In a MEMS capacitive accelerometer, there is an offset due to mechanical and electrical factors, and the offset would deteriorate the performance of the accelerometer. Reducing the offset from mechanism would benefit the improvement in performance. Yet, the compositions of the offset are complex and mix together, so it is difficult to decompose the offset to provide guidance for the reduction. In this work, a decomposition method of offset in a MEMS capacitive accelerometer was proposed. The compositions of the offset were first analyzed quantitatively, and methods of measuring key parameters were developed. Based on our proposed decomposition method, the experiment of offset decomposition with a closed-loop MEMS capacitive accelerometer was carried out. The results showed that the offset successfully decomposed, and the major source was from the fabricated gap mismatch in the MEMS sensor. This work provides a new way for analyzing the offset in a MEMS capacitive accelerometer, and it is helpful for purposefully taking steps to reduce the offset and improve accelerometer performance. With the progress of MEMS technology, the MEMS device is widely used in fields of consumer electronics, industry, and military for its small volume and low cost. The MEMS devices based on capacitance detection usually have the advantages of high accuracy and good stability, and the capacitive accelerometer is a typical representative application, which can be applied in inertial navigation and control systems ,2. OffseCurrently, the offset of MEMS capacitive accelerometers has been researched considerably, and the research has mainly involved the calibration and resource of the offset. The calibration of offset is just a mathematical operation ,5,6. ForThis paper proposed an offset decomposition method in a closed-loop MEMS capacitive accelerometer. Based on our developed methods of measuring key parameters of the MEMS accelerometer, the compositions of the offset were analyzed and decomposed. This decomposition method can help researchers distinguish the sources of offset quantitatively. Based on the decomposition result, the major source can be identified, and the corresponding improvement can be purposefully raised to reduce the offset. Once the offset is reduced from the mechanism level, the performance of the MEMS accelerometer can be improved. Therefore, our proposed method is of great significance for researchers to improve the performance of the MEMS capacitive accelerometer.For the closed-loop MEMS capacitive accelerometer, a sketch map of the servo system based on an electrostatic force balance is shown in k is the stiffness of the spring, x is the bent value of the spring, m is the inertial mass of the proof mass, a is the input acceleration, sF is the residual stress on the inertial mass along the sensitive direction, and the equation of electrostatic force eF is as follows:rε and ε0 are the relative and absolute dielectric constant, respectively, A is the overlapped area of capacitance, dV is the modulated voltage, outV is the output voltage and equal to the feedback voltage fbV, rV is the pre-load voltage, d is the gap between electrodes, and K1 is the scale factor and is equal to m × d2/(2 × rε × ε0 × A × rV).In the closed-loop system of the MEMS capacitance accelerometer, there is a force balance for the proof mass , and theEquation (2) is substituted into Equation (1), and the formula of force balance can be transformed to:TC and bC are the capacitances of the top electrodes and bottom electrodes, respectively, and CVK is the conversion parameter from capacitance to voltage.On the other hand, there is a capacitance balance in the closed-loop system of the MEMS capacitance accelerometer, which means that the voltage of detecting capacitance must be equal to 0. Therefore, the equation of capacitance balance is as follows:TC and bC contain the effective capacitance and parasitic capacitance. According to Equation (4), the mismatch of effective capacitance and parasitic capacitance can all result in the bending of the spring. Thus, the bent value x of the spring is determined by this capacitance balance, and the bent value of the spring can be expressed as:dx is the gap mismatch due to the fabricating error and px is caused by the parasitic capacitance and is equal to ΔpC/Kx2C, where ΔpC is the mismatch of parasitic capacitance and Kx2C is the conversion parameter of the sensor from displacement to capacitance.The capacitances Vout-0g is the output voltage without input acceleration, and eδ is the part caused by electrical components.The offset is the accelerometer output that has no correlation with input acceleration. In additional to the MEMS sensor, the error of the circuit would also affect the offset. Thus, the effect of the circuit should also be added into the offset, and the original offset can be expressed as follows according to Equations (3) and (5).In the closed-loop system of a MEMS capacitive accelerometer, the force balance and capacitance balance are key, and the model of the offset is deduced according to the two balances. Any factor that affects these two balances will change the offset. The offset of the MEMS capacitive accelerometer from the electrical part mainly originates from the parasitic capacitance and electrical components.pC can be obtained. The parameter Kx2C of the MEMS sensor can be expressed as:Using the method in our previous work , the misk, Kx2c, and ΔpC, the offset caused by parasitic capacitance can be separated from the whole offset.Based on the parameters of osV is the DC offset voltage of the PID amplifier and opK is the gain of the open loop, in units of V/g. The DC offset voltage of the amplifier can be found through looking up its datasheet, and the gain of the open loop can be obtained in the open-loop system. Usually, this composition would not be large.In the open-loop system of a MEMS capacitance accelerometer, its offset is seriously influenced by electrical components, such as the front-end capacitor and the gain of an amplifier . HoweverThe offset of the MEMS capacitive accelerometer from the mechanical part mainly originates from the gap mismatch and residual stress on the inertial mass.k and the gap mismatch x should be measured. Subsequently, this offset composition of can be calculated according to k × x m.To obtain the offset, which is caused by a gap mismatch, the parameters of mechanical stiffness The three-dimensional structure of a MEMS sensor is formed through the thermal bonding process, which would bring residual thermal stress, and the package would also cause mechanical stress on the sensor. This tiny stress is difficult to accurately measure, and the weight along the sensing direction is usually difficult to obtain. Therefore, it is difficult to measure this composition directly. In this paper, the value of this composition was obtained through deducting other compositions from the whole offset.In our decomposition method of offset, the parameters of the MEMS accelerometer are the basis, including the mechanical stiffness, the gap and its mismatch, and the mismatch of parasitic capacitance. Therefore, methods of measuring these parameters were developed.The actual gap between electrode plates would seriously deviate from the design value, owing to MEMS fabricating technology. Thus, the gap of the sensor should also be measured experimentally. In this paper, the value of the gap was extracted from the scale factor of the closed-loop accelerometer.K1 is a scale factor of the closed-loop accelerometer, d0 is the gap between electrode plates of the sensor, rε and ε0 are the relative and absolute dielectric constant, respectively, A is the overlapped area of capacitance, and rV is the pre-load voltage. Then, the calculated formula of the gap is as follows:In a closed-loop system, the scale factor of the MEMS capacitive accelerometer can be expressed as :(9)K1=m×pC would result in offset. The measuring method of the mismatch of parasitic capacitance has been described in our previous work [pC is as follows:In a MEMS capacitance accelerometer, the sensing principle is capacitance detection. Thus, the parasitic capacitance can disturb the output, and its mismatch Δous work . The calk is critical for calculating the elastic force. Due to the fabricating error of MEMS technology, the actual value of mechanical stiffness would deviate largely from the design and simulation value, and so the mechanical stiffness should be measured experimentally. In this paper, a new method of measuring the mechanical stiffness was proposed and is presented below.The mechanical stiffness of spring rV is applied to the sensor, the output would change due to the electrostatic stiffness. The difference in output voltage with different input acceleration is:a1 and a2 are different input accelerations on the accelerometer, ek is the electrostatic stiffness caused by the voltage rV [Kx2C is the conversion parameter of the sensor from displacement to capacitance, and KC2V is the conversion parameter from capacitance to voltage. Equation (11) can be transformed to:Y = 1/ΔoutV is the dependent variable, X = ek is the independent variable, a = −1/B, b = k/B, B = m × (a2 − a1) × Kx2C × KC2V that is a fixed value, and k is the mechanical stiffness.The mechanical stiffness was obtained through debugging the open-loop system of the MEMS accelerometer. Thus, the closed-loop accelerometer should be transformed into an open-loop system. In the open-loop system, the spring would bend with input acceleration, and there would be output voltage, while when DC voltage ltage Vr , Kx2C isoutV and ek. Through linear fitting, the slope a and intercept b can be obtained. Then, the mechanical stiffness k can be obtained and is equal to −b/a.Equation (12) shows that there is a strong linear relationship between 1/ΔAs a result of the fabricating error of MEMS technology, the gaps of the top and bottom electrode plates would be different. Consequently, the mismatch of the gap would result in an offset. The nanoscale and discreteness make the measurement of the gap mismatch difficult. Thus, a new method of measuring the gap mismatch was developed, and it is described as follows.TV and BV are the DC voltages applied to the top and bottom electrodes, respectively, and Td and Bd are the gaps between the top and bottom electrodes, respectively. According to Equation (13), the proportion α of gaps between top and bottom electrodes and the gap mismatch x can be obtained, and the formulas are as follows:This method is based on the balance of electrostatic forces between top and bottom electrode plates. First, the closed-loop accelerometer is transformed into an open-loop system, and DC voltages are applied to the top and bottom electrodes. Then, adjusting the voltage amplitudes makes the output equal to the offset voltage. Under this condition, the electrostatic forces between the top and bottom electrode plates are equal. Thus, there is a balance of electrostatic forces:The step-by-step procedure of our decomposition of offset is described as follows, and the flowchart is sketched in (1) The closed-loop MEMS capacitive accelerometer is selected as an experimental sample.K1, the gap d0 can be obtained according to Equation (10).(2) In a gravity field, the offset and scale factor of the closed-loop system are tested. Based on the scale factor m and overlapped area A are extracted, and some parameters can be obtained.(3) According to the design structure, the inertial mass pC can be obtained.(4) In the closed-loop system, the test of parasitic capacitance is carried out according to the method described in our previous work , and the(5) The closed loop is broken at the node of the PID, and the closed-loop system is changed into an open-loop system.rV is disconnected from the reference fixed voltage and connected to the output of the adjustable power supply. Then, the voltage rV is changed, and the outputs of the accelerometer are recorded under the input axis conditions of vertically upward and downward. Lastly, the mechanical stiffness can be obtained according to Equation (12).(6) In the open-loop system, the test of mechanical stiffness is carried out. The DC voltages of the top and bottom fixed plates are connected to GND, and the DC voltage of the proof mass rV is connected to GND, and the DC voltages of the top and bottom fixed plates are connected to two different outputs of the adjustable power supply. The DC voltage of the top fixed plate TV is set as a fixed voltage, and the DC voltage of the bottom fixed plate BV is adjusted to make the output equal to the offset voltage. Therefore, the gap mismatch x can be obtained according to Equation (14).(7) In the open-loop system, the test of gap mismatch is carried out. The DC voltage of proof mass opK can be obtained according to the outputs.(8) In the open-loop system, the test of the open gain is carried out in a gravity field. The DC voltage of the proof mass and fixed plates are all connected to GND, and the outputs are recorded under the input axis conditions of vertically upward and downward. The parameter s/mF. The composition of residual stress is calculated through deducting other compositions from the whole offset.(9) Based on the measured data, the compositions can be directly obtained except for The experimental sample is our self-built MEMS capacitive accelerometer. The structure of the sensor is a comb-finger, and the inertial mass is movable in-plane. The sensor is sealed in a ceramic shell under atmospheric pressure, and the detecting circuit is constructed by discrete devices on the PCB. The sample and structural diagram of the sensor are shown in The sensor of the MEMS capacitive accelerometer is fabricated with a bulk silicon process, and the process of SOG (silicon on glass) is adopted. The fabrication steps of the sensor are shown in The fabricated sensor is observed using a scanning electron microscope, and the SEM image is shown in K1 was 578.955 mV/g.First, the scale factor and offset of this closed-loop accelerometer were measured in a gravity field, and the data are recorded in d0 could be calculated and was equal to 3.455 µm. According to the data and Equation (7), the parameter Kx2c could be calculated and was equal to 5.281 × 10−6 F/m.Based on the value of the scale factor and Equation (10), the average gap of this sensor Y = 3.74 × 10−9 × X + 8.74 × 10−7. According the slope of linear fitting, the mismatch of parasitic capacitance ΔpC could be obtained and was equal to 12.9 fF.In the closed-loop system, the parasitic capacitance was measured. Based on our method proposed in our previous work , the misAfter completing the test in a closed-loop system, the closed loop was broken at the node of the PID and changed into an open loop. Then, the measurements of mechanical stiffness and gap mismatch were carried out in an open-loop system.rV was applied on the middle electrode plate, the fixture with the accelerometer was overturned to make the direction of the input axis vertically upward and downward, and the outputs were recorded. Then, the amplitude of rV was changed, and the above steps were repeated. Vout1 and Vout2 are the output voltages of the open-loop system under the input axis conditions of upward and downward, respectively.The measurement of mechanical stiffness was carried out based on our abovementioned method. When the DC voltage outV as the Y-axis and ek as the X-axis was made and is shown in Y = −0.0120 × X + 0.887, and the R2 of the fitting was 1.00, which shows a highly linear correlation between 1/ΔoutV and ek. According to Equation (12), the mechanical stiffness k of the spring in this accelerometer was equal to 73.92 N/m. It should be noted that the linearity would decrease when the voltage rV is larger. This is because the large displacement x caused by the large voltage rV would produce a nonlinear effect. On the other hand, several other samples were also tested. The linearities were all high, but they were different.A curve with 1/ΔBV, with a value of 1 V, was applied on the bottom electrode, and the voltage TV was then applied on the top electrode and adjusted. The tested data are shown in Then, the gap mismatch was also measured in an open-loop system. In this measurement, the input acceleration should be as small as possible, ensuring that the spring is in a free state, which can improve the accuracy of measurement. Thus, we adjusted the position of the accelerometer so that the value of the output was −116.0 mV. At that position, the voltage VT/VB = 1.008, and the gap mismatch was x = (1 − α) × d0/2 = −0.01382 µm. When the loop of the servo system was closed, the spring would bend due to the fabricated gap mismatch, and the bending value was equal to x. Thus, the offset caused by the fabricated gap mismatch was equal to k × x/m = −222.8 mg.According to Equation (14), the proportion α of gaps between the top and bottom electrode plates was equal to Lastly, the offset caused by the DC offset voltage in the PID amplifier was analyzed. The type of PID amplifier was OP4177 in this accelerometer, and its DC offset voltage was smaller than 60 µV. The measured gain of the open loop was 103.823 mV/g, and so the offset caused by this voltage was smaller than 0.6 mg according to Equation (8). Therefore, this composition was small enough to be ignored.Our proposed decomposition method of offset takes advantage of the characteristic that the MEMS sensor has a movable structure, and electrical methods were exploited to nondestructively measure the parameters of the accelerometer. Our proposed methods of measuring the accelerometer key parameters are based on our decomposition method of the offset, and it can also be extended to other applications, for example, the evaluation of MEMS fabricating technology and the design of a control system.The real values of the accelerometer key parameters are difficult to obtain exactly. For example, the structure of the sensor has hundreds of comb-fingers, which make the equivalent gap difficult to obtain exactly. The micro-scale also makes the mechanical stiffness difficult to obtain exactly. This fact prompted us to develop new methods. In order to verify the accuracy of the results obtained by our proposed methods, another approach was introduced, and measurements were carried out.d1 was 3.617 µm and d2 was 14.70 µm. According to the capacitance model shown in In this experimental MEMS sensor, the gap was designed to be 2.5 µm, and the over-etching width was about 1 µm in this SOG process. Based on our electrical measurement method, the fabricated gap of the MEMS sensor was 3.455 µm. Moreover, these data were compared with the result of dimension measurement. The SEM was used to experimentally measure the gap of the comb. The result of one comb is shown in Thus, the equivalent gap measured by SEM was 3.499 µm. The result of dimension measurement was close to the result of our algorithm, and the difference was 1.3%, which mainly comes from the following two aspects: (1) The sensor has several hundreds of combs, and the gap difference of different combs can reach up to 0.1 µm. (2) During the dimension measurement, an unclear boundary can lead to measurement error.The MEMS etching process also resulted in a gap mismatch with a value of −0.01382 µm. This value seems very small, but it introduced a major offset. Similarly, the mechanical stiffness deviated from the design value by the MEMS etching process. The measured value of mechanical stiffness was 73.95 N/m, and it was much smaller than the design value of 109 N/m. Using the confocal laser scanning microscope, the width of the spring was measured, and the value was 8.8712 µm. According to the theoretical formula of mechanical stiffness for the folded beam, the calculated value was 76.21 N/m, which is close to the result of our algorithm. The difference of 3.1% mainly came from the nonuniformity of the several beams and simplified theoretical formula.On the other hand, the error of the dimensional measurement using SEM was 0.1%, and the error of the source voltage was 0.2%. Based on these errors, the uncertainty in different items for the offset compositions can be obtained. The uncertainty in the first item k × Δp/Kx2c/mC = + 39.5 mg. The separated compositions are summarized in Based on our analysis and methods, the offset of the MEMS capacitive accelerometer was successfully separated from each other using our proposed decomposition method. For example, the offset caused by the mismatch of the parasitic capacitance was As can be seen from This paper describes a decomposition method of offset in a closed-loop MEMS capacitive accelerometer. The model of the offset was established, and the effect of the mechanics and electricity were analyzed. Methods of measuring the mechanical stiffness and gap mismatch in the MEMS capacitive accelerometer were first introduced and validated. The experiment of our silicon-based comb-finger MEMS accelerometer showed that the offset was successfully decomposed, and its source was mainly from the fabricated gap mismatch. Our future work may focus on reducing the gap mismatch and developing a method of measuring the residual stress based on the decomposition result. This work is helpful for designers to distinguish the source of offset in MEMS capacitive accelerometers and purposefully take steps to reducing the offset for improving performance.


Such selections permitted isolation of numerous suppressors after EMS (ethyl methanesulfonate) mutagenesis, leading to demonstration of delays in mutation fixation after initial EMS treatment, as has been shown in T4 bacteriophage but not previously in eukaryotes. Three strong dominant extragenic suppressor loci have been defined, all of which act specifically on allele e245, which causes a G347R mutation in UNC-17. Two of the suppressors (sup-1 and sup-8/snb-1) have previously been shown to encode synaptic proteins able to interact directly with UNC-17. We found that the remaining suppressor, sup-2, corresponds to a mutation in erd-2.1, which encodes an endoplasmic reticulum retention protein; sup-2 causes a V186E missense mutation in transmembrane helix 7 of ERD-2.1. The same missense change introduced into the redundant paralogous gene erd-2.2 also suppressed unc-17(e245). Suppression presumably occurred by compensatory charge interactions between transmembrane helices of UNC-17 and ERD-2.1 or ERD-2.2, as previously proposed in work on suppression by SUP-1(G84E) or SUP-8(I97D)/synaptobrevin. erd-2.1(V186E) homozygotes were fully viable, but erd-2.1(V186E); erd-2.2(RNAi) exhibited synthetic lethality , indicating that the missense change in ERD-2.1 impairs its normal function in the secretory pathway but may allow it to adopt a novel moonlighting function as an unc-17 suppressor.A missense mutant,  Caenorhabditis elegans, as a consequence of the small size of this animal, its diploidy, and its reproduction by self-fertilization, features which allow examination of large numbers of individuals and the isolation of both dominant and recessive suppressor mutations  strains over many years.Different mutagens were tested for efficacy: it was found that both EMS (ethyl methanesulfonate) and (much less efficiently) UV or X-irradiation could yield strong, apparently wild-type revertants . No sponC. elegans. The main effect of this agent on DNA is to cause the alkylation of guanine residues, creating O-6-ethylguanine (unc-17(e245) phenotype reversion system provided an opportunity to test for the same effect in a multicellular organism.The ease with which EMS revertants could be detected prompted the first experiment described below, which addressed the mechanism of EMS mutagenesis in lguanine . This molguanine . The uncC. elegans genetics: three loci were defined and named sup-1, sup-2, and sup-8. All three suppressors defined in these experiments behaved genetically as dominant allele-specific modifiers, acting only on the e245 mutation of unc-17  by its extragenic modifiers emerged from detailed analyses of sup-8 and sup-1, which were found to encode synaptic proteins (sup-8(e1563) is a missense mutation affecting SNB-1 (synaptobrevin), a small integral synaptic vesicle membrane protein that is essential for synaptic exocytosis. The sup-8(e1563) mutation results in the introduction of an acidic residue (I97D) into the middle of the single transmembrane domain of synaptobrevin. Therefore, restoration of acetylcholine transporter activity could be explained by compensatory charge interactions between the positively charged UNC-17(Arg347) and the negatively charged SNB-1(Asp97)  single-pass synaptic protein of uncertain function  and SUP-1(Glu84).Similarly, sup-2 remained unknown, and is addressed in the present report.The molecular identity of C. elegans were used (Standard methods for culture and growth of ere used . Experimfem-1(hc17) IV, CB933 unc-17(e245) IV, CB2210 unc-17(e245) IV; sup-2(e997) X, CB3031 unc-17(e245) IV; snb-1(e1563) V, CB3987 pha-1(e2123) III, CB4985 sup-1(e995) III; unc-17(e245) IV, CB7427 unc-17(e245) IV; eEx849[erd-2.2(V186E) + sur-5p::GFP], CB7430 unc-17(e245) IV; eEx855[erd-2.1(V186E) + sur-5p::GFP], CB7550 erd-2.1(e997) X, CB7551 rrf-3(pk1426) II; erd-2.1(e997) X, NL2099 rrf-3(pk1426) II, RM3727 pha-1(e2123) III; unc-17(e245) IV; mdEx1160[unc-17p::erd-2.1(V186E) + pBX].Strains utilized were: N2 wild type, BA17 “sup-8/snb-1” refers to the allele e1563, and “sup-2/erd-2.1” refers to the allele e997. Relevant new strains generated in this study are available from the Caenorhabditis Genetics Center.Unless otherwise specified, the term unc-17(e245) L1 larvae were obtained in two ways. For the first experiment, plates of starved unc-17 worms that had accumulated large numbers of arrested L1 larvae were washed off with M9 buffer and the resulting suspensions were taken through repeated cycles of settling under normal gravity in 5 ml volumes of M9, in order to remove all developmental stages later than the slow-to-settle L1 animals. For subsequent experiments, adult populations were bleached and sheared to produce pure egg populations, which were then hatched in M9 buffer overnight to generate synchronous arrested L1 larvae . A maximum projection tiff file was created and the 25-pixel circle within the nerve ring with the highest average intensity was identified. For each experiment, the highest average intensities in this circle for each strain were averaged (1–6 worms per genotype). These data supported the observed order of immunoreactivity: unc-17(e245) < unc-17(e245); sup < sup for each of sup-1(e995), sup-2/erd-2.1(e997), and sup-8/snb-1(e1563).Nematodes were fixed and stained as previously described (erd-2.1 was modified by site-directed mutagenesis to encode ERD-2.1(V186E) and fused to the 5 kb unc-17 promoter; this promoter is expressed specifically in (and defines) cholinergic neurons (pha-1(e2123ts) animals together with pBX, a pha-1(+) clone (unc-17(e245) and a suppressed line, RM3727 = pha-1(e2123ts); unc-17(e245); mdEx1160[unc-17p::erd-2.1(V186E) + pBX] established from subsequent progeny. Longer genomic clones of erd-2.1 and erd-2.2 that included presumed endogenous promoter regions were similarly modified to encode ERD-2.1(V186E) and ERD-2.2(V186E), and injected into wild-type animals (at 3 ng/µl) using sur-5p::GFP (pTG96) as a transformation marker (at 90 ng/µl). For erd-2.1, 6.6 kb including 4.7 kb of upstream intergenic sequence was cloned from wild-type DNA using primers aggaaacgcgtaaacgagtaacgc (erd-2.1For) and cccgcaggaaacaacaatcgatcc (erd-2.1Rev), and modified using primer gctggaatcGAGcaaaccgtt (erd-2.1V186EFor). For erd-2.2, 5.0 kb including 3 kb of upstream intergenic sequence was cloned from wild-type DNA using primers acgatcacagtcgtcacagaagagc (erd-2.2For) and cgtcgtttctccgagactttccaag (erd-2.2Rev), and modified using primer gccggaattGAAcaaactgtt (erd-2.2V186EFor). New England Biolabs Site-Directed Mutagenesis Kit E0554 was used for modification. The resulting extrachromosomal transgenes (eEx849 [erd-2.2(V186E) + sur-5p::GFP], eEx855 [erd-2.1(V186E) + sur-5p::GFP]) were then crossed into unc-17(e245) to establish suppressed lines. Three or four independent transgenes were tested for each construct. Strains CB7427 = unc-17(e245) IV; eEx849[erd-2.2(V186E) + sur-5p::GFP] and CB7430 = unc-17(e245) IV; eEx855[erd-2.1(V186E) + sur-5p::GFP] were used for the measurements shown in Procedures for microinjection and selection or identification of transformants were as described . A wild-C. elegans strains N2 (wild-type), CB7550 [sup-2(e997)], NL2099 [rrf-3(pk1426)], and CB7551 . HT115 E. coli clones containing L4440 plasmids coding for the dsRNAs of interest (erd-2.1 and -2.2) were selected from the Ahringer RNAi library  were found to be as efficacious as 1:1 mixtures. A single OP50-fed young L4 hermaphrodite (P0) was transferred onto each seeded plate and then removed after 48 h. Three to five separate broods were examined for each condition. Progeny was examined for survival and abnormal phenotypes. RNAi-knockdown of pop-1  was used as a positive control for the uptake and expression of dsRNA. Brood size, hatching and larval survival beyond L2 stage are shown in Supplementary Table S2.All RNAi experiments were performed at 20°C by the feeding method  suppression paradigm permitted a test of the phenomenon of delayed fixation of EMS mutations, originally observed in bacteriophage T4  animals were collected, exposed to EMS, washed and plated on 9 cm bacterial lawns, at multiplicities of 170–1000 per plate. Plates were incubated until egg-laying began and then, over the next six days, examined carefully for non-Unc F1 progeny animals. All non-Unc animals were picked; all exhibited a sustained apparently wild-type locomotory phenotype. Out of 97 plates, seeded with an average of 510 L1 worms per plate, 29 plates produced at least one non-Unc F1 animal. All such plates were re-screened repeatedly, to detect all members of a mutant clone.In initial experiments, L1 populations of e245 worms to the standard dose of EMS resulted in a reduction in self-fertility, from 190 (control) to 120 F1 worms per animal , so the largest clone of revertants  may have been as much as 25% of a single brood. However, it is likely that this apparent large clone represented two independent broods occurring on the same plate. Most of the clones detected were much smaller, indicating that fixation of a mutational event occurred at some variable number of divisions after the initial exposure to mutagen.Results are summarized in 1 revertant worms were picked to separate plates and allowed to produce F2 self-progeny. Most segregated both Unc and non-Unc worms, in approximately 1:3 ratio, indicating that the parent worm was heterozygous for a dominant suppressor mutation. A minority segregated only non-Unc worms, indicating homozygosity in the parent, and therefore that the induced mutation had contributed to both oogenic and spermatogenic pools in the hermaphrodite germ-line. This observation showed that homozygous mutants could be generated in the F1 generation after mutagenesis, but only at low frequency.Eighty of the 144 Fe245 animals were mutagenized, some of their rare non-Unc revertant progeny failed to breed true and produced F2 broods consisting only of Unc worms. Most probably such worms were genetically mosaic, with germlines in which the suppressor mutation had been lost or corrected while the soma remained mutant. A further experiment showed that such mosaicism is frequent when the parent worms were mutagenized at a late larval or adult stage. unc-17(e245) worms were synchronized at L1 stage and equal numbers were allowed to develop for 0–4 days at 15°C before mutagenesis, corresponding to mutagenesis at each of the four larval stages and young adulthood. F1 broods were then screened for non-Unc animals and all were picked, as in the first experiment. As shown in When more mature Mutagenesis even at L3 or L4 stage yielded some homozygous revertant progeny, confirming the previous inference that spermatogenic and oogenic germlines do not become segregated early in larval development.unc-17(e245) were recovered using either of these agents.Attempts to repeat these experiments using mutagens expected to have more immediate effect, such as UV or X-irradiation, were not successful, owing to much lower efficiency of mutagenesis . Howeverunc-17(e245) homozygotes . The complete dominance exhibited by these suppressors precluded complementation testing, so it was assumed that all defined the same locus, designated sup-1. One suppressor exhibited strong linkage to the sex-linked marker dpy-6, defining a second suppressor locus, sup-2. One X-ray-induced suppressor also exhibited sex-linkage but was not further analyzed.Many of the EMS-induced extragenic suppressors generated in the above experiments were mapped genetically . Most  but having no effect on other tested alleles of this gene . Independent isolates of the unc-17(G347R) mutation  were all well suppressed by each of the three suppressors. Limited tests using mutants in a variety of other genes showed no suppressive effects, indicating that these were gene-specific suppressors, in contrast to sup-5 and other informational suppressors that have been studied in C. elegans  at +1.36 ± 0.36 cM on LGX, corresponding to an interval of 9.30–9.85 Mb on the complete X-chromosome genomic sequence (The unc-17(e245); sup-2(e997)] revealed a total of 112 base changes on the X chromosome, three of which lay in this interval and three just outside it. Of these six candidates, a Val-to-Glu missense change in F09B9.3, now named erd-2.1  seemed most plausible. The relevant nucleotide change in erd-2.1 was a T to A transversion , unlike the G to A transitions most commonly induced by EMS  animals. Homozygous unc-17(e245) animals carrying this transgene were non-Unc, indicating that suppression was occurring.A transgene encoding this mutant form of ERD-2.1 (derived from CB2110 genomic DNA) and driven by the erd-2.1(V186E) was confirmed by using a different transgene carrying 6.6 kb of wild-type genomic sequence encompassing erd-2.1 plus 4.7 kb of upstream sequence, with the appropriate single base change introduced by site-directed mutagenesis, and sur-5p::GFP as a transformation marker. When this transgene was crossed into a homozygous unc-17(e245) background, all fluorescent animals were non-Unc and all nonfluorescent animals were Unc, confirming suppression. Three out of three independent transformed lines exhibited suppression. Fluorescent animals from one of these lines were picked for the assays shown in unc-17(e245); sup-2(e997) = CB2110].Suppression by C. elegans genome contains two genes with homology to Saccharomyces cerevisiae ERD2: F09B9.3 and C28H8.4 (ERD2 has 44% amino acid sequence identity to both). These genes have therefore been given the names erd-2.1 and erd-2.2. The encoded proteins both contain 213 amino acids and are 68% identical, 84% similar in amino acid sequence. Previous work S. cerevisiae ERD2 . To test this possibility, an erd-2.2(V186E) transgene was constructed from a 5 kb genomic clone including erd-2.2 plus 3 kb of upstream sequence, modified with a single base change introduced by site-directed mutagenesis. This was then injected into worms together with sur-5::GFP as a transformation marker, and crossed into an unc-17(e245) background. Four out of four independent transformed lines exhibited suppression, demonstrating that erd-2.2 can also act as an e245 suppressor, with similar or possibly greater efficiency to erd-2.1  was detectably weaker than suppression by either sup-1(e995) or snb-1(e1563), because heterozygous unc-17(e245); sup-2/+ animals moved significantly less well than unc-17(e245); sup-2 homozygotes  and erd-2.2(V186E) was also weaker than with sup-1 and sup-8/snb-1 . The suppressing missense change introduces an acidic residue into the seventh transmembrane helix of the ERD-2 receptor, so it seems likely that the mechanism of suppression is similar to that inferred for sup-1 and sup-8/snb-1. That is, restoration of UNC-17 function or stability is achieved by compensatory charge interactions between the mutant arginine (G347R) in the predicted TM9 of UNC-17, and a mutant acidic residue in a transmembrane domain of SUP-1, SNB-1, ERD-2.1, or ERD-2.2, as shown diagrammatically in A crystal structure of the chicken KDELR2 receptor has recently been determined , which are synaptic proteins normally residing in synaptic vesicle membranes and therefore capable of sustained interaction with UNC-17, ERD-2 proteins would be expected to shuttle between the endoplasmic reticulum and the Golgi apparatus in most or all tissues. Opportunities for interaction between these proteins and UNC-17 might be expected to be only transient, during early trafficking and maturation of UNC-17, and suppression of a synaptic protein by a modified ERD-2 is therefore surprising. Possibly, the proposed interaction increases the stability of the protein or allows correction of a defect in folding or post-translational modification. Alternatively, it is possible that the association of the two proteins allows some aberrant trafficking of mutant ERD-2 so that enough ends up in synaptic vesicles to permit functional suppression of UNC-17(G347R).unc-17(e245) animals are viable and fertile, albeit slow-growing and extremely uncoordinated. In contrast, unc-17(null) animals are inviable and die after hatching as immobile L1 larvae (unc-17(e245) (UNC-17(G347R) must retain a small amount of transporter activity, because unc-17(e245) mutants  background appeared possibly more intense than in completely wild-type animals  background, whereas the double knockdown is lethal, with similar effects in both wild-type and rrf-3 backgrounds. Many embryos die before hatching, and few animals develop beyond L1 larval stage. In contrast to the viability of erd-2.2(RNAi) in a wild-type background, RNAi knockdown of erd-2.2 in a sup-2 background resulted in lethality (erd-2.2(RNAi); erd-2.1(RNAi) and erd-2.2(RNAi); erd-2.1(V186E). Repeating these experiments in a rrf-3 background resulted in a small enhancement of lethality (data not shown). It remains possible that both erd-2.1(RNAi) and erd-2.1(V186E) retain a low level of ERD-2 receptor activity, insufficient to compensate for the loss of erd-2.2.We tested this possibility by carrying out RNAi knockdowns of kgrounds . We confe245 suppressors.These observations indicate that ERD-2.1(V186E) has lost most or all of its normal function, which would be consistent with the evidence for the essential importance of residues in helix 7. Nonfunctional KDEL receptors appear to be trafficked to compartments further along the secretory pathway, rather than being retrieved to the ER. It is therefore likely that ERD-2(V186E) gets similarly misdirected, which may allow sustained interaction between the abnormal ERD-2.1(V186E) and UNC-17(G347R), and consequent restoration of transporter function to UNC-17. If so, it is only by losing their normal function that ERD-2 proteins can take on a moonlighting role  as e245 C. elegans and most other animal species. In the hope of identifying some function uniquely provided by erd-2.1, we crossed erd-2.1(e997) onto an unc-17(+) background to generate strain CB7550, and compared various properties of this strain with the wild-type parental strain N2, but observed no obvious difference in size, mobility, growth rate, hermaphrodite fertility, dauer formation, male mating efficiency or sensitivity to heatshock or starvation (Supplementary Table S2).It is not obvious why ERD-2 function is shared between two redundant genes in We also tried to test the relative importance of the two genes by varying the input ratios of dsRNA-expressing bacteria in the double knockdown experiments, but observed the same levels of lethality when either of the RNAi feeding strains was provided in nine-fold excess.C. elegans  suppressor detection to explore the effect of different mutagens and to test whether EMS mutagenesis exhibits the same delayed fixation that had previously been shown for mutagenesis of T4 bacteriophage  would be expected to express a dominant suppressor mutation and therefore exhibit wild-type locomotion. Only one out of 29 suppression events detected gave rise to a clone of this size, and even this one may have been a double event. In principle, the results listed in The initial impetus for the work described in this study was to utilize the convenience of riophage . This waunc-93(e1500)  . ENU  has been previously elucidated for two of the suppressors, sup-8 , showing that either erd-2.1(V186E) or erd-2.2(V186E) can suppress.The molecular nature of the allele-specific suppression of sup-8/snb-1 and sup-1. In all three situations, suppression depends on the introduction of an acidic residue near the middle of a transmembrane domain, which should allow electrostatic charge interaction with the mutant basic residue in TM9 of UNC-17(G347R). This interaction may act to restore either stability or function or both, to the UNC-17 acetylcholine transporter. In the absence of suppression, levels of mutant UNC-17 are reduced, but it has been established that simple overexpression of UNC-17(G347R) does not correct the mutant phenotype  tagging of SUP-1 and UNC-17 was used to demonstrate close proximity of these proteins in synaptic vesicles, which is consistent with the model but does not prove sustained direct molecular interaction.  and erd-2.2(RNAi) indicates that ERD-2.1(V186E) has lost most or all of its normal function, because RNAi knockdown of erd-2.2 in an erd-2.1(V186E) background is lethal, whereas the same knockdown in a wild-type background has no effect. Redundancy between the two erd-2 genes allows suppression to occur without lethality. In contrast, the suppressing form of SNB-1 is compatible with its normal function as a synaptic exocytosis protein, because sup-8/snb-1(I97D) appears to be homozygous viable and normal, whereas snb-1(null) is lethal  can act as a suppressor at all: it may be that only by losing its normal function that this protein can be trafficked downstream and take on a new function of interacting with UNC-17. If so, the adoption of a novel function for ERD-2 comes with a cost, and is only possible because of the redundancy of lighting . Alternaerd-2.1(V186E) strain revealed no obvious differences from wild type, so the reason for the redundancy is unclear. Whether this apparent lack of a detectable phenotype is also true of erd-2.2(V186E) remains to be tested. Further experimentation on the C. elegans erd-2 genes is feasible and may allow detailed in vivo investigation of ER and Golgi function in this model system, as well as more stringent tests of apparent redundancy between erd-2.1 and erd-2.2. As shown in an extensive analysis (erd-2 genes, appears to have been maintained for many millions of years, despite the expectation of evolutionary loss or functional divergence.The presence of two, or sometimes three, paralogs of the KDEL receptor is almost universal in animal genomes, with rare exceptions such as Drosophila (Redundant or partly redundant gene families, both small and large, are a common feature of eukaryotic genomes. One incidental advantage of such redundancy may be that it enables a wider spectrum of mutational possibilities, by permitting survival of otherwise deleterious mutants, as in the present instance.A remaining question is whether the strong suppression effects described in this and previous papers (Nevertheless, even though none of these suppression effects may have relevance to the normal life of the organism, they may become important in a long-term context. Rare missense mutations, such as those we have described, may result in novel protein–protein interactions with unusual phenotypic consequences and thereby open up new realms of biology for evolutionary exploration.


Most of the human genome is transcribed to generate a multitude of non-coding RNAs. However, while these transcripts have generated an immense amount of scientific interest, their biological function remains a subject of an intense debate. Understanding mechanisms of action of non-coding RNAs is a key to addressing the issue of biological relevance of these transcripts. Based on some well-understood non-coding RNAs that function inside the cell by interacting with other molecules, it is generally believed many other non-coding transcripts could also function in a similar fashion. Therefore, development of methods that can map RNA interactome is the key to understanding functionality of the extensive cellular non-coding transcriptome. Here, we review the vast progress that has been made in the past decade in technologies that can map RNA interactions with different sites in DNA, proteins or other RNA molecules; the general approaches used to validate the existence of novel interactions; and the challenges posed by interpreting the data obtained using the interactome mapping methods. Even though most (97–98%) of the human genome sequence does not encode exons of protein-coding genes, most of it is transcribed to generate a plethora of apparently non-coding long and short RNAs in a phenomenon referred to as “pervasive transcription” . In factDrosophila dosage compensation system being one of the best understood from both biochemical and genetic perspectives.Nonetheless, the past decade has seen remarkable progress in understanding molecular mechanisms of functions of non-coding RNAs, particularly in the area of mapping intermolecular interactions between these transcripts and other molecules. Uncovering such interactions could likely hold the key to figuring out the mechanisms of function of non-coding transcripts and potentially their biological relevance. The conceptual foundation of this assumption is, at least in a large part, rooted in the pioneering work of multiple groups that studied mechanisms of dosage compensation of genes located on sex chromosomes. Animals, where females have two X chromosomes and males have only one, change expression levels of most of X-linked genes to achieve gene dosage parity between the two genders . Non-codDrosophila males upregulate the X-linked genes via action of Male-Specific Lethal (MSL) complex that binds to hundreds of specific, well-characterized sites on the X chromosome  of the Drosophila MSL2  on the X-chromosome to be inactivated  spliced non-coding RNA ctivated  and remactivated  leading ctivated  via targromosome  [revieweromosome ].Altogether, the dosage compensation lncRNAs provided a paradigm of how at least a fraction of the dark matter RNAs might function: targeting of specific proteins or protein complexes, such as chromatin modifiers for example, to specific locations in the genome and modulating gene expression by creating subcellular compartments and/or changing local chromatin environment . Combinein vivo cross-linked  and fragmented chromatin with an antibody to a protein of interest. The major difference is that instead of an antibody, several pioneering RNA centric interactome mapping techniques such as ChIRP , CHART ication, ], RAP  and CHIication,  relied oication, ; Table 1The original techniques that used the oligonucleotide-based enrichment strategy focused on identification of DNA regions that interacted with different lncRNAs of interest. However, later this strategy was also adapted to identify protein [CHART-MS, ; ChIRP-MOn the other hand, usage of psoralen-based crosslinkers can create reversible interstrand crosslinks in nucleic acid helices , thus alA number of more recent RNA-centric techniques are built on a promising proximity labeling technology based on the ability of a peroxidase to generate biotin-phenoxyl radicals in presence of biotin-phenol and hydrogen peroxide ; Table 1in vivo by creating peroxidase fusions with catalytically dead (d) Cas13 enzymes and transfecting constructs encoding the fusion and the targeting guide RNAs into live cells  oligonucleotides with the melting temperatures in the 55–60°C range and sparsely spaced (every 500 nt) in the target RNA . On the The COMRADES methodology  that comOn the other hand, the global methods can provide a very broad view of RNA-interactome highly desirable for the systems-based studies, albeit with likely reduced sensitivity for specific transcripts . HoweverHowever, the additional bioinformatic challenges are not limited to mapping of the chimeric reads and extend to all downstream aspects of the analysis since these global methods generate information whose structure is intrinsically much more complex compared to that of the RNA-centric methods. Therefore, to address the issues of dealing with mapping of the chimeric reads and other downstream analytical and interpretational challenges, some of the groups that develop global methodologies also make publicly available corresponding suites of bioinformatics methods that would allow users to analyze their own data, such as, for example, MARIO tools for the analysis and visualization of the MARIO data .in vivo RNA-interactome mapping techniques that rely on CRISPR/dCas13 . Strong enrichment of the detected interaction sites for these lncRNAs on the X chromosomes compared to the autosomes was demonstrated by ChIRP  RNA to specific site on ribosomal (r) RNAs to mediate site-specific RNA modifications, known sites of interactions between the rRNAs and spliced mRNAs in the context of ribosome, and interactions of small nuclear (sn) RNAs components of spliceosome with each other or with pre-mRNAs, among others. For example, RIC-seq could detect specific enrichment of binding of U58A and U74 snoRNAs at their known binding sites on the 28S rRNA . Likewisin vivo RNA-centric proximity labeling method RPL (RNA proximity labelling) where U1 snRNA was targeted by dCas13 fused to APEX2  also based on dCas13, but instead of APEX2, fused to a biotin ligase   . Combinehodology . RNA/DNAchnology . A combiy CARPID   genes could be found by all 3 techniques  using CHIRT technology. The authors have depleted TERRA transcripts using antisense oligonucleotides and found that expression levels of the 914 mouse genes containing binding sites of these non-coding transcripts were affected more significantly, either up- or down-regulated, than the 15,871 control genes without the binding sites (NEAT1 lncRNA on the fate of transcripts found to interact with that lncRNA using the proximity labeling HyPro-seq methodology. They found that the transcripts that interacted with the lncRNA did have statistically-significant trend to be downregulated compared with the ones that did not, however, the authors did not comment on the actual numbers of transcripts used in the analysis (Three studies attempted to analyze genome-wide effects on the interactome of specific lncRNA transcripts following their genetic depletion. The study by ng sites . The stuanalysis .The above-mentioned study by Mapping RNA interactome is a key to understanding molecular mechanisms of action of the RNA dark matter. In addition, deciphering interactome of both non-coding and protein-coding transcripts is also crucial to fully understand intricate details of the spatial organization, functioning and regulation of various subcellular compartments of the cell. It can also help us to better appreciate the molecular mechanisms responsible for generation of aberrant transcripts that are common in malignant states. Tremendous progress has been done in developing multiple methods to map RNA interactions at different levels. However, the abundance of data obtained with these technologies also naturally brings with it challenges in interpreting this information. Thus, comprehensive elucidation of the properties of mapped RNA interactions, such as for example, estimates of the distances between the interacting molecules mapped by the different methods and identification of biologically relevant RNA interactions, are critical for our appreciation of the complexities of the function and regulation of RNA dark matter, protein coding mRNAs and ultimately the cell.


Following publication of the original article , the autIncorrect:4Shanghai TCM-Integrated Institute of Vascular Anomalies, Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200082, China.Correct:1Experiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.4Shanghai TCM-Integrated Institute of Vascular Anomalies, Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200082, China.


Caenorhabditis elegans on its natural microbiota improves its fitness and immunity against pathogens. Although C. elegans is known to exhibit choice behavior and pathogen avoidance behavior, little is known about whether C. elegans actively chooses its  microbiota and whether the microbiota influences worm behavior. We examined eleven natural C. elegans isolates in a multiple-choice experiment for their choice behavior toward four natural microbiota bacteria and found that microbiota choice varied among C. elegans isolates. The natural C. elegans isolate MY2079 changed its choice behavior toward microbiota isolate Ochrobactrum vermis MYb71 in both multiple-choice and binary-choice experiments, in particular on proliferating bacteria: O. vermis MYb71 was chosen less than other microbiota bacteria or OP50, but only after preconditioning with MYb71. Examining escape behavior and worm fitness on MYb71, we ruled out pathogenicity of MYb71 and consequently learned pathogen avoidance behavior as the main driver of the behavioral change toward MYb71. The change in behavior of C. elegans MY2079 toward microbiota bacterium MYb71 demonstrates how the microbiota influences the worm’s choice. These results might give a baseline for future research on host–microbiota interaction in the C. elegans model.In comparison with the standard monoxenic maintenance in the laboratory, rearing the nematode  Caenorhabditis elegans has been extensively used as a research model and is usually kept in monoxenic culture with the Escherichia coli strain OP50 as food. This is in stark contrast to C. elegans natural environment  where the nematode lives in close association with a huge variety of microbes  were grown for 24 h at 25°C on 9-cm nematode growth medium (NGM) plates. The lawns were scraped off, pooled from five plates, and pelleted at 4,000 g at 4°C for 15 min, and 100 µl of bacterial pellet was resuspended in 1 ml of RNAmagic . Aliquots of 800 µl were frozen in liquid nitrogen, thawed at 45°C and frozen in three repeated cycles, and stored at −80°C until RNA isolation. Total RNA was isolated using MACHEREY-NAGEL  NucleoSpin Kit using the protocol for bacterial cells.Bacterial lawns , and 25 µl of each bacterium and a PBS control were pipetted equidistantly in a circle onto 9-cm peptone-free NGM (PFM) plates or NGM plates and left to dry for 2 h. Approximately 100 synchronized C. elegans in the fourth larval stage (L4) were pipetted to the center of the plate. The number of worms residing on each bacterium was determined after 2 or 24 h. We calculated the mean proportion of worms per bacterium = number of worms on a bacterium/total number of worms on all bacteria per plate.For the multiple-choice experiments, four microbiota bacteria and OP50 were adjusted to ODC. elegans was grown on OP50 until the L4 stage, washed three times in sterile M9 buffer, and pipetted to preconditioning plates freshly inoculated with one bacterium in OD60010. Preconditioning was performed with live and heat-killed (80°C for 40 min) MYb71 and OP50, with OP50 lawns spiked with 21 ng of total RNA of MYb71 or OP50, or with the odor of viable MYb71 or OP50. For the latter, L4 worms were placed on OP50 lawns with either 500 µl MYb71 or OP50 on a thin NGM layer in the lid of the plate. Lining the edge of the plate with 1% palmitic acid in ethanol kept the worms on the OP50 lawn. After 24 h, the preconditioned adults were washed repeatedly in M9 buffer and subsequently applied to binary-choice assay plates.Approximately 70 naïve L4 worms or preconditioned adults were pipetted centrally between two opposing 30-µl bacterial spots on 6-cm NGM plates. The number of worms residing on each bacterium was determined after 2 and/or 24 h. We calculated a choice index = (number of worms on the bacterium opposing the microbiota bacterium − number of worms on the microbiota bacterium)/. To test for bacterial signals produced upon contact with worms, the initially placed worms were removed after 24 h, and naïve adult worms (from OP50) were pipetted centrally onto the same plates. The choice index for the newly introduced worms was determined after 2 h .C. elegans MY2079 L4 worms were preconditioned on MYb71 or OP50 for 24 h. Adults were washed repeatedly in M9 buffer, and approximately 50 adults were pipetted onto NGM plates inoculated with 50 µl of either MYb71 or OP50. The number of worms on and outside the bacterial lawn was scored after 2 h. We calculated the proportion of escaped worms = number of worms outside the lawn/total number of worms on the plate.Synchronized 60010 adjusted in PBS and stored at 20°C for 24 h. Initially, one L4 worm was picked onto the plate and transferred daily to a new plate. We scored the hatched offspring of each worm until the worm stopped laying eggs. Data of worms that died or escaped from the plate before the end of the egg-laying period were excluded.NGM and PFM plates were inoculated daily with 50 µl MYb71 or OP50 at ODStatistical calculations were performed with R studio software (version 1.3.1093) and can be found in E. coli OP50 as a food source. Natural C. elegans isolates can differ in their behavioral response to bacterial cues . We confirmed the results of the screen for MY2079 with an additional multiple-choice experiment using a higher replication (n = 15), in which not only MY2079 (p = 0.012) but this time also N2 (p = 0.008) showed choice behavior after 24 h. Yet the choice behavior between MY2079 and N2 differed significantly   but not after 2 h, whereas C. elegans N2 showed generally no choice behavior on NGM  and 24 h  . These results suggest that the change in choice behavior toward MYb71 over time is specific for C. elegans MY2079 and is caused by avoidance of proliferating MYb71.We noticed in the multiple-choice experiment on proliferating bacteria that MY2079 changed its choice behavior toward MYb71 and OP50 over time and eventually avoided MYb71 in favor of OP50 (C. elegans MY2079 toward MYb71 in OD60010 and OD60030 (directly adjusted from a liquid culture) and toward MYb71 lawns grown on a plate for 2 or 24 h. The latter was done for L4 larvae and adults to examine developmental influences. Both L4 larvae (p < 0.001) and adults (p < 0.001) chose the 24 h MYb71 lawn over the 2 h lawn (p = 0.003) and MY2079 (p = 0.014) chose MYb71 at OD60030 over OD60010  bacterial proliferation led to an increase in cell density and therefore higher concentration of bacterial products after 24 compared with 2 h. 2) At the same time, the worms developed from the L4 stage to the adult stage. We therefore compared the attraction of C. elegans prefers a higher MYb71 cell density in direct comparison with a lower MYb71 cell density independent of the developmental stage. However, in the presence of an alternative bacterial lawn, the MYb71 lawn after 24 h is less attractive .Bacterial communities are able to react to their environment, including being grazed on by bacterivores. esponses . These tThese findings suggest that the production of a repellent bacterial product triggered by exposure to worms is rather unlikely.p < 0.001; As we did not observe a late microbiota avoidance response in naïve worms but in worms that have likely fed on MYb71, we hypothesized that worms had to be exposed to MYb71 to show the late microbiota avoidance response. Therefore, we preconditioned worms with MYb71 or OP50, i.e., exposed L4 worms for 24 h to either MYb71 or OP50, and subsequently performed a binary-choice experiment scoring behavior only after 2 h. Interestingly, we found the late microbiota avoidance response in preconditioned worms as in previous assays after 24 h, whereas worms preconditioned with OP50 did not show the late microbiota avoidance response . Preconditioning with MYb10 had no effect on choice behavior, and MYb10 and OP50 were always chosen equally , but OP50 was even more preferred in worms preconditioned with MYb237 , whereas worms preconditioned with OP50 chose OP50 and MYb49 equally in two out of three runs  and heat-killed MYb71 (p = 0.011) chose OP50 over MYb71 (p = 0.022). Worms from OP50 chose MYb71 and OP50 equally, independent of the preconditioning.To answer the question of whether These results indicate that the late microbiota avoidance response is not caused by total bacterial RNA nor bacteria-derived odors but primarily by the worm’s colonization with viable MYb71.C. elegans toward its natural microbiota. We found that the natural C. elegans isolate MY2079 avoided specifically the microbiota isolate O. vermis MYb71 during a second exposure.In the present study, we examined the choice behavior of the bacterivore nematode C. elegans MY2079 toward O. vermis MYb71 only either over time or during a second encounter. This behavior is reminiscent of the learned avoidance behavior in C. elegans against the pathogenic P. aeruginosa PA14 . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


They rendered this process programmable, linking the presence of virtually any RNA to cutting of matching DNA by Cas9. This capability is the basis of a new CRISPR diagnostic method developed by the authors that can detect many biomarkers at once. Named LEOPARD, this method can detect, for example, RNAs from severe acute respiratory syndrome coronavirus 2 and other viruses, thereby translating a new CRISPR discovery into a powerful diagnostic tool.The Cas9 nuclease widely used for genome editing is derived from natural bacterial defense systems that protect against invading viruses. Cas9 is directed by RNA guides to cut matching viral DNA. Jiao Science, abe7106, this issue p. 941; see also abi9335, p. 914 Cas9 guide RNAs can be derived from cellular RNAs, inspiring a multiplexable diagnostic platform. Campylobacter jejuni, we discovered tracrRNA hybridizing to cellular RNAs, leading to formation of “noncanonical” crRNAs capable of guiding DNA targeting by Cas9. Our discovery inspired the engineering of reprogrammed tracrRNAs that link the presence of any RNA of interest to DNA targeting with different Cas9 orthologs. This capability became the basis for a multiplexable diagnostic platform termed LEOPARD . LEOPARD allowed simultaneous detection of RNAs from different viruses in one test and distinguished severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its D614G (Asp614→Gly) variant with single-base resolution in patient samples.CRISPR-Cas systems recognize foreign genetic material using CRISPR RNAs (crRNAs). In type II systems, a trans-activating crRNA (tracrRNA) hybridizes to crRNAs to drive their processing and utilization by Cas9. While analyzing Cas9-RNA complexes from  CRISPR-Cas immune systems degrade foreign genetic material through the guidance of CRISPR RNAs (crRNAs) (Campylobacter jejuni NCTC11168 (CjeCas9) revealed crRNA-guided RNA targeting by CjeCas9 (C. jejuni strain CG8421 harboring only two spacers in its endogenous type II-C CRISPR-Cas system (Our prior work interrogating RNAs bound to Cas9 from s system . Motif #p = 3 × 10−7)  . However × 10−7) , likely fliF and dctA mRNAs) matched those found in CG8421 . Although cas9 deletion did not significantly perturb FliF protein concentrations in vivo under standard growth conditions (fig. S5), deleting the CRISPR array in NCTC11168 increased levels of the fliF RNA fragment (fig. S4C). Finally, the fliF RNA fragment was a processing product, as confirmed with Terminator exonuclease treatment (C. jejuni NCTC11168 and likely exist in other C. jejuni strains on account of the shared tracrRNA binding site in fliF (fig. S6).These crRNA-like RNAs raised the question of whether these same RNAs were present in our prior RIP-seq analysis with strain NCTC11168  (fliF ncrRNA given its presence in both C. jejuni strains and detection by Northern blotting. Applying this assay to the tracrRNA and mRNA comprising the entire fliF coding region (1683 nts) (p = 5.4 × 10−5). Expressing the equivalent crRNA reduced GFP levels 15.1-fold compared with the nontargeting control. The reduced GFP silencing for the fliF mRNA versus the crRNA potentially reflects not only reduced targeting efficiency but also delayed complex formation. Overall, the TXTL results offer evidence that mRNA-derived ncrRNAs can direct DNA targeting by Cas9.To evaluate ncrRNA-dependent targeting, we exploited a cell-free transcription-translation (TXTL) assay previously used to characterize CRISPR-Cas systems (683 nts) , we founfliF mRNA in TXTL could be due to how an ncrRNA deviates from a standard crRNA. These deviations include the crRNA repeat sequence, the secondary structure of the duplex formed with the tracrRNA anti-repeat, and 5′ or 3′ extensions to the repeat that do not undergo efficient processing. To evaluate these deviations, we systematically mutated or extended the standard crRNA, either as a single guide RNA (sgRNA) to ensure duplex formation or as a crRNA:tracrRNA pair, and evaluated GFP silencing in TXTL  yielded a >twofold reduction in GFP reporter levels compared with a nontargeting crRNA control (p < 0.001). Furthermore, targeting was directed specifically through the predicted ncrRNA, as mutating the “seed” region of the putative ncrRNA , likely due to low ncrRNA abundance compared with the strain’s crRNAs under the examined growth conditions. For E. coli, overexpressing the dctA mRNA, CjeCas9, and the tracrRNA led to moderate (15.5-fold) clearance of a transformed plasmid with the putative dctA ncrRNA target (p = 0.0036), but not when the tracrRNA anti-repeat was scrambled (1.6-fold) (p = 0.068) (fig. S9B). We therefore conclude that ncrRNAs derived from mRNAs can elicit DNA targeting in both in vivo and cell-free systems.Beyond TXTL, we assessed ncrRNA function as part of DNA targeting in Streptococcus pyogenes Cas9 (SpyCas9) can be extensively modified as long as the secondary structure is maintained . What if the tracrRNA anti-repeat sequence could be changed to hybridize to other RNAs while maintaining the appropriate structure for Cas9 recognition? If so, then the resulting reprogrammed tracrRNA  could specifically derive an ncrRNA from a cellular RNA. The resulting ncrRNAs can then guide Cas9 to matching DNA targets . AlthougfliF sgRNA while preserving the secondary structure  exhibiting at most modest GFP silencing in TXTL (p = 1 × 10−6 to 0.0011), even if repression was not as strong as with the canonical crRNA:tracrRNA pair (p = 6 × 10−7 to 0.002). Notably, mutating the predicted seed region, scrambling the tracrRNA anti-repeat, or replacing CjeCas9 with FnCas12a restored GFP expression (Neisseria meningitidis (CjeCas9 recognizes a perfect RNA duplex formed between the crRNA repeat and tracrRNA anti-repeat (fig. S2B) . Therefos26-s31, . GFP sils26-s31, . Next, wRNA pair . FinallyRNA pair . Startinpression . NortherStreptococcus pyogenes Cas9 (SpyCas9) and the Streptococcus thermophilus CRISPR1 Cas9 (Sth1Cas9) as examples. In both cases, we devised design rules for Rptrs based on the known secondary structure of the crRNA:tracrRNA duplex and the preference of RNase III to cleave double-stranded RNA with AT-rich sequences (fig. S10A) (p = 1 × 10−7 to 1 × 10−4) . The targeted plasmid was efficiently cleared even when expressing the sensed mRNA at low levels (fig. S12A) or when deleting RNase III (fig. S12B). Overall, the tracrRNA for different Cas9 orthologs can be converted into Rptrs to elicit DNA targeting based on the presence of a selected cellular RNA.Given the functionality of CjeCas9 Rptrs, we asked whether tracrRNAs for other Cas9 homologs can be similarly reprogrammed. We selected the well-characterized  × 10−4) . As befoBy linking DNA targeting to an RNA of interest, Rptrs offer a valuable opportunity for RNA detection and a different paradigm for CRISPR diagnostics. Current CRISPR diagnostics principally rely on Cas12a or Cas13 searching for double-stranded DNA or RNA targets in a sample, where target recognition elicits nonspecific single-stranded DNA or RNA cleavage of a fluorescent reporter .To begin assessing LEOPARD, we performed a simplified in vitro reaction using T7-transcribed RNAs, commercially available SpyCas9 protein, and linear DNA targets (fig. S13A). We began with RNA corresponding to one of the synthetic ncrRNA loci within CJ8421_04975  mutation in the spike protein of SARS-CoV-2 served as an example, as it comprises a single base change (A23403G) that increased infectivity and drove global spread . As this sensitivity would be sufficient for detecting SARS-CoV-2 RNA in patient samples, we applied LEOPARD to evaluate samples confirmed positive or negative for SARS-CoV-2 by RT-qPCR  and in vitro transcription similar to Cas13-based diagnostics . ApplyinC. jejuni, we discovered that cellular transcripts can be the source of noncanonical crRNAs through hybridization with the tracrRNA. This discovery adds ncrRNAs to the list of RNA guides found in nature, including crRNAs, scaRNAs that similarly pair with the tracrRNA anti-repeat, and “natural” sgRNAs formed through upstream transcription of the tracrRNA (C. jejuni. Future studies therefore could help clarify whether ncrRNAs derived from outside CRISPR arrays are spurious off-target products that are tolerated by the host or if they confer yet-to-be-discovered functions extending beyond adaptive immunity.Starting from the characterization of a native CRISPR-Cas9 system in the bacterial pathogen We further demonstrated that Rptrs can link the presence of an RNA of interest to sequence-specific DNA targeting by Cas9. This capability could enable in vivo applications with Cas9 such as multiplexed transcriptional recording or transcription-dependent editing. The most immediate application involved multiplexed RNA detection in vitro through LEOPARD. LEOPARD adds to the existing CRISPR diagnostic platforms principally based on Cas12a or Cas13 (While systematically perturbing the standard crRNA:tracrRNA duplex, we found that many deviations–particularly outside of the 5′ end of the repeat–were tolerated by Cas9 and still led to targeting of designed DNA targets. However, despite this promiscuity, targeting is still determined by the upstream guide sequence and the requirement for a flanking PAM. Thus, both anti-repeat hybridization and guide-dependent DNA targeting may limit off-targeting activity. Although we did not observe any detectable off-targeting in vitro or in vivo, future work could devise design rules for Rptrs that account for potential off-targeting as well as on-target activity, similar to existing sgRNA design algorithms (


In the accept–reject task, people are presented 50–50 gambles offering a monetary gain and a loss and asked whether they accept or reject the opportunity to play. For example, consider a 50–50 chance to win $20 or lose $10. If people reject this gamble, we say that they are loss averse, because the $10 loss is looming larger than the $20 gain. We agree that the approach taken in André and de Langhe reanalyzed data from Here we present a model-free analysis on those same common gambles, which leads to a rather different conclusion. We measure the effect of our range manipulation by simply counting the proportion of accept choices for the gambles that are common across experimental conditions . Furthermore, the choice proportion pattern is not consistent with the three alternative mechanisms that André and de Langhe propose .The limitation of using choice proportions is that people’s willingness to accept mixed lotteries cannot be attributed to loss aversion alone. One could argue that the differences described above are a product of variation in a bias to accept or reject mixed lotteries—a general tendency to reject lotteries without asymmetric weighting of gains and losses. For example, one cannot tell whether the tendency to reject a 50–50 chance to win $20 or lose $10 is because the loss of $10 looms large due to loss aversion or is because of a bias to reject all mixed gambles, irrespective of the exact gain and loss on offer. Parenthetically, we do not think the effect should be dismissed as a status quo bias, where people prefer the status quo of not playing the gamble. Although it is an empirical question, we think people would still be averse to playing these mixed gambles even if they are presented as an active choice between the gamble or zero, rather than as an acceptance of the gamble. Further, we do not think the effect should be dismissed because it could be a bias rather than loss aversion. What is required is a model to explain why the acceptance rates for these gambles are so strongly affected by the range of gains and losses on offer. Only a model where the wider experience of gains and losses affects the decision to accept the gain/loss pair in a specific question, such as DbS, can do this.In the second part of this reply, we summarize our recent work showing how bias and loss aversion cannot be reliably estimated using responses on the accept–reject task.In the second part of our reply, we consider loss aversion as operationalized by prospect theory’s λ. This null result can be attributed to the poor recoverability of the λ parameter. Simulation and recovery analyses have shown that this is the least reliable parameter within prospect theory . In our We also share André and de Langhe’s concerns about comparing λ estimates across different choice sets. Here we show that André and de Langhe’s measurement invariance critique of λ estimates is a special case of a much more serious model recovery problem. We take the same approach as The results are shown in The failure of λ to generalize across even random splits of the choice set is not due simply to the stochasticity of responses. The green (light gray) distribution see  shows thThus, the argument made by André and de Langhe attribute the problem in The insight here also explains why André and de Langhe were able to make loss aversion to disappear and reverse in their simulation of three models. What all these models had in common was that they incorporated some departure from prospect theory. Thus, the data generated from these models created an omitted variable problem for the version of prospect theory being used to recover λ, which had differential effects in choice sets with different ranges of gains and losses.We agree with André and de Langhe that it is not appropriate to estimate prospect theory’s λ from different choice sets. Here we show a much more general problem: λ does not generalize across even random splits of a choice set. Thus, Walasek and Stewart’s error was in assuming that the λ parameter could be used to abstract something of an individual’s differential sensitivity to gains and losses from different choice sets—it cannot. Since the publication of the 2015 paper, Walasek and Stewart have made this point very clear in two publications , 2021. IWe have demonstrated a large and reliable effect of range manipulation on people’s willingness to accept or reject mixed gambles. There are very large differences in acceptance rates for the gambles that are common between different conditions in the design used by In sum, the tendency to reject 50–50 mixed gambles can be made to disappear or reverse. This was predicted in advance by decision by sampling but not prospect theory. It is now less clear how this tendency should be decomposed into loss aversion and a bias toward rejecting mixed gambles. These individual mechanisms cannot be separately or reliably estimated from people’s choices in the accept–reject task .


Fused in sarcoma/translocated in liposarcoma (FUS/TLS) is a multitasking RNA/DNA binding protein. FUS aggregation is implicated in various neurodegenerative diseases. RNA was suggested to modulate phase transition of FUS. Here, we found that FUS transforms into the amorphous aggregation state as an instant response to the shear stress caused by usual pipetting even at a low FUS concentration, 100 nM. It was revealed that non-coding RNA can suppress the transformation of FUS into aggregates. The suppressive effect of RNA on FUS aggregation is sequence-dependent. These results suggested that the non-coding RNA could be a prospective suppressor of FUS aggregation caused by mechanistic stress in cells. Our finding might pave the way for more research on the role of RNAs as aggregation inhibitors, which could facilitate the development of therapies for neurodegenerative diseases. FUS has been considered as a molecular link between apparently different human diseases such as cancer and neurodegenerative diseases11. FUS was found as the major component of nuclear polyglutamine (polyQ) aggregates in a Huntington disease (HD) cell model8, where FUS was converted from a soluble form to insoluble aggregates9. Then, FUS was also found to be a member of the PolyQ aggregates in other diseases including spinocerebellar ataxia (SCA) types 1, 2, and 3, and dentatorubral-pallidoluysian atrophy (DRPLA)7. Around the same time, FUS mutations were found in amyotrophic lateral sclerosis (ALS)11 and frontotemporal lobar degeneration (FTLD) patients12. Those mutations were found to accelerate the FUS transition into an insoluble form13. Although the above-mentioned neurodegenerative diseases have different manifestations, FUS aggregation is associated with all of them5, which suggests a common pathway for their neuropathologies.Fused in sarcoma/translocated in liposarcoma (FUS/TLS) is an RNA/DNA binding protein, which regulates various biological processes15. The implication of mutations of the RNA-binding domain of FUS in the etiologies of neurodegenerative diseases suggests that the RNA binding ability of FUS is necessary to maintain neuron functionality. Therefore, FUS is considered as an emerging therapeutic target for neurodegenerative diseases as well as cancer prevention and treatment16.Dysregulation of RNA metabolism is a major cause of various human diseases20. It was found that dynamic liquid-like FUS-containing droplets yielded by liquid–liquid phase separation (LLPS) play a key role in the assembly of membrane-less organelles such as stress granules21. It was also found that high concentration of RNA can suppress LLPS of FUS18. It was noted that in physiological conditions, FUS can interchange between a dispersed phase, liquid droplets, and a reversible gel, while through aging or pathological conditions, liquid droplets can be converted into irreversible gels and fibrils22.FUS is known to take on different states such as dispersed, liquid droplet, gel, and fibril ones depending on factors such as pH, ionic strength, protein concentration, thermal stress, shear stress, and RNA presence24.FUS consists of a low complexity domain (LC domain), three arginine-glycine-glycine-rich domains (RGG domains), an RNA recognition motif (RRM), and a zinc-finger domain (ZnF domain). Only the RRM and ZnF domains are structured, the others being regarded as intrinsically disordered regions (IDRs). Previously, we showed by fluorescence resonance energy transfer (FRET) and high-speed atomic force microscopy (HS-AFM) analyses that FUS takes on a compact conformation in its free-form but becomes extended upon binding to RNA/DNAIn this study we found that mechanistic shear stress caused by pipetting can induce FUS aggregation by means of fluorescence spectroscopy, fluorescence microscopy, and transmission electron microscopy (TEM). Then, we revealed the difference in the suppressive effect on the FUS aggregation between FUS-binding non-coding RNA and irrelevant RNA.CCND1), by FUS in response to DNA damage25. We showed that a long non-coding RNA that is transcribed from the promoter region of CCND1, which was named promoter-associated non-coding RNA (pncRNA), can induce a conformational change of FUS. This conformational change enables FUS to interact with transcriptional coactivators, p300/CBP, and suppress their histone acetyl transferase activity. This leads to CCND1 transcription suppression and subsequent cell cycle arrest, which may provide the time needed for DNA damage repair. We used FRET assaying to detect the effect of pncRNA on the conformational change of FUS23. FUS fusion protein with blue fluorescence protein (BFP) and green fluorescence protein (GFP) attached to its N- and C-termini, respectively, was used for the FRET assays. In that study, we noticed that upon sample pipetting, both the BFP and GFP fluorescence intensities decreased. To examine the effect of pipetting more quantitatively, 45 strokes of pipetting were applied to a FUS protein sample and fluorescence spectra were measured every three strokes of pipetting   (data not shown).Pipetting can subject protein molecules to shear stress due to the velocity gradient; shear stress is most prominent for molecules close to the surface of the pipette tip2 was counted. More FUS particles were formed as the number of strokes of pipetting increased -GFP-FUS, was constructed in order to exclude the effects of MBP and BFP on FUS aggregation. We prepared four protein samples with different numbers of strokes of pipetting . Samples were prepared by diluting the stock protein solution 5 times with 3 gentle strokes of pipetting to get a thoroughly mixed protein solution of 100 nM. For the P0 sample, no further pipetting was applied. The P15, P30, and P45 samples underwent a further 15, 30, and 45 strokes of pipetting, respectively. All samples were examined by fluorescence microscopy. The number of particles larger than 0.002 mmNext, we investigated the appearance of the pipetting-induced FUS aggregates by TEM to determine whether the formed aggregates are amorphous or take on a particular structure such as amyloid fibrils. A protein sample was examined before pipetting, the P0 sample Fig. a, and af24. Interestingly, this time we found that the reduction in the fluorescence intensity caused by shear stress on pipetting was not observed when full-length pncRNA was added to the FUS fusion protein  and fragments of pncRNA , where E = IGFP/IGFB + IBFP, and IBFP and IGFP are the fluorescence intensities at 453 nm and 506 nm, respectively. As the 31-mer fragment of pncRNA  showed that shear stress can induce the formation of amyloid fibrils from SOD1 monomers, while under static conditions there is no change in the monomer state34. Therefore, it is possible that shear stress caused by pipetting induced the transition to the amorphous aggregate state.In this study, we demonstrated that the usual manner of pipetting can induce aggregation of FUS protein. FUS aggregates were visualized by TEM as being amorphous. The more the number of strokes of pipetting is, the more the number of aggregates is. We assumed that the shear stress caused by pipetting is a driving force for the formation of aggregates. The shear stress on the protein structure and the subsequent induction of aggregation such as amyloid fibril formation have been studied for decades35. The decrease in the fluorescence intensity of the FUS fusion protein was observed as an instant response to the pipetting, occurring in less than 60 s , which has an important function in coagulation. It was suggested that high shear stress at the site of bleeding injury could induce a structural change in vWF, which is critical for platelet adhesion and thrombus formation at the wound site38. Moreover, at the cellular level, the velocity of organelles inside cells is not uniform. Therefore, a velocity gradient arises, which in turn creates shear stress on proteins inside the cells.The biological significance of the conformational change caused by shear stress has been suggested. In vivo, blood flow in narrow capillaries can induce considerable shear stress in the circulatory system18. Low RNA/FUS ratios promote the formation of droplets due to LLPS, whereas high ratios prevent the droplet formation in vitro. Reduction of nuclear RNA levels or genetic ablation of RNA binding causes the formation of cytotoxic solid-like assemblies in cells18. So far, on the other hand, an effect of RNA on the shear-mediated formation of solid fibers of FUS from the liquid–liquid phase separated form has not been reported in the literature. Here, we showed that full-length pncRNA and its fragments, R31 and R13, can protect FUS from aggregation caused by shear stress on pipetting , a ZnF domain (423–453), and the third RGG domain (454–526)25. Therefore, there is the possibility that RNA bound to the C-terminal region of FUS masks the interface required for the formation of aggregates, resulting in the prevention of aggregate formation. It was also reported that the cation-π interaction between the N-terminal LC domain and C-terminal RGG domain is critical for LLPS of FUS40. Therefore, it is also likely that RNA bound to the C-terminal region of FUS neutralizes the cations and reduces the cation-π interaction. The reduction of the interaction may prevent FUS not only from LLPS but also from aggregation. Specific RNAs bind to FUS with higher affinity than non-specific ones. This can explain why the suppressive effect on aggregation of FUS is RNA sequence-dependent. It might also be the case that non-specific RNA does not necessarily bind to the interface needed for the formation of aggregates, resulting in a lower suppressive effect. The correlation between the extent of conformational change of FUS caused by each RNA, which was estimated by ΔE, and resistance to aggregation by each RNA may also imply that the FUS conformation induced by RNA is unfavorable for the formation of aggregates. It would be added that TEM images of aggregates of FUS in the presence of U13 looked different from those of FUS alone. This may be due to involvement of U13-bound FUS to some extent in aggregates in the former case.It was reported that the prion-like domain (residues 1–239) comprising the LC domain and a part of the first RGG domain in the N-terminal region and the second RGG domain (374–422) in the C-terminal region are essential for aggregation41. Fusion of GFP to FUS is widely used for marking FUS even in the studies of the FUS-RNA interactions42, which indicates that GFP is not supposed to interact with RNA. Additionally, BFP whose sequence similarity with GFP is 93% is not supposed to interact with RNA, either.It should be added that the FUS-RNA interaction was not likely to be affected by the presence of MBP, GFP, and BFP. MBP has no RNA binding activity43. The suppressive effect of NaCl is suggested to be common to LLPS and aggregation of FUS.The recovery of the florescence intensity of FUS on pipetting with 300 mM NaCl Fig.  indicateIn conclusion, we found that the shear stress caused by pipetting instantly induces the transition of FUS to amorphous aggregates even at low FUS concentration. The non-coding RNA we previously identified, pncRNA, can suppress this transition in a sequence-dependent manner. Our finding might serve for the development of therapies for neurodegenerative diseases by using RNA as aggregation inhibitors.24. Briefly, the fusion protein was expressed in BL21 Gold (DE3) Escherichia coli cells. The protein was induced by the addition of 0.1 mM isopropylthio-β-d-galactopyranoside (IPTG) for 20 h at 20 °C. Cell pellets were sonicated in lysis buffer comprising 50 mM Tris–HCl (pH 7.6), 25 mM glucose, 1% CHAPS, 10 mM benzamidine, 5 U/mL DNase I, 1 mg/L RNase, and 0.2 g/L lysozyme. The supernatants were purified by nickel-affinity column chromatography using Ni-sepharose beads , followed by size exclusion chromatography (SEC) using a HiloadTM 16/60 SuperdexTM 200 prep grade column (GE Life Sciences). Protein was stored at 4 °C. 5 mM fresh dithiothreitol (DTT) was added to a purified fusion protein solution on the same day as the experiment. The protein sample was diluted five times to obtain ~ 100 nM FUS fusion protein in 10 mM Tris–HCl (pH 7.6), 5 mM glucose, 0.2% CHAPS, and 50 mM NaCl. This fusion protein was used for FRET assaying and TEM imaging.MBP-BFP-FUS-GFP-6xHis protein was expressed and purified as described previously2, 0.2 mM EDTA, 0.05% Triton X-100, and 10% glycerol). Cells were lysed by sonication on ice. The cell lysates were centrifuged at 110,000g for 40 min. The supernatants were purified on a Strep-Tactin Sepharose column . The column was washed with wash buffer (100 mM Tris–HCl (pH 8.0) 150 mM NaCl, and 1 mM EDTA), and protein was eluted with elution buffer (100 mM Tris–HCl (pH 8.0), 300 mM NaCl, 1 mM EDTA, and 2.5 mM desthiobiotin). The protein was concentrated with Amicon ultra-0.5 centrifugal filters to a final concentration of around 5 μM. For the aggregation assays, 100 nM sample was dissolved in 10 mM Tris–HCl (pH 7.5) and 50 mM NaCl. This fusion protein was used for fluorescence microscopy.Strep-GFP-FUS protein was expressed using BL21. The cells were collected and frozen in −80 °C overnight, and then resuspended in WCE buffer (25 mM HEPES (pH 7.9), 150 mM NaCl, 1.5 mM MgClA final concentration of 100 nM FUS in 10 mM Tris–HCl (pH 7.6), 0.2% CHAPS, 5 mM glucose, 50 mM NaCl, and 1 mM DTT was prepared in a total volume of 150 µL by diluting the FUS stock solution (50 mM Tris–HCl (pH 7.6), 1% CHAPS, 25 mM glucose, 250 mM NaCl, and 5 mM DTT). For the experiments in the presence of RNA, an equimolar amount of RNA was added to the FUS solution. Fluorescence spectra were collected with a steady-state photon counting spectrofluorometer  using a standard quartz cuvette with an optical path length of 1 cm. The excitation wavelength was 402 nm. The spectra slit width of 5 nm was used for excitation and emission with an integration time of 1 nm/s from 415 to 650 nm. All the measurements were carried out at 25 °C. A blank was measured and subtracted from all the spectra. Data were processed using a JASCO Spectra Manager of the FP-8000 series.Pipetting was carried out in a cuvette using a pipette tip whose point orifice and root diameters, and length are ca. 0.5 mm, 3.9 mm, and 36 mm, respectively. Sucking up was done in ca. 0.5 s, followed by extruding in ca. 0.5 s, one stroke of pipetting being accomplished every one second. The concentration of the sample after pipetting was measured as follows; after spinning the sample solution, the supernatant was collected and its concentration was measured on the basis of UV absorbance.2 to exclude background noise. To distinguish between LLPS particles and aggregates, 10% 1,6-hexanediol was added to each well, with which LLPS particles are dissolved, while aggregates are preserved. p values were calculated by two-tailed T test using T.TEST function of Microsoft Office Excel (2019).100 µL of 100 nM protein was placed in a 96-well plate and visualized under different pipetting conditions. GFP fluorescence was observed under a fluorescence microscope (Keyence BZ-X710). Images were converted to black and white. Fiji software (RRID: SCR_002285) was used to set particle size parameters to count particles > 0.002 mmA sample solution was diluted tenfold up to 10 nM and then spotted onto a collodion‐coated copper grid . After 1 min, the remaining solution was removed with filter paper and 5 μL of 1% (w/w) phosphotungstic acid (PTA) was spotted onto a collodion‐coated copper grid. The solution was removed immediately with filter paper. Then, the grid was washed with 5 μL pure water to remove excess PTA. After 1 min, the remaining solution was removed in the same manner. Images were obtained using a H‐7650 TEM  operating at 80 kV.Supplementary Information 1.