency for a range of inserted coding regions with diverse sequence compositions. We show that optimized circRNA is capable of producing large quantities of protein and also that it can be effectively be purified by HPLC. Finally, we demonstrate that circRNA can produce greater quantities of protein for a longer duration than the unmodified and modified linear RNAs used in this study, providing evidence that circRNA holds potential as an alternative to mRNA for the stable expression of protein. However, more work needs to be done to fully investigate the potential of circRNA for therapeutic and non-therapeutic applications, including further optimizations of protein translation from circRNA and a comprehensive study of the translation efficiency and stability of circRNA in other cell types and tissues. The nicking of longer circRNAs that we observed during the production of circRNA  and cloned into a PCR-linearized plasmid vector containing a T7 RNA polymerase promoter by Gibson assembly using a NEBuilder HiFi DNA Assembly kit (New England Biolabs). Spacer regions, homology arms, and other minor alterations were introduced using a Q5 Site Directed Mutagenesis Kit (New England Biolabs). Primers for this and the following methods can be found in Supplementary Data 18. Modified linear GLuc mRNA was obtained from Trilink Biotechnologies and consisted of a codon optimized GLuc coding region, a proprietary synthetic 5′ untranslated region, an alpha globin 3′ untranslated region, a cap 1 structure, a 120-nucleotide polyA tail, and complete replacement of uridine and cytosine along the entire mRNA with pseudouridine and 5-methylcytosine, respectively. Modified hEpo mRNA was also obtained from Trilink Biotechnologies and was structurally identical to the Trilink GLuc mRNA described above, except that it was modified with 5-methoxyuridine and the coding region coded for human erythropoietin. Unmodified linear RNA consisted of a GLuc or hEpo coding region but did not include specific untranslated regions. Unmodified linear mRNA or circRNA precursors were synthesized by in-vitro transcription from a linearized plasmid DNA template using a T7 High Yield RNA Synthesis Kit (New England Biolabs). After in vitro transcription, reactions were treated with DNase I (New England Biolabs) for 20 min. After DNase treatment, unmodified linear mRNA was column purified using a MEGAclear Transcription Clean-up kit (Ambion). RNA was then heated to 70 °C for 5 min and immediately placed on ice for 3 min, after which the RNA was capped using mRNA cap-2′-O-methyltransferase (NEB) and Vaccinia capping enzyme (NEB) according to the manufacturer’s instructions. Polyadenosine tails were added to capped linear transcripts using E. coli PolyA Polymerase (NEB) according to manufacturer’s instructions, and fully processed mRNA was column purified. For circRNA, after DNase treatment additional GTP was added to a final concentration of 2 mM, and then reactions were heated at 55 °C for 15 min. RNA was then column purified. In some cases, purified RNA was recircularized: RNA was heated to 70 °C for 5 min and then immediately placed on ice for 3 min, after which GTP was added to a final concentration of 2 mM along with a buffer including magnesium . RNA was then heated to 55 °C for 8 min, and then column purified. To enrich for circRNA, 20 µg of RNA was diluted in water  and then heated at 65 °C for 3 min and cooled on ice for 3 min. 20U RNase R and 10 µL of 10× RNase R buffer (Epicenter) was added, and the reaction was incubated at 37 °C for 15 min; an additional 10U RNase R was added halfway through the reaction. RNase R-digested RNA was column purified. RNA was separated on precast 2% E-gel EX agarose gels (Invitrogen) on the E-gel iBase (Invitrogen) using the E-gel EX 1–2% program; ssRNA Ladder (NEB) was used as a standard. We were unable to obtain adequate circRNA separation using other agarose gel systems. Bands were visualized using blue light transillumination and quantified using ImageJ. Unprocessed agarose gel images are present as Supplementary Fig. RNA structure was predicted using RNAFoldSplicing reactions enriched for circRNA with RNase R and then column purified were heated at 65 °C for 5 min in the presence of a DNA probe  as recommended by the manufacturer using a primer specific for a region internal to the putative circRNA. PCR product for sequencing was synthesized using Q5 polymerase (New England Biolabs) and a pair of primers spanning the splice junction.2 in Dulbecco’s Modified Eagle’s Medium (4500 mg/L glucose) supplemented with 10% heat-inactivated fetal bovine serum  and penicillin/streptomycin. HEK293 and HeLa cells tested negative for mycoplasma. Min6  medium was additionally supplemented with 5% hiFBS, 20 mM HEPES (Gibco), and 50 μM beta-mercaptoethanol (BioRad). Cells were passaged every 2–3 days. For all circRNA data sets presented in Fig. HEK293, HEK293-GFP, HeLa, and A549 cells (ATCC) were cultured at 37 °C and 5% COFor luminescence assays, cells and media were harvested 24 h post-transfection. To detect luminescence from Gaussia luciferase, 10–20 µL of tissue culture medium was transferred to a flat-bottomed white-walled plate (Corning). 25 µL of BioLux Gaussia Luciferase reagent including stabilizer (New England Biolabs) was added to each sample and luminescence was measured on an Infinite 200Pro Microplate Reader (Tecan) after 45 s. To detect luminescence from Firefly luciferase, 100 µL of Bright-Glo Luciferase reagent (Promega) was added to each well, mixed, and incubated for 5 min. 100 µL of the culture medium and luciferase reagent mix was then transferred to a flat-bottomed white-walled plate and luminescence was detected as described above. GFP fluorescence was detected 24 h post-transfection and images were taken using an EVOS FL cell imager (Invitrogen). Erythropoietin was detected by solid phase sandwich ELISA (R&D Systems) essentially according to the manufacturer’s instructions except cell culture supernatant 24 h post transfection was used, and samples were diluted 1:200 before use. Interferon-ɑ and interleukin 6 were detected by Fireplex immunoassay (Abcam).CRISPR-Cas9-mediated GFP ablation was detected by flow cytometry 96 h after transfection. HEK293-GFP and HEK293 control cells were trypsinized and suspended in Dulbecco’s Modified Eagle’s Medium (4500 mg/L glucose) supplemented with 10% fetal bovine serum and penicillin/streptomycin. Cells were then washed twice in FACS buffer  and resuspended in FACS buffer containing Sytox Blue Dead Cell Stain (Thermo Fisher) according to the manufacturer’s instructions, or FACS buffer alone for GFP and blank controls. Fluorescence was detected for 10,000 events on a BD FACSCelesta flow cytometer (BD Biosciences). Data was analyzed in Flowjo (Flowjo LLC).A total of 50,000 HeLa cells were reverse transfected with 200 ng of GLuc circRNA or modified linear mRNA. Cells were washed and RNA was harvested and purified 24 h after transfection using an RNeasy Mini Plus kit (Qiagen) according to the manufacturer’s instructions. Synthesis of first-strand cDNA from total RNA was performed with High-Capacity cDNA Reverse Transcription Kit using random hexamers (Thermo Fisher Scientific). Gene specific TaqMan primers were purchased as Assay-on-Demand from (Thermo Fisher Scientific), GAPDH (Hs99999905_m1), DDX58 (Hs01061436_m1), IFN-β1 (Hs01077958_s1). The qPCR reaction was carried out using LightCycler 480 Probe Master Mix (Roche) and LightCycler 480 instrument (Roche). For each sample, the real-time PCR reaction was performed in duplicate and the averages of the obtained threshold cycle values (Ct) were processed for further calculations according to the comparative Ct method. Gene expression levels were normalized to the expression of the housekeeping gene GAPDH.t-test, assuming unequal variances. Differences were considered significant when p < 0.05. For all studies, data presented is representative of one independent experiment.Statistical analysis of the results was performed by a two-tailed unpaired Welch’s The data that support the findings of this study are available from the corresponding author upon reasonable request.Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1


To determine intrinsic functional connectivity (IFC) related to symptom changes induced by rTMS in mal de debarquement syndrome (MdDS), a motion perceptual disorder induced by entrainment to oscillating motion. Twenty right-handed women  with MdDS received five sessions of rTMS  over consecutive days. High-density (128-channel) resting-state EEG were recorded prior to and following treatment sessions and analyzed using a group-level independent component (IC) analysis. IFC between 19 ICs was quantified by inter-IC phase coherence (ICPC) in six frequency bands . Correlational analyses between IFCs and symptoms were performed. Symptom improvement after rTMS was significantly correlated with (1) an increase in low alpha band (8–10 Hz) IFC but a decrease of IFC in all other bands, and (2) high baseline IFC in the high alpha (11–13 Hz) and beta bands (14–30 Hz). Most treatment related IFC changes occurred between frontal and parietal regions with a linear association between the degree of symptom improvement and the number of coherent IFC changes. Frequency band and region specific IFC changes correlate with and can predict symptom changes induced by rTMS over DLPFC in MdDS. MdDS symptom response correlates with high baseline IFC in most frequency bands. Treatment induced increase in long-range low alpha IFC and decreases in IFC in other bands as well as the proportion of coherent IFC changes correlate with symptom reduction. Mal de debarquement Syndrome (MdDS) is a motion-triggered disorder of persistent oscillating vertigo that occurs after prolonged exposure to passive motion  over the dorsolateral prefrontal cortex (DLPFC) is able to acutely reduce the perception of oscillating self-motion in MdDS  is a term used to denote baseline connectivity that is not stimulus driven . Participants provided written informed consent and were recruited under ClinicalTrials.gov study NCT02470377. Details of the long-term treatment effects have been previously reported  chronic perception of rocking vertigo that started within two days after disembarking from sea, air, or land based travel; (2) symptoms lasting at least 6 months; (3) no other cause for symptoms after evaluation by a neurologist or otolaryngologist with appropriate testing for peripheral inner ear or other central nervous system cause for symptoms. Exclusion criteria included: (1) an unstable medical or psychiatric condition, including a history of bipolar disorder or psychosis; (2) pregnant or planning to become pregnant during the study; (3) contraindications to receiving rTMS or MRI, including medications known to reduce seizure threshold; (4) an unclear history of the onset of symptoms; (5) an inability to complete all study related testing.All participants underwent structural brain MRI imaging for use in neuronavigation during the rTMS sessions. A T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) sequence with SENSE using the following parameters was acquired: FOV = 240 mm, axial slices per slab = 190, slice thickness = 0.9 mm, image matrix = 256 × 256, TR/TE = 5/2.012 ms, acceleration factor R = 2, flip angle = 8°, inversion time TI = 725 ms, sampling band-width = 31.2 kHz.abductor pollicis brevis muscle in 50% of trials. rTMS sessions consisted of 1 Hz right DLPFC stimulation at 110% of MT for 1200 pulses followed by 10 Hz left DLPFC stimulation at 110% MT for 2000 pulses. The 10 Hz protocol was administered as trains of 40 pulses over 4 s (10 Hz) followed by 26 s of rest.rTMS was performed with the Magventure MagPro X100 stimulator with a cooled figure-of-eight coil in biphasic mode with the handle back at a 45-degree angle relative to the mid-sagittal plane. The Localite TMS Navigator  frameless stereotaxy system was used for neuronavigation to identify the center of the DLPFC as the anterior portion of the middle of the middle frontal gyrus. Motor thresholds (MT) were determined each day with independent measurements made for both the right and left M1 hand areas before each of five treatment sessions that were performed on consecutive days at the same time each day. MTs were defined as the percent intensity of the stimulator output that generated a 50 µV motor evoked potential in the contralateral The participants rated their symptom status on a visual analogue scale (VAS) of 0–100 in which 0 represented complete absence of rocking vertigo and 100 represented symptoms so severe that they could not remain upright. The change of the VAS score from the first (Day 1) to the last (Day 5) day was calculated. Participants whose symptoms decreased by 10-points or more were considered to be “positive” responders (improved); those whose scores increased by 10 points or more were considered “negative” responders (worsened); those with scores in-between were considered to be “neutral.” The minimum criterion of 10 points was chosen because it best correlated with the participants’ own perceptions of significant symptom change.Two sessions of 5-min resting state EEG data acquisition were performed before the first rTMS session (Day 1) and about 3 h after the last rTMS session (Day 5) using a 128-channel EEG cap . The post rTMS EEG data were acquired with a delay because of the obligatory time spent to prepare the cap on the subject with electrode paste. The post-treatment EEG data thus represented more sustained neuromodulatory effects than if the recordings were made immediately following the last treatment. The online reference channel was located at the FCz position and the ground electrode at the AFz position. Impedance of all electrodes was maintained below 10 KΩ with a sampling frequency of 1000 Hz, an analog filter from 0.016 to 250 Hz, and a resolution of 0.1 µV. Participants sat in a chair with their eyes closed in a quiet darkened room during the recording.FASTER toolbox and visual inspection . The significance level was set to p < 0.05 with Bonferroni correction [significance level divided by the number of IC pairs based on 19 selected ICs /2) * the number of frequency bands ].Pre- and post-rTMS ICPC values were separately examined via a one-sample p value of the correlation analysis was < 0.05 and the ICPC value was significantly different from zero in either the pre- or post-rTMS session, as detected in the first analysis.Cross-subject Pearson correlation analysis was performed on the pre- to post-rTMS  ICPC differences and VAS scores to identify symptom change-related IFCs. An IFC was of statistical significance only when the p value of the correlation analysis was < 0.05 and the ICPC value was significantly different from zero in the pre-rTMS session detected in the first analysis.An independent cross-subject Pearson correlation analysis was performed between pre-rTMS (i.e. baseline) ICPC values and VAS score changes to identify IFCs whose baseline values correlated with treatment response. Here, an IFC was considered statistically significant only when the Based on the overlapping IFCs that showed consistently significant correlations in both the prior correlation analyses, we calculated the proportion of IFCs that exhibited the same direction (coherency) of changes induced by rTMS as indicated in the prior correlation analyses for each participant. A third cross-subject correlation analysis was then conducted between this proportion and the VAS score changes. The goal of this analysis was to examine the treatment-related IFC changes beyond individual IFCs in order to determine whether there was a general pattern of IFC changes that correlated with treatment response.In steps 2 and 3, we did not perform a correction for multiple comparisons in terms of the number of IC pairs and frequency bands, but only implemented a constraint that the ICPC values were different from zero in either pre- or post-rTMS session.Twenty right-handed individuals with MdDS completed all 5 days of the protocol. Despite being open to either sex, only female participants volunteered for the study, reflecting the significantly higher proportion of women to men in this disorder , indicating that rTMS-induced IFC enhancement in this band was correlated with a reduction in symptoms. Conversely, the IFCs in the high alpha and beta bands were predominantly positive , indicating a general rTMS-induced IFC reduction in the high alpha and beta bands with improvement in symptoms. The IFCs in other frequency bands showed no predominant directional correlation with symptom change. When counting the ICs that were identified in these IFCs across all frequency bands, six ICs were present at least once in five frequency bands, i.e., IC2, IC3, IC9, IC16, IC18 and IC19, and five ICs were present in at least eight IFCs across all frequency bands, i.e., IC2(11), IC3(8), IC7(8), IC9(10), and IC18(8). It was notable that most of the ICs and IFCs that correlated with symptom changes were long-range and inter-hemispheric, especially related to frontal and parietal regions.Intrinsic functional connectivity changes that significantly correlated with VAS score changes are illustrated in Fig. Baseline IFC measurements that were significantly correlated to VAS score changes and may be predictive of treatment response are illustrated in Fig. A group of IFCs were identified with significant correlations in the preceding two types of correlation analyses. Among them, 16 IFCs were simultaneously identified with consistent correlation patterns Fig. , i.e., tr = − 0.81, p = 0.000013, Fig. The correlation analysis between the coherency of IFCs changes (exhibiting the same direction of change) and VAS score changes revealed a significantly negative relationship  or engagement (low power) of specific neurocognitive processes  showed IFC changes discrete from those who either did not change or who worsened, creating basically two functional groups—responders and non-responders. Supporting this pattern is that these IFC results were consistent with resting-state functional connectivity changes measured with BOLD, which also showed that those who improve with rTMS exhibit connectivity patterns different from those who either show no change or who worsen , in which IFC increased after successful treatment. A favorable response was associated with higher baseline IFC values and a greater coherence in the direction of IFC change induced by rTMS. Though this was true in all frequency bands, the strongest correlations were in the high alpha and beta bands. In addition, most of these IFCs covered frontal and parietal regions with long range and interhemispheric connectivity. Uncovering these prognostic and treatment related factors may aid in the development of more precise and effective neuromodulation therapies for motion perception disorders, including studies that aim to prime the brain by enhancing IFC and by targeting specific frequency bands for treatment.