The performance of MAVRICS is evaluated using validated pathogen detection assays and real‐world and contrived samples. Unlike conventional methods, MAVRICS works directly in samples inactivated in phenol‐chloroform , thus allowing infectious samples to be handled safely without biocontainment facilities. MAVRICS allows wastewater biomass immobilized on membranes to be directly inactivated and lysed in TRIzol followed by RNA extraction by magnetic nanoparticles, thereby greatly reducing biohazard risk and simplifying processing procedures. Using 39 COVID‐19 patient samples and two wastewater samples, it is shown that MAVRICS rivals commercial kits in detection of SARS‐CoV‐2, influenza viruses, and respiratory syncytial virus. Therefore, MAVRICS is safe, fast, and scalable. It is field‐deployable with minimal equipment requirements and could become an enabling technology for widespread testing and wastewater monitoring of diverse pathogens.Molecular diagnosis and surveillance of pathogens such as SARS‐CoV‐2 depend on nucleic acid isolation. Pandemics at the scale of COVID‐19 can cause a global shortage of proprietary commercial reagents and BSL‐2 laboratories to safely perform testing. Therefore, alternative solutions are urgently needed to address these challenges. An open‐source method,  One important bottleneck in the diagnosis and surveillance of COVID‐19 is the shortage of kits for RNA extraction. Magnetic‐nanoparticle‐aided viral RNA isolation from contagious samples (MAVRICS) is an open‐source, safe, fast, and scalable method for RNA extraction. MAVRICS rivals commercial kits but requires minimal materials, and thus could become an enabling technology for widespread community testing of diverse pathogens. The emergence of new strains could have serious implications in the efficacy of diagnostic tests and success of vaccines. For example, 87 of 2816 genomes sampled between Jan and May 2020 have the T28688C SNV  that alters the sequence of the binding site of the forward primer of the CDC N3 rRT‐PCR assay, potentially compromising its effectiveness. Thus, continued surveillance of the evolution and geographic distribution of viral strains by high‐throughput sequencing is another pillar of public health measures to combat COVID‐19.Testing for COVID‐19 is vital for monitoring and mitigating the spread of SARS‐CoV‐2 and for safely restarting the normal economy. To date, molecular diagnosis of COVID‐19 predominantly relies on detection of SARS‐CoV‐2 RNA using real‐time reverse transcription polymerase chain reaction (rRT‐PCR) assays, such as those approved by the US Centers for Disease Control and Prevention (CDC).1 As S for RNA extraction. The US CDC recommends several commercially available RNA extraction kits. Fully automated diagnostic systems  that perform all steps from RNA extraction to rRT‐PCR without human intervention are also popular among diagnostic laboratories. Commercial kits and procedures typically yield consistent quality RNA and are easy to use, but come with a high price tag. Moreover, the availability of commercial proprietary reagents is seriously affected by the disruption of the global supply chain caused by the COVID‐19 pandemic. The high cost and low availability of proprietary reagents impose a bottleneck on testing capacities in rich and poor countries alike. Additionally, since the first reports of SARS‐CoV‐2 shedding in stool, the presence of the virus has been confirmed in municipal wastewater, sometimes even before the first confirmed cases in the community. This suggests that wastewater surveillance is an important public health measure, and it could be effective for monitoring the total COVID‐19 case load (including asymptomatic cases) in the population. Monitoring pathogens in wastewater requires methods that satisfy the biosafety requirements of handling unknown infectious agents and can overcome the low virus concentration and PCR inhibitors that are ubiquitous in wastewater. Therefore, there is great incentive to develop alternative methods that only require locally available and inexpensive chemicals, are simple to perform, and rival the performance of commercial kits. Besides alleviating supply shortage, the alternative methods should ideally eliminate the risk of handling live viruses, thus lowering the strict biosafety and biosecurity requirements on testing facilities. Any self‐build RNA extraction method that satisfies the above‐mentioned criteria can help increase testing capacity not only in clinical laboratories but also in rural healthcare facilities, university laboratories and field testing sites.Both rRT‐PCR testing and high‐throughput sequencing of SARS‐CoV‐2 require RNA extraction from nasopharyngeal swab samples. In the clinic, swabs are collected in viral transport media (VTM) and, if necessary, transported following specific cold‐chain biological substances transport guidelines1 for  (sold as TRIzol by Invitrogen or TRI Reagent by Sigma‐Aldrich) has been successfully used in life sciences laboratories around the world for nearly four decades. It requires widely available chemicals at a low cost. Previous studies indicate that TRIzol inactivates several infectious virus, including the Middle East Respiratory Syndrome Coronavirus (MERS‐CoV) and SARS‐CoV‐2. In addition, TRIzol reagent had the least effect on the RNA quality. The AGPC methods has been found to match the performance of commercial kits and automated systems in SARS‐CoV‐2 rRT‐PCR detection. In these studies, swabs were first collected in VTM or cell culture media, which were then used in AGPC RNA isolation. This workflow necessitates handling of live viruses and requires Biosafety Level 3 (BSL‐3) or BSL‐2 with enhance containment practices (BSL‐2+) facilities. We hypothesized that it should be possible to collect swabs directly in AGPC, which achieve two goals: 1) complete inactivation of any infectious agent by AGPC so that the downstream procedures  can be performed at relaxed biosafety levels, and 2) preservation of RNA integrity by denaturing nucleases.RNA isolation by acid guanidinium thiocyanate‐phenol‐chloroform extraction (AGPC)9 (sol Solid‐phase reversible immobilization (SPRI) of nucleic acid on MNPs offers a simple and elegant alternative to centrifuge‐ or column‐based methods. Under dehydrating conditions the MNPs are able to reversibly bind to nucleic acids  present in the sample. In the presence of a magnetic field nucleic acids are rapidly separated from most impurities, and the purified nucleic acids can be further released from the surface of MNPs by elution buffer with a different ionic strength. SPRI allows fast and thorough washes to eliminate inhibitors of downstream molecular biology reactions and yields high quality RNA for PCR and high‐throughput sequencing. Because it requires no centrifugation and only low‐cost materials, the MNP‐based RNA extraction is inherently scalable and amenable to automation.However, the AGPC method as is commonly practiced has several drawbacks that make it unsuitable for high‐volume testing. It requires extensive manual pipetting of hazardous chemicals and multiple centrifugation steps, which increase the risk of human errors and personnel injury especially. In the last decade, synthetic magnetic nanoparticles (MNPs) have been developed for various applications.26 Sol However, open‐source protocols based on home‐made MNPs are limited. Although some studies suggested that lab‐made MNPs could potentially work for COVID‐19 diagnosis, they suffer from either a lack of efficiency data on COVID‐19 samples or lower efficacy compared to commercial kits. Furthermore, the compatibility of MNPs and AGPC‐inactivated COVID‐19 samples was not tested. Although the combination of the AGPC and SPRI technologies would be obviously advantageous in consideration of reagent availability, cost, biosafety and ease‐of‐use, development of AGPC compatible MNP‐based RNA extraction protocols has been limited.In response to the COVID‐19 pandemic, commercial MNP‐based protocols for RNA extraction of COVID‐19 samples have been reported.34 Howmagnetic‐nanoparticle‐aided viral RNA isolation from contagious samples (MAVRICS) workflow  are available commercially  and widely used in molecular biology workflows such as PCR cleanup and sequencing library preparation. Unfortunately, cMNPs (in the form of RNAClean XP) failed to recover detectable RNA from AGPC solutions (in the form of TRIzol) spiked with high quality total RNA from human cells, while the conventional AGPC method based on organic phase separation and centrifugation recovered ≈45% of input RNA. On the other hand, cMNPs were capable of 96% recovery when the same RNA was spiked in water, suggesting that AGPC interferes with RNA binding onto cMNPs . SiMNPs coupled with the TNA protocol resulted an increase of 3.1 in Ct value compared to the official TRIzol Reagent protocol, which means a 11.1% yield of viral RNA relative to the AGPC method  inactivated in AGPC (in the form of TRIzol). As previously reported, SiMNPs were able to isolate RNA directly from TRIzol using the total nucleic acid extraction protocol (hereafter referred to as TNA protocol).30 We 2.23 protocols. We also noticed an improvement by washing the SiMNPs once with TRIzol and RNA binding buffer (1:1), presumably further removing RNases. Nonetheless, none of these protocols could improve upon the TRIzol Reagent protocol  to the RNA binding buffer and increasing its guanidinium chloride concentration to 3 m, the yield of RNA doubled . Using MAVRICS 12 samples can be extracted in parallel in ≈70 min (5.8 min per sample). Our preliminary results show that MAVRICS can be carried out by a Tecan FreedomEVO 200 liquid‐handling robot in a 96‐well format.We combined the modifications, i.e., the additional wash step and new binding buffers, that improved the recovery of viral RNA by SiMNPs and showed that they outperformed the TRIzol reagent protocol as judged by both the N1 and N3 rRT‐PCR assays  were extracted using the MAVRICS and TRIzol Reagent protocol respectively. The Ct values (N3 rRT‐PCR assay) obtained by both methods were highly concordant  spiked in wastewater concentrate, in which viral particles in 250 mL raw sewage were concentrated on electronegative membranes followed by ultrafiltration with Centripep YM‐50 to a final volume of 700 µL.40 TheA Figure .We further simplified the preparation of wastewater by using TRIzol to inactivate and lyse the sewage biomass  immobilized on the electronegative membranes, followed by RNA extraction by MAVRICS. Again, the spike‐in SARS‐CoV‐2 was efficiently recovered Figure , and the2.5Last, we validated the MAVRICS method for detection of other human pathogenic viruses than SARS‐CoV‐2. A commercial human respiratory pathogens control panel that contains influenza A and B viruses, and respiratory syncytial virus (RSV) was lysed in TRIzol and used for RNA extraction by MAVRICS. We then used a clinical diagnostic rRT‐PCR panel to quantitate the viruses. Interestingly, influenza A, influenza B and RSV were readily detectable in samples extracted using SiMNPs, but the Ct value of the same pathogens lagged by 4.08, 6.03, and 5.57, respectively, for samples extracted using the TRIzol Reagent protocol Figure . No viru3We described a SiMNP‐based RNA extraction workflow, MAVRICS, that is compatible with pathogen detection in clinical and environmental samples. All reagents used in MAVRICS are either readily available or can be synthesized in any biology laboratory with basic equipment. The longest preparation step is the synthesis and silica coating of MNPs, which can be done overnight with ≈3 h hands‐on time. The material cost for one synthesis is inconsequential yet can support thousands of RNA extractions. Because MAVRICS works for samples inactivated and preserved in AGPC , it allows potentially infectious samples to be handled safely without special biocontainment facilities. Importantly, MAVRICS matches, and often exceeds, the performance of commercial proprietary reagents using established molecular diagnostic tests of SARS‐CoV‐2, influenza viruses, and RSV Figures ,D,E. TheWe noticed that the correlation between SiMNP and DIRECT‐zol was lower than that between SiMNP and TRIzol . This protocol enables safe, economical, and effective extraction of RNA from clinical and environmental samples. Its performance rivals commercial RNA extraction kits in validated diagnostic tests of SARS‐CoV‐2, influenza, viruses, and respiratory syncytial virus. Because this protocol is centrifuge‐free, ongoing and future work will focus on automated high‐throughput of RNA extraction by liquid‐handling robots. In conclusion, MAVRICS has the potential to become an enabling technology for widespread community testing and wastewater monitoring in the current and future pandemics.58 copies per µL). Anonymized RNA samples were obtained from the Ministry of Health (MOH) hospitals in the western region in Saudi Arabia. The use of clinical samples in this study is approved by the institutional review board (IRB# H‐02‐K‐076‐0320‐279) of MOH and KAUST Institutional Biosafety and Bioethics Committee (IBEC). Oropharyngeal and nasopharyngeal swabs were carried out by physicians and samples were steeped in 1 mL of TRIzol (Invitrogen Cat. No 15596018) to inactivate the virus during transportation. The respiratory (21 targets) control panel (Microbiologics Cat. No 8217) was used as controls in rRT‐PCR assays.Contrived SARS‐CoV‐2 saliva samples were prepared by mixing 1000 µL of TRIzol, 100 µL of saliva from a health volunteer, and 5 µL of in vitro transcribed SARS‐CoV‐2 N gene RNA  attached to a glass filter holder . Magnesium ions were removed by passing 200 mL of 0.5 × 10‐3m H2SO4 (pH 3.0) through the filter, and the viruses were eluted with 10 mL of 1.0 × 10‐3m NaOH (pH 10.8). The eluate was recovered in a tube containing 50 µL of 100 × 10‐3m H2SO4 (pH 1.0) and 100 µL of 100 × tris–EDTA buffer (pH 8.0) for neutralization. The samples were further concentrated using a Centripep YM‐50 (Merck Millipore) to obtain a final volume of 600–700 µL.One liter of raw sewage was individually sampled at 9 AM and 4 PM on 7 June 2020 from the equalization tank of wastewater treatment plant operated within KAUST. The sewage from both time‐points was then mixed together to constitute a composite sample. Raw sewage (300–500 mL) was concentrated by using an electronegative membrane in the presence of cation which was described previously.40 Brihttps://doi.org/10.17504/protocols.io.bik4kcyw.Core magnetic nanoparticle synthesis and silica coating of MNPs were done following published protocols (Protocols 1.1 and 2.1 in reference 29). A detailed supplementary protocol 1 can be found in online Supporting Information. A step‐by‐step protocol is also available at url: 2O, and sonicated (Ultrasonic cleaner JSP US21) for 1 min.Size and zeta potential measurements, in SiMNPs and in commercial magnetic beads , were obtained using a Zetasizer nano Series . Prior to measurements the sample concentrations were adjusted to 0.1% w/v particles in ddHRNA extraction was performed using the Direct‐Zol RNA Miniprep kit (Zymo Research Cat. No R2070), TRIzol reagent (Invitrogen Cat. No 15596026), or RNAClean XP beads following the manufacturer instructions. Viral RNA was extracted from the concentrated raw sewage by using QIAamp viral RNA mini kit  following manufacture instruction. A 140 µL of concentrated raw sewage was used to obtain a final elution of 80 µL. The RNA was stored in ‐20 °C freezer until further use.Zap  and RNase AWAY  before and after use. The filtered pipette tips (Eppendorf epT.I.P.S. LoRetention series) and centrifuge tubes  used in this study were PCR‐clean grade.Reverse transcription of RNA samples was done using either NEB ProtoScript II reverse transcriptase (NEB Cat. No M0368) or Invitrogen SuperScript IV reverse transcriptase (Thermo Fisher Scientific Cat. No 18090010), following protocols provided by the manufacturers. After reverse transcription, 5 units of RNase H (New England Biolabs Cat. No M0523S) was added and incubated at 37 °C for 20 min to remove RNA. All of the web‐lab experiments in this study were conducted in a horizontal flow clean bench to prevent contaminations. The bench was decontaminated with 70% ethanol, DNA Please note that in the experience of ours and other (ref. ) the performance of the N1, N2, and N3 assay is similar, and the correlation of Ct value of the three assays in standard curves of SARS‐CoV‐2 samples is high. This indicates that reliable results can be obtained with any of them. When this study was conducted between March and June 2020, Saudi Arabia (where one are located) imposed a ban on international flights. One had limited supplies of real‐time PCR reagents, and it was not clear if one could obtain more in the near future. Because of the comparable performance of the three assays, one decided to use one assay (N3) only in the preliminary optimization phase and save N1 and N2 probes for clinical diagnostic purposes. Thus, the first 12 clinical samples were tested with the N3 assay, and it was done consistently in all figures. Two assays (N1 and N3) were used in the next standardization phase . Real‐time PCR analysis of SARS‐CoV‐2 sequences was analyzed on a CFX384 touch real‐time PCR detection system (Bio‐rad) using the following program: 50 °C for 2 min, 95 °C for 2 min followed by 45 cycles of 95 °C for 5 s and 59 °C for 30 s. Real‐time PCR assays for influenza A, B/RSV were purchase from IDT (Cat. No 1079729) and used per manufacturer recommendation. For influenza and RSV assays, the following program was used: 50 °C for 2 min, 55 °C for 120 s, 60 °C for 360 s, 65 °C for 240 s, followed by five cycles 95 °C for 5 s and 55 °C for 30 s, and then 45 cycles of 91 °C for 5 s and 58 °C for 25 s. MNV and PMMoV real‐time PCR assay was conducted using the primer and probes, which described previously.42 PleThe authors declare no conflict of interest.M.L. and G.R.M. performed majority of the molecular biology experiments. M.L. and G.R.M. analyzed the data and wrote the manuscript. R.S., S.M., and J.X. performed experiments. A.R. and P.H. performed experiments on wastewater. DBS performed the evaluations of size and zeta potential. FSA, AK, AMH, NAMA and AA collected clinical samples. SH and AP coordinated the clinical samples and molecular testing. ML conceived and supervised the study.Supporting InformationClick here for additional data file.


Importantly, the direct method had sufficient sensitivity to reliably detect those patients with viral loads that correlate with the presence of infectious virus. Thus, this strategy has the potential to ease supply choke points to substantially expand COVID-19 testing and screening capacity and should be applicable throughout the world.The ongoing COVID-19 pandemic has created an unprecedented need for rapid diagnostic testing. The World Health Organization (WHO) recommends a standard assay that includes an RNA extraction step from a nasopharyngeal (NP) swab followed by reverse transcription–quantitative polymerase chain reaction (RT-qPCR) to detect the purified SARS-CoV-2 RNA. The current global shortage of RNA extraction kits has caused a severe bottleneck to COVID-19 testing. The goal of this study was to determine whether SARS-CoV-2 RNA could be detected from NP samples via a direct RT-qPCR assay that omits the RNA extraction step altogether. The direct RT-qPCR approach correctly identified 92% of a reference set of blinded NP samples ( A major bottleneck to RT-PCR-based COVID-19 testing is the RNA extraction step. This study shows that a “direct RT-PCR” approach that omits the RNA extraction step can reliably detect SARS-CoV-2 RNA in nasopharyngeal swabs from individuals most likely to be infectious. This approach has a sensitivity of 95% on samples with a clinical cycle threshold (CT) at or below 32, which corresponds to a viral load of 1.7 × 104 copies/ml. Notably, this is considerably below the threshold at which samples have been shown to contain live virus and are thought to be infectious (106–107 copies/ml) ) . The inc4 copies/ml of patient sample as measured by the UW clinical LDT  for the direct approach to be a clinical CT of 32, which corresponds to approximately 50 RNA copies/reaction, or 1.7 × 10ical LDT . Recent l RNA/ml . To direTo determine the specificity of the direct approach we also tested 30 samples known to be SARS-CoV-2 negative by the UW LDT. All 30 samples were negative for SARS-CoV-2 RNA by the direct approach, and 29/30 successfully amplified the EXO spike-in control . From thCOVID-19 testing demands are currently overwhelming the world’s clinical laboratories. A major choke point is the RNA extraction step, due to both the time and labor for this step and the critical shortage of extraction kits and required reagents. As a means to circumvent these limitations on clinical testing availability, we show here that a direct RT-qPCR approach that omits an RNA extraction step can effectively identify SARS-CoV-2 RNA from NP swabs. When applied to a large collection of clinical NP specimens representative of the range of COVID-19 patients in the state of Washington, the direct RT-qPCR assay correctly identified 92% of the donors screened, with 100% specificity. The only samples missed were those with very low levels of viral RNA, near the limit of detection even when RNA extraction was used. It is likely that the direct assay would detect the most infectious patients, as the ability to isolate live virus from NP swabs correlates with viral loads that are robustly detected here ,8,10. InWe propose that the direct RT-qPCR approach described here could be useful in at least 2 settings. First, in regions of the world that have some degree of access to RNA extraction kits to perform the recommended CDC or WHO clinical RT-qPCR test, we envision that this approach could be used as a screening strategy to expand testing capacity to those  who are not currently receiving tests. As this approach would pick up the majority of cases, including those most infectious as well as presymptomatic or asymptomatic individuals ,10, we sThe testing approach described here could also easily be adopted in more resource limited settings, including large portions of the developing world that at present completely lack access to RNA extraction. A testing approach that uses patient samples directly without RNA extraction would open up perhaps the only viable avenue for widespread testing in these regions. In recent months the scientific community has made enormous strides towards addressing the formidable challenge of providing ample and accessible COVID-19 testing across the globe, and yet the problem is assuredly not solved. An “all-in” approach to testing (which we describe further here ) in whicRT-qPCR analysis of clinical samples for this study was approved by the University of Vermont and the University of Washington institutional review boards with a consent waiver. The de-identified samples were determined to be exempt because they were not considered human subjects research due to the quality improvement and public health intent of the work.Clinical NP swabs were collected in 3 ml of M6 transport medium. Patients were confirmed to be negative (3) or positive (6) for SARS-CoV-2 by the Vermont Department of Health using the CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel [Clinical NP swabs were collected in 3 ml of universal transport medium (UTM). Thirty samples from patients confirmed to be SARS-CoV-2 negative and 210 samples from patients confirmed to be SARS-CoV-2 positive by the University of Washington Medical Laboratory with a range of viral loads  and sufficient volume were selected for this study Figs  and S2.All patient samples at each testing site were stored at 4°C in between sample collection and transport to the laboratory, and again until clinical testing was carried out, maintaining a standardized sample acquisition and processing protocol.To compare the effect of nucleic acid extraction with direct RT-PCR, RNA from a pooled patient sample was extracted using the QIAamp Viral RNA Mini Kit  according to the manufacturer’s instructions. A total of 140 μl of pooled NP swab diluent was extracted and eluted in 60 μl; 5 μl  was used for real-time RT-PCR .To compare the effect of nucleic acid extraction with direct RT-PCR, RNA from 30 μl or 200 μl of patient sample was extracted using the Roche MagNA Pure 96 platform (Roche Lifesciences) and eluted into 50 μl of buffer; 5 μl of RNA  was used for real-time RT-PCR. To monitor RNA recovery and RT-PCR efficiency, 40,000 copies of EXO internal control RNA were added into the lysis buffer and went through the extraction process with each sample Figs  and S2.In For Figs For both the University of Vermont and UW, sample selection  and RNA extraction/RT-PCR of samples were performed by separate individuals; the person running the assays was blinded to the original clinical CT value of the samples.S1 TableA) CT values from COVID-19 patient NP swabs following direct RT-qPCR versus standard RT-qPCR for SARS-CoV-2 RNA detection that included RNA extraction. A total of 150 NP swab samples representing high , intermediate , or low  SARS-CoV-2 RNA loads as determined by clinical RT-qPCR at UW in Seattle  were analyzed by the indicated methods. Direct RT-qPCR was performed on 3 µl of NP swab diluent after heating for 10 minutes at 95°C or not. In parallel, RNA was extracted from 30 µl of NP swab diluent that had been previously heated at 95°C for 10 minutes or not, and RNA representing 3 µl of the original diluent was used in RT-qPCR to allow a head-to-head comparison with direct RT-qPCR on the same quantity of NP swab diluent. For selected samples (n = 100), RNA was also extracted from 200 µl of NP swab diluent  that had been previously heated at 95°C for 10 minutes or not, and RNA representing 20 µl of the original diluent was used in RT-qPCR. Samples below the limit of detection (CT of 40 or more) are designated “NEG.” Three separate experiments  were performed and are indicated. A subset of this data is linked to B) CT values from COVID-19 patient NP swabs following direct RT-qPCR versus standard RT-qPCR for EXO RNA that was spiked into the swab diluent. A total of 150 NP swab samples representing high , intermediate , or low  SARS-CoV-2 RNA loads as determined by clinical RT-qPCR at UW in Seattle  were analyzed by the indicated methods. For the donors indicated, an aliquot of swab diluent was spiked with 4 × 104 copies of EXO control RNA prior to RNA extraction or direct addition of sample to the RT-qPCR reaction for subsequent detection with an EXO primer/probe set. Direct RT-qPCR was performed on 3 µl of NP swab diluent after heating for 10 minutes at 95°C or not. In parallel, RNA was extracted from 30 µl of NP swab diluent that had been previously heated at 95°C for 10 minutes or not, and RNA representing 3 µl of the original diluent was used in RT-qPCR to allow a head-to-head comparison with direct RT-qPCR on the same quantity of NP swab diluent. For selected samples (n = 100), RNA was also extracted from 200 µl of NP swab diluent  that had been previously heated at 95°C for 10 minutes or not, and RNA representing 20 µl of the original diluent was used in RT-qPCR. Samples below the limit of detection (CT of 40 or more) are designated “NEG.” Three separate experiments  were performed and are indicated. EXO, EXO primer/probe set; N1, 2019-nCoV_N1 primer/probe set; N2, 2019-nCoV_N2 primer/probe set; nd, not done.(XLSX)Click here for additional data file.S2 TableA) CT values from COVID-19 patient NP swabs or non-COVID-19 patient NP swabs following direct RT-qPCR versus standard RT-qPCR for SARS-CoV-2 RNA detection that included RNA extraction. A total of 90 NP swab samples representing low SARS-CoV-2 RNA loads  or non-detected  SARS-COV-2 RNA as determined by clinical RT-qPCR at UW in Seattle  were analyzed by the indicated methods to establish the limit of detection and specificity of the direct RT-qPCR method. Direct RT-qPCR was performed on 3 µl of NP swab diluent after heating for 10 minutes at 95°C. In parallel, RNA was extracted from 200 µl of NP swab diluent  that had been previously heated at 95°C, and RNA representing 20 µl of the original diluent was used in RT-qPCR. Samples below the limit of detection (CT of 40 or more) are designated “NEG.” These data are linked to B) CT values from COVID-19 patient NP swabs or non-COVID-19 patient NP swabs following direct RT-qPCR versus standard RT-qPCR for EXO RNA that was spiked into the swab diluent. A total of 90 NP swab samples representing low SARS-CoV-2 RNA loads  or non-detected  SARS-COV-2 RNA as determined by clinical RT-qPCR at UW in Seattle were analyzed by the indicated methods. For the donors indicated, an aliquot of swab diluent was spiked with 4 × 104 copies of EXO control RNA prior to RNA extraction or direct addition of sample to the RT-qPCR reaction for subsequent detection with an EXO primer/probe set. Direct RT-qPCR was performed on 3 µl of NP swab diluent after heating for 10 minutes at 95°C. In parallel, RNA was also extracted from 200 µl of NP swab diluent  that had been previously heated at 95°C for 10 minutes, and RNA representing 20 µl of the original diluent was used in RT-qPCR. Samples below the limit of detection (CT of 40 or more) are designated “NEG.” EXO, EXO primer/probe set; N2, 2019-nCoV_N2 primer/probe set.(XLSX)Click here for additional data file.


Arabidopsis thaliana. Then using the optimized strategy, we determined the accumulation of circular and corresponding linear transcripts in plant seedlings and organs. We observed that only a small fraction of circRNAs was reproducibly generated. Among them, two groups of circRNAs were discovered: ubiquitous and organ-specific. The highest number of circRNAs with significantly increased accumulation in comparison to other organs/seedlings was found in roots. The circRNAs in seedlings, leaves and flowers originated mainly from genes involved in photosynthesis and the response to stimulus. The levels of circular and linear transcripts were not correlated. Although RNase R treatment enriches the analyzed RNA samples in circular transcripts, it may also have a negative impact on the stability of some of the circRNAs. We also showed that the normalization of NGS data by the library size is not proper for circRNAs quantification. Alternatively, we proposed four other normalization types whose accuracy was confirmed by ddPCR. Moreover, we provided a comprehensive characterization of circRNAs in A. thaliana organs and in seedlings. Our analyses revealed that plant circRNAs are formed in both stochastic and controlled processes. The latter are less frequent and likely engage circRNA-specific mechanisms. Only a few circRNAs were organ-specific. The lack of correlation between the accumulation of linear and circular transcripts indicated that their biogenesis depends on different mechanisms.RNA-seq is currently the only method that can provide a comprehensive landscape of circular RNA (circRNAs) in the whole organism and its particular organs. Recent years have brought an increasing number of RNA-seq-based reports on plant circRNAs. Notably, the picture they revealed is questionable and depends on the applied circRNA identification and quantification techniques. In consequence, little is known about the biogenesis and functions of circRNAs in plants. In this work, we tested two experimental and six bioinformatics procedures of circRNA analysis to determine the optimal approach for studying the profiles of circRNAs in  Oryza sativa , the total number of circRNAs in A. thaliana identified in different studies reached 38,938.Circular RNAs (circRNAs) have recently emerged as a new, large class of noncoding RNAs with functions that, in most cases, remain unknown. To date, the abundance and evolutionary conservation of circRNAs have been shown across different species within the animal and plant kingdoms . Howevera sativa , Arabidothaliana , Zea mayZea mays , Solanumpersicum , Glycinehirsutum , Triticuaestivum , Hordeum vulgare , etc. A  vulgare . Unfortu vulgare  to appropersicum . The sametween 6  and 6,01etween 6 , dependiA. thaliana is currently the best-characterized plant in terms of circRNAs. A large fraction of these molecules was identified based on RNA-seq data generated earlier to study gene expression levels. Thus, RNA isolation and sequencing protocols were rarely optimized for circRNA research. During bioinformatics analyses, it was routinely assumed that a circRNA is valid if its presence is supported by at least two so-called back-spliced reads (reads overlapping a circRNA splicing site). The depth of the library was normally not taken into consideration, and thus, the numbers of circRNA candidates varied markedly between studies. Accordingly, questions about the levels of circRNA accumulation in plants and, consequently, their functional relevance have not been satisfactorily answered to date. Some reports have suggested that circRNAs in A. thaliana are expressed in tissue and developmental stage-specific manners  and several approaches of RNA-seq data normalization that are routinely used to quantify other transcripts. We showed that the treatment of RNA samples with RNase R significantly increased the number of identified circRNAs. However, the spectrum of highly abundant circRNAs was reduced. Moreover, to compare the levels of circRNA accumulation in various plant organs, it is necessary to apply a circRNA-dedicated method of RNA-seq library normalization. After testing six normalization methods, we identified those that provided data that were most coherent with droplet digital PCR (ddPCR) results. We also noticed that the best correlation was observed when comparing samples collected from the same organs.A. thaliana seedlings and organs, which led to the identification of ubiquitous and organ-specific circRNAs. Our results revealed that, in many cases, the abundance of circRNAs was not directly linked to the level of parent gene expression, which suggested the existence of circRNA-dedicated regulatory mechanisms.Next, using the optimized strategy, we investigated the accumulation of circular and corresponding linear transcripts in A. thaliana plants (deposition number: CS70000) were obtained from Arabidopsis Biological Resource Center (ABRC). The formal identification of the plant material used in the study was performed by J. Ecker laboratory  using Illumina sequencing by synthesis technology. Seeds were sterilized by placing them in filter tubes and washing them with 70% ethanol, distilled water, 0.01% Amistar 250 SC (Syngenta) and distilled water, using a vacuum pump. Next, the seeds were exposed to stratification for 4 days at 4°C in 0.1% agarose solution. Plants were grown using Arasystem (Betatech) and Jiffy-7 peat pellets in a growth chamber with 16 h of light at 23°C and 8 h of dark at 18°C. Whole seedlings at stage 1.0 (cotyledons fully open), whole roots and leaves at stage 3.90 (rosette growth complete) and whole flowers at stage 6.90  (Seeds of wild-type (Col-0) roduced)  were colTotal RNA samples (isolated as described above) were divided into two portions: one portion was used to prepare an RNA-seq library without prior RNase R treatment (R−), and the other portion was used to prepare an RNA-seq library from RNase R-treated RNA (R+). For library preparation, we used 2.5 μg of total RNA. According to the first protocol (R−), 2.5 μg of total RNA was treated with Ribo-Zero (Illumina) following the manufacturer’s recommendation. The Ribo-Zero rRNA Removal Kit (Plant Leaf) was used for seedlings, leaves and flowers, and the Ribo-Zero rRNA Removal Kit (Plant Seed/Root) was used for roots. The level of rRNA depletion was determined by capillary electrophoresis  with the Plant RNA Pico Assay.The second protocol (R+) also included treatment of 2.5 μg of total RNA with Ribo-Zero. Then, 500 ng of the Ribo-Zero-treated RNA was denatured at 70°C for 3 min, treated with 10 U of RNase R (Epicentre) at 37°C for 1 h and subsequently purified with the QIAquick Nucleotide Removal Kit (Qiagen). The quality and integrity of the resultant RNA was tested using capillary electrophoresis  with the Plant RNA Pico Assay.One hundred nanogram aliquots of R− and R+ RNA samples from seedlings, roots, leaves, and flowers were prepared in four biological replicates. Next, 8 indexed libraries per biological replicate  were prepared separately using the TruSeq RNA Sample Preparation Kit (Illumina) in accordance with the manufacturer’s instructions with minor changes. The protocol was modified by omitting the mRNA purification step and reducing reaction volumes by one-third at subsequent steps. The libraries were submitted to qualitative analysis using capillary electrophoresis  with the High Sensitivity DNA Assay and quantitative analysis with a Qubit fluorometer (Invitrogen) prior to sequencing. The samples were sequenced with the Genome Analyzer IIx (Illumina) and 108-bp, paired-end protocol.Raw reads were trimmed and quality-filtered with AdapterRemoval . As a rCircRNAs were identified using the protocol recommended by . Briefly2, 0.2 mM dNTPs, 1× Taq Buffer with (NH4)2SO4 (Thermo Fisher Scientific), and 0.3 µM of each primer (Genomed). PCR was performed in a T-100 thermal cycler (Bio-Rad) using the following program: preheating at 95°C for 3 min, followed by 40 cycles (with divergent primers) or 35 cycles (with convergent primers) at 95°C for 30 s, 59°C to 62°C (dependent on the melting temperature (Tm) of the primers used – listed in For the selected circRNAs, their formation was confirmed by PCR. For each individual circRNA, two PCRs were performed: the first reaction involved divergent primers (circular transcript specific), and the second reaction involved convergent primers (linear transcript specific). As a control, analogous PCRs with gDNA as a template were performed. All primers are listed in ACT2. To determine the raw read numbers mapping to the selected gene, we applied the protocol proposed by . Gene quantification analyses were performed with StringTie [version 1.3.3b; . CircRNAs were grouped by hierarchical agglomerative clustering and divided between classes as follows: high for 5% of circRNAs with the highest accumulation in organs/seedlings; medium - circRNAs with higher accumulation than 80% of circRNAs and lower than 5% of circRNAs with the highest accumulation; low – remaining circRNAs; not detected - circRNAs not detected in particular organ/seedlings. Linear counterparts were ordered corresponding to circRNAs. To evaluate associations between two variables  we calculated Pearson correlation using R package. GO enrichment analyses were conducted with agriGO .m of the primers used – listed in ACT2 expression level was determined in parallel in four technical repeats as a reference for normalization.ddPCR reactions were performed with the QX200 ddPCR System (Bio-Rad) in accordance with the manufacturer’s protocol. ddPCR reactions were performed with two sets of primers: a pair of divergent primers or a pair of convergent primers. All primers used are listed in A. thaliana  and prepared RNA-seq libraries using two protocols that are widely applied in circRNA studies. In line with the first approach, we used total RNA depleted of rRNA . For the R+ libraries, 25,932,926 paired-end reads, on average, were obtained; 99.00% of the reads passed trimming and quality filtration, and 91.87% of them mapped to the A. thaliana reference genome (TAIR10).On average 60,292,166 paired-end reads were obtained for R− libraries; 99.54% of the reads passed trimming and quality filtration, and 95.30% of them mapped to the For the R− libraries, from 0.6% to 7.57% of the reads mapped to the rRNA sequences . For the R+ libraries, the percentage of reads that mapped to the rRNA sequences varied from 0.27% in roots to 3.18% in flowers. This observation was consistent with the capillary electrophoresis results . In the positive control (lane 11), leaves cDNA were used as a template, and in the negative (lane 12), no template was added. The obtained results were fully consistent with the RNA-seq data obtained for both the R− and R+ libraries.In the next step, the RNA-seq results were validated by reverse transcription PCR (RT-PCR). We selected 10 circRNA candidates that were identified in both the R− and R+ libraries. Nine of the candidates were found in leaves, and 1 was absent in leaves but present in 2 other organs and in seedlings  to 2.7% (R+) for the leaf libraries and from 4.4% (R−) to 5.0% (R+) for the root samples Figure 2The above results showed that a large fraction of circRNAs did not form reproducibly in plants. Moreover, some circRNAs with considerable functional potential, i.e., accumulating in plants to high levels, were not identified in R+ libraries. Consequently, in further analyses, we used RNA-seq data obtained with R− libraries, as we intended to study highly abundant, reproducible circRNAs with functional potential.In former reports on circRNAs, their accumulations in whole plants and in different organs were usually determined based on RNA-seq data (read counts) without further validation by other experimental methods. To obtain detailed insight into this issue, we compared the results of RNA-seq-based quantitative analysis of circRNAs with corresponding data obtained using ddPCR. To achieve this goal, we selected 8 circRNAs and determined their levels in seedlings, roots, leaves, and flowers by ddPCR. The summarized ddPCR results based on 3 biological replicates are shown in The difficulties with proper RNA-seq data normalization motivated us to compare the content of the RNA-seq libraries. We found significant differences in the composition of organ/seedling transcriptomes. In particular, the numbers of reads mapping to rRNA genes and the chloroplast genome were markedly distinct  the number of back-spliced reads, (ii) the DESeq2 size factor (iii) the library size without rRNA and chloroplast RNA reads, (iii) the number of back-spliced reads without rRNA and chloroplast RNA reads and (iv) housekeeping gene Moreover, analysis of the ddPCR results showed that 50 copies of circRNA per microgram of total RNA (cp/µg) represented the minimal value for quantification of circRNA using this method. Below this threshold, the standard deviation and average values were comparable, which made the results unreliable , which corresponded to the threshold of 50 cp/µg established by the ddPCR and were additionally identified by find_circ program (Gene ontology (GO) analysis of chloroplast genes giving rise to circRNAs did not reveal any significant enrichment. Consecutive GO analysis revealed that the circRNAs in seedlings, leaves and flowers predominantly came from genes involved in photosynthesis and the response to stimulus (seedling and flower) , A. thaliana chromosomes were a preferable source of circRNAs. However, this analysis did not reveal any statistically significant differences.The analysis of back-spliced reads revealed the predominance of reads corresponding to chloroplast circRNAs in seedlings  displayed a common accumulation profile, characterized by a continual increase in their amounts from seedlings through roots, leaves to flowers Figure 7A. thaliana in different studies . The plausible reason for this result is the natural variation of the transcriptome composition of different organs. Consequently, the applied experimental procedures have different efficiencies, depending on the type of plant material. This phenomenon was evidenced by the varying effectiveness of rRNA depletion from particular organs. Moreover, the organ-specific differences may influence the RNA-seq ability to identify and quantify transcripts, in particular, the less abundant ones, such as circRNAs. To optimize the comparative analyses of circRNAs, we tested five other normalization methods. Four of these methods, namely, normalization by the (i) number of back-spliced reads, (ii) DESeq2 size factor (iii) library size without rRNA and chloroplast RNA reads and (iv) housekeeping gene  by qPCR . MoreoveA. thaliana seedlings and organs was based on 127 circRNAs identified by CIRI2 and find_circ programs and supported by at least 10 normalized RNA-seq reads, which corresponded to 50 copies per microgram of total RNA. Based on the provided data, we believe that this set well represents reproducibly generated circRNAs that are most likely to be physiologically relevant. In general, circRNAs were accumulated in an organ-specific manner; however, approximately 41% were ubiquitous. GO analysis revealed that genes giving rise to circRNAs were significantly enriched in those involved in photosynthesis in seedlings, leaves and flowers. However, roots had the highest number of unique circRNAs and most circRNAs of significantly increased accumulation  in comparison to other organs/seedlings. The smallest number of circRNAs with increased accumulation was found for the seedlings. Moreover, our results clearly demonstrated that there was no direct link between the accumulation of circRNAs and their linear counterparts. While the levels of some circRNAs increased with the increase in their linear counterpart transcripts (circ_AT4G07390 and lin_AT4G07390), there was an overall lack of correlation between the accumulation of these two transcriptome fractions (Pearson correlation coefficient: 0.14). This finding indicated that there have to exist specific mechanisms regulating the formation of reproducibly generated circRNAs. What is more, some circRNAs  were selectively increased in particular organs, while the levels of their linear counterparts remained relatively stable throughout the plant. It is tempting to speculate that their biogenesis involves an organ-specific molecular switch that changes the regular splicing pattern. These circRNAs also emerge as attractive candidates for functional studies.Our analysis of circRNAs across Recently, chloroplasts were described as circRNA production hotspots, and circRNAs were proposed to be involved in photosynthesis . Our datA. thaliana circRNAs. By using ddPCR results as feedback to improve RNA-seq normalization, we developed a reliable strategy of circRNA comparative analyses. This strategy allowed us to comprehensively characterize circRNAs across plant organs and in seedlings. Our results stimulate further research of organ-specific circRNAs and of the mechanisms that guide a switch between the formation of circular and their linear counterpart transcripts.Here, we integrated RNA-seq and ddPCR to study https://www.ncbi.nlm.nih.gov/bioproject/PRJNA525820.The original contributions presented in the study are publicly available. This data can be found here: MF conceived the overall idea of the study. AP, PJ, and MF conceived and designed the experiments. KN performed all bioinformatics analyses. AP, PJ and MF analyzed and discussed the results, MS cultivated plants, isolated RNA and performed PCR/ddPCR. MS and PJ cloned and sequenced PCR products. MS and JP prepared RNA samples for sequencing. JP and LH generated the RNA-seq libraries. AP, KN, MS, and PJ drafted the manuscript. MF was responsible for the final version of the manuscript. All authors contributed to the article and approved the submitted version.This work was financed by the National Science Centre grant number UMO-2014/15/D/NZ2/02305 to AP. Partial financial support was also provided by the Polish Ministry of Science and Higher Education under the KNOW program. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.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.


A-to-I RNA editing diversifies the transcriptome and has multiple downstream functional effects. Genetic variation contributes to RNA editing variability between individuals and has the potential to impact phenotypic variability.We analyze matched genetic and transcriptomic data in 49 tissues across 437 individuals to identify RNA editing events that are associated with genetic variation. Using an RNA editing quantitative trait loci (edQTL) mapping approach, we identify 3117 unique RNA editing events associated with a cis genetic polymorphism. Fourteen percent of these edQTL events are also associated with genetic variation in their gene expression. A subset of these events are associated with genome-wide association study signals of complex traits or diseases. We determine that tissue-specific levels of ADAR and ADARB1 are able to explain a subset of tissue-specific edQTL events. We find that certain microRNAs are able to differentiate between the edited and unedited isoforms of their targets. Furthermore, microRNAs can generate an expression quantitative trait loci (eQTL) signal from an edQTL locus by microRNA-mediated transcript degradation in an editing-specific manner. By integrative analyses of edQTL, eQTL, and microRNA expression profiles, we computationally discover and experimentally validate edQTL-microRNA pairs for which the microRNA may generate an eQTL signal from an edQTL locus in a tissue-specific manner.Our work suggests a mechanism in which RNA editing variability can influence the phenotypes of complex traits and diseases by altering the stability and steady-state level of critical RNA molecules.The online version contains supplementary material available at 10.1186/s13059-021-02287-1. RNA editing is a cellular process in which the sequence in mature RNA molecules is enzymatically altered from the genomic sequence . The mosMicroRNAs (miRNAs) are a class of small noncoding RNAs that regulate gene expression by transcript degradation or by translational repression . Since mQuantitative trait loci (QTL) mapping of molecular traits is a widely used approach to find genetic effects on gene regulation . QTL stuGenome-wide association studies (GWAS) have been successful in identifying genetic associations with phenotypic traits . HoweverHere, we analyzed cis-regulated RNA editing events using an edQTL and allele-specific RNA editing (ASED) approach across 49 tissues and 437 individuals. We find evidence to suggest that tissue-specific ADAR and ADARB1 levels are responsible for many tissue-specific edQTL signals. Many of these edQTL signals are associated with GWAS traits. Surprisingly, we find that many edQTLs also colocalize with their corresponding genes’ steady-state transcript levels. Furthermore, we find evidence to suggest that miRNAs may play a role in linking RNA editing with steady-state transcript levels by targeting the edited or unedited version of the transcripts. We propose a mechanism in which an edQTL can generate an eQTL signal and consequently affect phenotypes by modulating transcript stability in an editing-specific manner.In order to study the factors that influence RNA editing variability across human tissues and individuals, we used genetic and transcriptomic data from the GTEx Project . We analWe used an edQTL approach as the primary means to identify cis-regulated RNA editing events and found 3117 unique RNA editing sites that are associated with at least one edQTL SNP across 49 tissues  gene has a large effect size of 0.36 in the nucleus accumbens but a small effect size of 0.056 in skeletal muscle  is relatively consistent across all tissues but much smaller in skeletal muscle. Coincidentally, skeletal muscle has the lowest expression level of ADAR  with ADARB1 levels . However, for a small fraction of edQTL sites, some additional tissues (other than muscle) also have varying effect sizes. After inspecting RNA editing sites with a high variance of effect sizes (|coefficient of variation| ≥ 1) across tissues Fig. d, we ideNext, we aimed to identify edQTL sites that are known to be associated with human disease. We intersected our sites with the Editome Disease Knowledgebase  and founIn our edQTL analysis, the RNA editing site at chr5:79923430 is significantly associated with rs1650720 in three tissues: lymphoblastoid cell lines (LCL), fibroblasts, and spinal cord . Four hundred forty-three RNA editing sites  experiments across 29 cell lines and 27 miRNAs .A-to-I RNA editing is widespread in human transcriptomes and influences multiple layers of gene regulation , 46. Recp values for all SNPs in a large genomic window. Intuitively, a high posterior probability of colocalization is reached if the two sets of p value distributions track each other. We highlighted FADS1 as an example of an edQTL signal that colocalizes with its eQTL signal as well as multiple GWAS traits  identify tissue-specific edQTL:eQTL colocalization events, (2) attribute some of these tissue-specific colocalization events to tissue-specific miRNA levels, and (3) experimentally confirm editing-specific miRNA-mRNA regulation using 3′-UTR luciferase reporter assays. These results demonstrate that the DHFR example generalizes to other genes and RNA editing sites.We should note that the list of edQTL events that may generate eQTL events is expected to be substantially larger than the candidate events identified in Fig. Our study focused on miRNAs as trans-acting regulators that generate eQTLs from edQTLs; however, we expect that a similar scenario could occur to RNA binding proteins that regulate RNA stability via sequence-specific protein-RNA interactions. In fact, 14% of edQTL sites (443 out of 3117) have at least one tissue in which the edQTL signal colocalizes with the eQTL signal, suggesting that a trans-acting regulator (miRNA or RNA binding protein) may alter RNA stability in an editing-specific manner. In theory, editing-specific transcript stability control by RNA binding proteins could also generate an eQTL from an existing edQTL. It has been demonstrated that ELAV1/HuR stabilizes the edited version of CTSS transcripts . If ELAVThis work expands prior knowledge on genetically regulated RNA editing events in several major ways. Previous studies have surveyed genetically regulated RNA editing events across a limited number of cell types and tissues. In our earlier work , we usedMillions of A-to-I RNA editing sites have been identified across the human transcriptome, but the functions of most RNA editing events are unknown . The majRNAeditinglevel=G/(A+G)).For GTEx samples, RNA-seq alignments hg19) and genotype information  were obtained from dbGAP (Accession phs000424.v7.p2). Alignments were downloaded using the sam-dump command from SRA-Tools . Through9 and genAnatograms were obtained from the GTEx Portal and originated from the Expression Atlas , under tFor any given tissue, we required the RNA editing sites to meet the following criteria: a minimum average coverage of at least two reads supporting the edited version, a minimum average total coverage of at least ten reads, and a minimum of 10% difference between the editing levels of the 90% quantile and the 10% quantile across all individuals. To remove potential artifacts, we also limited our analysis to annotated ATLAS RNA editing sites that did not overlap with annotated SNPs from the GTEx project , 1000 Gep value for each SNP. To ensure accurate RNA-seq estimation of RNA editing levels, we required each sample to have a minimum coverage of 20 reads. For each SNP, we required a minor allele frequency of at least 5%. For each RNA editing site, the edQTL SNP was defined as the closest SNP with the most significant association. The number of tested sites and the number of tested site-SNP pairs per tissue are available  threshold with a permutation procedure [p value cutoffs to 1e−5  and the x values are the genotypes .For each RNA editing site, we applied a linear model to SNPs within a 400-kb window centered at the editing site. We used the lm function within R to regress the editing level (Φ) against the genotype across individuals of a given tissue in order to obtain a rocedure , 59 yielΦij is the RNA editing level of site i of sample j; μi is the baseline RNA editing level of site i; Genotypej and Tissuej are the genotype and tissue type of sample j; and α, β, and γ are the regression coefficients that represent the effects of genotype, tissue type, and their interaction term on RNA editing levels. Tissuej is a binary categorical variable that represents muscle  and non-muscle tissues. To assess if the genotype effect on a given RNA editing site is tissue-dependent, we performed a likelihood ratio test by comparing the fit for the model with versus without the Genotypej ∗ Tissuej interaction term.To further investigate tissue-dependent edQTL signals in muscle vs non-muscle tissues, we fitted the data to the following multivariate model:Allele-specific alignments were obtained by aligning RNA-seq reads using STAR   were obtained from the GTEx Portal . We usedp values were obtained using a likelihood ratio test to compare the quadratic model (whole data) with the linear model (whole data).The full edQTL data were fit to a quadratic model and a linear model. The homozygous samples (Ref:Ref and Alt:Alt) were fit to a linear model. Non-linearity shifts were determined by measuring the difference between the quadratic fit (whole data) at the heterozygous genotype with the linear fit (homozygous data) at the heterozygous genotype. 2 > 0.8) with GWAS SNPs. Genotypes from the GTEx project were used in the LD calculation. LD plots were generated with Haploview [We obtained GWAS signals from the NHGRI-EBI GWAS Catalog  . These values were chosen to demonstrate the effect of miRNA-mediated transcript degradation on edQTL and eQTL signals across a range of degradation rates. Based on the degradation rate, either the edited transcripts or unedited transcripts were proportionally degraded. Then, the editing levels and steady-state transcript levels were computed for each genotype.p values were obtained using a generalized linear mixed model [RNA-seq reads  have at least one tissue with colocalizing edQTL and eQTL signals (PP4 > 0.75), (2) have at least one tissue with non-colocalizing edQTL and eQTL signals (PP1 > 0.75), (3) be in the 3′-UTR, and (4) have an editing-specific miRNA which is differentially expressed (fold change > 2) between the colocalizing and non-colocalizing tissues. We used TargetScan  to identHEK293T cells (ATCC) were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (Invitrogen). Plasmids were transiently transfected into HEK293T cells using the calcium phosphate method .EcoRI and NheI downstream of the Firefly luciferase ORF using Seamless Cloning Kit . The regions of 3′-UTRs cloned into pRF-con and the tested RNA editing sites are listed in Additional file To generate the dual-luciferase 3′-UTR reporter constructs for target validation, PCR fragments of unedited versions of 3′-UTRs for selected genes were amplified from SW480 genomic DNA using primers listed in Additional file BamHI and BglII using Seamless Cloning Kit. Expression constructs of hsa-miR-17, hsa-miR-125a, hsa-miR-26b, and hsa-miR-214 were kindly provided by Dr. Mofang Liu. Sequences of pri-hsa-miR-17, pri-hsa-miR-125a, pri-hsa-miR-26b, pri-hsa-miR-214, and pri-has-miR-4701 inserted in the vectors are listed in Additional file To generate the expression construct of hsa-miR-4701, PCR fragment containing pri-miR-4701 was amplified from SW480 genomic DNA using primers listed in Additional file t test . Biological replicates were n = 3 and data were presented as the mean ± SD.The dual-luciferase 3′-UTR reporter constructs  and miRNA expression constructs or empty pSIF-NEO-IRES-GFP  were co-transfected into HEK293T cells in 6-well plates. Cells were scraped 32 h after transfection, and luciferase activities were measured with the Dual-Luciferase Reporter Assay System (Promega) using the GloMax™ 20/20 Luminometer (Promega) according to the manufacturer’s instructions. The Firefly luciferase activities were calculated as Firefly/Renilla luciferase values and then normalized to the empty pSIF-NEO-IRES-GFP control for each 3′-UTR reporter construct tested. Statistical analyses were performed using Student’s T method relative to that of the Renilla mRNA and further normalized to the empty pSIF-NEO-IRES-GFP control for each 3′-UTR construct tested. Statistical analyses were performed using Student’s t test . Biological replicates were n = 3 and data were presented as the mean ± SD.Total RNAs of HEK293T cells co-transfected with a dual-luciferase 3′-UTR reporter construct and a miRNA expression construct or empty pSIF-NEO-IRES-GFP were isolated using TRIzol™ Reagent  according to manufacturer’s instructions. Total RNAs were treated with RQ1 RNase-free DNase  and then reverse-transcribed into the first-strand cDNAs using Random primer and Superscript III reverse-transcriptase . The cDNAs were further analyzed by real-time PCR using iTaq™ Universal SYBR Green® Supermix  on a LightCycler® 96 Instrument . Primers used in RT-qPCR analyses are listed in Additional file Additional file 1: Table S1. List of analyzed datasets.Additional file 2: Figure S1. Distribution of RNA editing levels (Φ) across 49 analyzed tissues. Figure S2. Scatter plot of the number of edQTL sites normalized by the number of tested sites vs sample size across 49 tissues. Figure S3. Stacked bar plots for the number and proportion of shared and tissue-specific edQTL sites and ASED sites across all tissues. Figure S4. Impact of edQTL SNP on RNA secondary structure and RNA editing. Figure S5. Tissue-dependent genotype effect sizes in muscle vs non-muscle tissues. Figure S6. Allele-specific expression analysis of DHFR with respect to rs1650720. Figure S7. Comparison of miRNA quantification between qPCR and the RNA-seq based pri-miRNA proxy method. Figure S8. Simulations of edQTL and eQTL signals with miRNA targeting unedited transcripts. Figure S9. Simulations of edQTL and eQTL signals with miRNA targeting edited transcripts. Figure S10. Examples of nonsynonymous edQTL sites. Figure S11. GWAS traits associated with edQTL and eQTL signals of FADS1. Figure S12. Luciferase protein expression data for validating editing-specific targeting of miRNAs to unedited or edited 3′-UTR sequences.Additional file 3: Table S2. List of edQTL sites across the 49 tissues.Additional file 4: Table S3. List of ASED sites across the 49 tissues.Additional file 5: Table S4. List of edQTL sites with effect sizes correlated (R2 ≥ 0.5) to median ADARB1 levels across the 49 tissues.Additional file 6: Table S5. List of nonsynonymous edQTL sites.Additional file 7: Table S6. List of edQTL sites associated with GWAS traits.Additional file 8: Table S7. Summary of colocalization analysis of edQTL and eQTL signals.Additional file 9: Table S8. List of miRNA perturbation datasets.Additional file 10: Table S9. List of differential RNA editing sites upon miRNA perturbation.Additional file 11: Table S10. List of miRNA-mediated tissue-specific edQTL:eQTL colocalization events.Additional file 12: Table S11. Number of tested sites and tested site-SNP pairs per tissue.Additional file 13: Table S12. List of edQTL p-value cutoffs for FDR of 10% across the 49 tissues.Additional file 14: Table S13. Primer sequences used for 3′-UTR luciferase reporter assays.Additional file 15: Table S14. Description of plasmids used for 3′-UTR luciferase reporter assays.Additional file 16. Review history.


Here, we revisit the effects of open unc-64/syntaxin by generating knockin (KI) worms. The KI animals exhibit enhanced spontaneous and evoked exocytosis compared to WT animals. Unexpectedly, the open syntaxin KI partially suppresses exocytosis defects of various mutants, including snt-1/synaptotagmin, unc-2/P/Q/N-type Ca2+ channel alpha-subunit and unc-31/CAPS, in addition to unc-13/Munc13 and unc-10/RIM, and enhanced exocytosis in tom-1/Tomosyn mutants. However, open syntaxin aggravates the defects of unc-18/Munc18 mutants. Correspondingly, open syntaxin partially bypasses the requirement of Munc13 but not Munc18 for liposome fusion. Our results show that facilitating opening of syntaxin enhances exocytosis in a wide range of genetic backgrounds, and may provide a general means to enhance synaptic transmission in normal and disease states.Assembly of SNARE complexes that mediate neurotransmitter release requires opening of a ‘closed’ conformation of UNC-64/syntaxin. Rescue of  unc-13 nulls as well as in diverse C. elegans mutants.Opening of the UNC-64/syntaxin closed conformation by UNC-13/Munc13 to form the neuronal SNARE complex is critical for neurotransmitter release. Here the authors show that facilitating the opening of syntaxin enhances exocytosis not only in  This four-helix bundle is believed to be partially formed before Ca2+ influx4. Ca2+, acting through synaptotagmin-16, triggers full zippering of the SNARE complex, which ultimately results in fusion of the vesicle with the plasma membrane.Synaptic vesicle exocytosis provides the chemical basis for neuronal communication, enabling the amazing diversity of functions of the brain. The SNARE (soluble NSF-attachment receptor) proteins syntaxin, synaptobrevin/VAMP, and SNAP-25 play a central role in exocytosis by forming a tight SNARE complex2+ entry. The priming process is tightly controlled by multiple proteins, including Munc18-1/UNC-189, Munc13-1/2/UNC-1312, Tomosyn15, and RIM/UNC-1017. However, the precise mechanisms through which these proteins mediate priming is still unclear.A biochemical step preceding the full fusion is often referred to as “priming.” It involves formation of the fusion-competent state of synaptic vesicles just prior to Ca18. The binding of closed syntaxin and Munc18-1/UNC-18 has been shown to be critical for the level and plasmalemmal localization of syntaxin22. However, when held closed by Munc18-1/UNC-18, syntaxin is unable to interact with synaptobrevin and SNAP-25 to form SNARE complexes24. Munc13-1/UNC-13 was postulated to open syntaxin and consequently promote SNARE complex assembly and subsequent exocytosis at axon terminals. This important hypothesis originated from studies in which multi-copy overexpression of a constitutively open form of syntaxin/UNC-64 in Caenorhabditis elegans partially restored motility and strongly rescued synaptic vesicle exocytosis defects of unc-13 null worms25. The rescue was suggested to be due to a specific genetic interaction between unc-13 and syntaxin, as expression of the open syntaxin in unc-64-null (js21) mutant26 did not enhance exocytosis compared with the wild-type (WT) syntaxin and did not rescue the reduced exocytosis caused by reduced Ca2+ influx in a severe loss-of-function mutant (e55) of UNC-2 Ca2+ channels25. This model also received support from diverse biochemical experiments, including the demonstration that the MUN domain of Munc13-1 enhances SNARE complex assembly starting from the Munc18-1-closed syntaxin-1 complex29.Syntaxin/UNC-64 is a key SNARE protein that is crucial for exocytosis. It exists in an open and a closed conformation, the latter forming a tight complex with Munc18-1/UNC-18unc-10/RIM mutants17 and dense core vesicle-docking defects in unc-31/CAPS mutants30, calling into question the specificity of the genetic interaction between open syntaxin and unc-13, as well as others. Strong overexpression of syntaxin may not inform on the full physiological state or functions of the endogenous gene products. Indeed, the extent of open syntaxin-mediated restoration of evoked neurotransmitter release in unc-13-null mutant by these transgenes was variable in C. elegans25.However, multicopy expression of open syntaxin was also found to rescue the exocytosis defects in C. elegans was quite different from that of open syntaxin-1B knock-in (KI) mice32. In particular, open syntaxin-1B led to enhanced Ca2+ sensitivity and fusion competency, as well as an increase in spontaneous release in hippocampal neurons31, which was not observed in open syntaxin worms25. In measurements performed at the Calyx of Held, the open syntaxin-1B mutation enhanced the speed of evoked release and accelerated fusion pore expansion32. These phenotypes were postulated to arise from an increase in the number of SNARE complexes formed on vesicles, as a consequence of the facilitation of syntaxin-1B opening. However, use-dependent depression of excitatory postsynaptic currents (EPSCs) was increased in hippocampal synapses, suggesting a reduction in readily releasable pool (RRP) size in the open syntaxin-1B mutants due to reduced interactions between open syntaxin-1B and Munc18-1, and a corresponding decrease in the levels of both proteins31. Furthermore, open syntaxin-1 was reported to fail or yield very limited rescue of phenotypes observed in Munc13-1 knockout (KO) or Munc13-1/2 double KO (DKO) mice33.Moreover, the reported phenotype of multicopy open syntaxin in C. elegans. We then introduced the LE open mutation into various exocytosis mutant backgrounds to systematically examine the genetic interactions between open syntaxin and other regulators of exocytosis. The phenotype of open syntaxin and its genetic interactions with other synaptic transmission mutants only shared limited similarity with the ones previously described using multicopy transgenes25. Our data show that the open syntaxin KI enhances neurotransmitter release and can partially rescue the phenotypes of a wide variety of exocytosis mutants except for Munc18/UNC-18. These results support the proposal that increasing the number of assembled SNARE complexes leads to enhanced neurotransmitter release and suggest that controlling the opening of syntaxin provides a general avenue to modulate synaptic transmission, which may help to develop therapeutic strategies for neurological diseases with impaired synaptic function.In this study, we re-evaluated the effects of the open form of syntaxin by generating the first in vivo KI model of the open syntaxin mutant  in 18. Previous studies demonstrated that multicopy expression of UNC-64, the C. elegans syntaxin, harboring the analogous L166A and E167A mutations led to slower-moving animals than the WT without affecting the level of exocytosis25. To determine the effects of a KI open syntaxin mutation on exocytosis, we generated unc-64(sks4) mutants where we introduced an L166A and E167A mutation in the unc-64 endogenous locus by CRISPR/Cas9-directed homologous recombination  western blot analyses , open syntaxin KI worms exhibited comparable (p = 0.46) thrashing rates to N2 WT worms 36, with the open syntaxin KI mutant to assay for thrashing ability and aldicarb sensitivity  double mutants exhibited greater thrashing rates and paralysis in response to aldicarb than those observed for the snt-1(md290) mutant  and evoked release is triggered by blue light37.In open syntaxin KI and open syntaxin KI; snt-1(md290) mutants in the zxls6 background. When stimulated by 10 ms blue light (3.75 mW/mm2), open syntaxin KI mutants exhibited a significant increase in the half-width and charge transfer of EPSCs compared to WT Fig. Open syntaxin KI; snt-1(md290) mutants exhibited increases in the amplitude as well as the half-width and charge transfer of EPSCs compared with snt-1(md290) animals -null mutant better than the WT syntaxin and did not rescue the reduced exocytosis caused by reduced Ca2+ influx in a severe loss-of-function mutant (e55) of UNC-2 Ca2+ channels25. UNC-2 is an α-subunit of P/Q/N-type CaV2-like voltage-gated calcium channels, which control the influx of calcium upstream of synaptic vesicle exocytosis38. The e55 mutant has a Q571Stop mutation in the CaV2-like voltage-gated calcium channel α-subunit, which reduces calcium current and leads to impaired locomotion and exocytosis39. As our open syntaxin KI, or unc-64(sks4), increases synaptic exocytosis compared to WT N2 .The key evidence that supported a specific genetic interaction between open syntaxin and UNC-13 derived from the observation that open syntaxin did not rescue exocytosis of the unc-64js1-null muunc-2(e55) worms exhibited reduced thrashing and aldicarb sensitivity, whereas open syntaxin KI; unc-2(e55) double mutants displayed robustly rescued thrashing (p = 0.00) compared to the unc-2(e55) mutant alone, and an aldicarb sensitivity comparable to the WT level , and the open syntaxin; unc-2(e55) double mutants displayed similar amplitudes, but there was markedly reduced mPSC frequency in the unc-2(e55) worms that were rescued by open syntaxin KI in the double mutant   exhibited striking hypersensitivity to aldicarb  was not greater than that of the N2 WT  double mutants appeared to exhibit a slight further increase of aldicarb sensitivity when compared with unc-2(hp647) alone  mutant (0.0125/min) was slightly alleviated by open syntaxin KI, which increased thrashing of open syntaxin KI; unc-13(s69) double mutant to 0.713/min  nor as strong as the effect of multicopy open syntaxin, which was reported to be ~6/min25. Moreover, we did not observe an increase in aldicarb sensitivity when compared to the unc-13(s69) mutant after the usual 4 h exposure  worms were paralyzed, compared to the 7% paralyzed unc-13(s69) worms. All WT worms paralyzed at the end of the 24 h. Thus, there is only a weak rescue of acetylcholine release from unc-13(s69) animals.Unlike multicopy expression of open syntaxin in  WT Fig.  and rescmin Fig. . Howeverure Fig. . After 2unc-13(s69) animals by multicopy expression of open syntaxin25. We therefore performed electrophysiological analyses of the effects of open syntaxin KI on unc-13(s69) mutants. The amplitudes of the mPSCs in the unc-13(s69) mutant were similar to those of the N2 worms, but the frequency of mPSCs were drastically reduced  background enhanced mPSC frequently significantly from <0.5 Hz to ~2 Hz  mutants, we generated unc-13(s69) as well as open syntaxin KI; unc-13(s69) mutants in the zxIs6 background. When stimulated by 10-ms blue light, we found that although there was almost no evoked release in unc-13(s69) mutant, open syntaxin significantly increased evoked release in the unc-13(s69) background  mutants possess a C1029fs mutation in both isoforms that results in a severe deleterious phenotype such that rescue with open syntaxin may be minimal. Therefore, we investigated whether the KI open syntaxin can rescue weaker loss-of-function alleles of unc-13: e51, e1091, and n2813. e51 and e1091 mutants are null in their LR isoform only, while n2813 mutants possess a partial loss-of-function gene that results in a single S1574R missense mutation in both UNC-13 isoforms12. Open syntaxin KI; unc-13(e51) double mutants did not show rescued thrashing (p = 0.91) but did display increased sensitivity to aldicarb compared to the unc-13(e51) mutant alone  double mutants did not show rescued thrashing (p = 0.13) but did exhibit increased sensitivity to aldicarb compared to the unc-13(e1091) alone  double mutant displayed rescue in thrashing (p = 0.00) compared to the unc-13(n2813) mutant alone  double mutant was also enhanced compared to the unc-13(n2813) mutant alone  and Middle and Right region (MR) isoformsone Fig. . Similarone Fig. . Finallyone Fig. . Aldicarone Fig. . Overallunc-13(s69) by open syntaxin KI could be due to too severe impairment of synaptic vesicle priming in the absence of unc-13. In this context, the tom-1 mutant that lacks Tomosyn, a protein that competes with synaptobrevin for SNARE complex formation42, partially rescued unc-13 phenotypes and multicopy expression of the open syntaxin mutant further increased the rescue to a modest extent15. In contrast, we recently discovered an interesting synergism between a KI of an unc-18 mutant containing a point mutation (P334A) that is believed to unfurl a loop involved in synaptobrevin binding and the tom-1(ok285)-null mutant in rescuing the unc-13(s69) mutant in synaptic vesicle exocytosis43. That is, although unc-18(P334A) KI or tom-1(ok285) had a limited rescuing effect in aldicarb sensitivity of the unc-13(s69) mutant, in combination they restored aldicarb sensitivity to the WT level. Therefore, we investigated whether introducing open syntaxin as a KI can restore unc-13(s69) strongly in the tom-1 null background.A limited rescue of tom-1 on acetylcholine release and thrashing. As previously reported43, tom-1 null exhibited slightly reduced motility and thrashing compared to N2 WT, despite the increased acetylcholine release  mutant, it further increased aldicarb sensitivity , we observed that the open syntaxin partially increased motility and acetylcholine release of unc-13 in the absence of tom-1  mutant in the absence of TOM-1 and UNC-13. As we previously reported, the aldicarb sensitivity of unfurled unc-18(sks2) KI; tom-1(ok285); unc-13(s69) reached N2 WT levels  mutant, was also reported to rescue exocytosis defects of unc-10 mutant17 as well as docking defects of dense core vesicles of unc-31 mutant. UNC-10 can bind and activate UNC-1346. UNC-31 is involved in dense core vesicle exocytosis but may also influence synaptic vesicle exocytosis48. To determine whether open syntaxin KI indeed enhances exocytosis of these synaptic exocytosis mutants, we crossed severe loss-of-function mutants, unc-10(md1117) and unc-31(e928) C. elegans, with open syntaxin KI mutants to generate double mutants, and assayed for thrashing ability and aldicarb sensitivity  double mutants displayed moderate rescue in thrashing rates (p = 0.00), as well as aldicarb sensitivity  double mutants also displayed moderate rescue of thrashing (p = 0.00), but restored aldicarb sensitivity to levels similar to those of WT worms  and neomycin that disrupts proper transcription of the unc-18 gene43.Thus far, open syntaxin KI increased exocytosis to some degree in all the genetic backgrounds that we tested. Previous work suggested that multicopy over-expression of syntaxin does not bypass the requirement of UNC-18unc-18 alleles, thrashing rate was severely reduced and very little to no aldicarb sensitivity was observed  strongly reduced this thrashing activity . The double mutant and md299 mutant displayed similarly poor aldicarb sensitivity. Therefore, worms were left overnight in the aldicarb plate and examined after 24 h for paralysis. At the end of the 24-hour period, 100% of WT worms were paralyzed, whereas ~7% of the unc-18(md299) worms were paralyzed, and double mutants did not paralyze on 1 mM aldicarb even after 24 h  double mutants were too small and sick to perform reliable neuromuscular junction preparations for electrophysiology.We examined the effects of open syntaxin KI on und Fig. . The ampunc-18 loss-of-function mutants. The slower growth rate and smaller size of unc-18 single mutants were previously reported49. Starting from 15 eggs (day 0) in N2 WT worms, by day 7 the plate is populated with adults and the OP50 bacterial lawn is depleted. Because of their impaired movement, the various unc-18 mutants were unable to fully populate the nematode growth media (NGM) plate and deplete the entire OP50 bacterial lawn. However, the areas of the plate where they were located were completely populated with smaller-sized adults and depleted of OP50 by day 9. In contrast, the open syntaxin KI; unc-18 mutants failed to populate the plate or deplete the bacterial lawn to the same extent as the unc-18 mutants by day 9  and liposomes containing syntaxin-1 and SNAP-25 (T-liposomes) in the presence of NSF and α-SNAP requires Munc18-1 and a Munc13-1 C-terminal fragment led to a model whereby Munc18-1 and Munc13-1 orchestrate SNARE complex assembly in an NSF-αSNAP-resistant manner, and provided a basis to understand the critical requirement of Munc18-1/UNC-18 and Munc13/UNC-13 for neurotransmitter release51.Membrane fusion assays using reconstituted proteoliposomes provide a useful tool to correlate the physiological effects of mutations in components of the release machinery observed in vivo with the effects of these mutations in vitro on membrane fusion using minimal systems, yielding key insights into the mechanisms underlying the phenotypes52, we observed fast, Ca2+-dependent fusion between V-liposomes and T-liposomes containing WT syntaxin-1 in the presence of NSF, α-SNAP, Munc18-1, a fragment spanning the C1, C2B, MUN, and C2C domains of Munc13-1 (C1C2BMUNC2C), and a fragment spanning the C2 domains that form the cytoplasmic region of synaptotagmin-1 (C2AB) 53, and correlate with the partial rescue of unc-13 phenotypes by the syntaxin-1 open mutation. Overall, these data nicely correlate with our in vivo experiments showing that the open syntaxin mutant can partially rescue unc-13 phenotypes but not the phenotypes of unc-18 mutants and are consistent with the notion that mutations that facilitate SNARE complex formation render membrane fusion and neurotransmitter release less critically dependent on Munc13/UNC-13.We used an analogous approach to examine how the open LE mutation that opens syntaxin-1 affects the requirement of Munc13-1 and Munc18-1 for liposome fusion, and thus test whether these reconstitution experiments correlate with the phenotypes of our genetic studies. Using an assay that simultaneously monitors lipid and content mixingAB) Fig. . Similarn-1 Fig. . Moreoven-1 Fig. . These r32, whereas this effect was not observed in more conventional hippocampal synapses31. Therefore, we analyzed the kinetics of mPSCs of open syntaxin KI animals at the C. elegans neuromuscular junction. We found that there is no difference in rise time of mPSCs between WT control and open syntaxin KI animals  and the mixture of two signals may interfere with the detection of subtle differences in fusion pore kinetics of individual vesicles.Despite the availability of many synaptic mutants, most mutants do not affect the fusion kinetics of synaptic vesicle fusion. Importantly, a recent study of open syntaxin-1B in mice showed that it significantly reduces rise time in miniature EPSCs (mEPSCs) in high-fidelity Calyx of Held synapsesunc-49(e407) mutant, which lacks a functional GABAA receptor. In the thrashing assay, unc-49-null worms exhibited severely reduced motility  background  mutants and open syntaxin; unc-49(e407) double mutants, as well as no differences in the kinetics of the mPSCs . The tight complex between Munc18-1/UNC-18 and closed syntaxin serves as the starting point for this mechanism, and Munc13/UNC-13 was proposed to mediate the transition to the SNARE complex by opening syntaxin. A key finding that served as a basis for this model was that multicopy expression of the constitutively open LE syntaxin mutant18 rescued the total abrogation of release observed in C. elegans unc-13 nulls25. Subsequently, KI of open syntaxin-1B in mice was shown to enhance spontaneous release and vesicular release probability, which was proposed to arise from enhanced SNARE complex assembly, although open syntaxin-1B KI did not rescue the lethal Munc13-1 KO phenotype31. Our data now show that KI of open syntaxin in C. elegans enhances exocytosis in an otherwise WT background, as well as in a wide variety of genetic backgrounds characterized by diverse defects in synaptic transmission. These results indicate that the open syntaxin mutation provides a general means to enhance synaptic transmission and that increasing the number of SNARE complexes can overcome phenotypes that arise not only from defects in the SNARE complex assembly pathway but also from impairment of other aspects such of Ca2+ sensing, Ca2+ influx, or neurotransmitter recognition. These findings also suggest that manipulating SNARE complexes may provide a powerful tool for functional studies of synaptic transmission and neural networks, as well as opportunities to develop therapies for diverse neurological disorders.Great advances have been made in the past three decades in our understanding of the mechanism of neurotransmitter release, showing that release depends on SNARE complexes that bridge the vesicle and plasma membranes, and that SNARE complex assembly is orchestrated by Munc18-1/UNC-18 and Munc13/UNC-13 . Hence, these results were not incompatible with the proposed role of Munc13/UNC-13 in opening syntaxin.The pioneering studies of Richmond et al.open syntaxin KI increases synaptic vesicle exocytosis in an otherwise WT background  und Fig. ; (ii) op-1 Figs.  and 3, uc-2 Fig. , tom-1  null mutant    null mutant via the other Ca2+ channels, namely EGL-19, and we propose that the open syntaxin-1 mutant overcomes the reduced Ca2+ influx in unc-2(e55) mutant by increasing the Ca2+ sensitivity of the release machinery, which was actually shown in Gerber et al.31. There are at least two additional Ca2+ channels  in addition to UNC-2 (P/Q/N-type) in the genome of C. elegans56. Importantly, Liu et al.57 showed that SLO-2 K+ channels regulate neurotransmitter release from cholinergic and GABAergic motor neurons and that the activity of SLO-2 in motor neurons depends on Ca2+ entry through EGL-19, but not other Ca2+ channels (CCA-1 or UNC-2). Thus, EGL-19 Ca2+ channels play a regulatory role in neurotransmitter release from motor neurons, although direct evidence of EGL-19 in neurotransmitter release had been difficult to obtain due to the lethality of egl-19 null mutant58. Therefore, although UNC-2 is the major Ca2+ channel that controls neurotransmitter release, EGL-19 seems to play an additional role. This also explains why the null mutant of unc-2(e55) still shows significant residual acetylcholine release and motility  in the genome of C. elegans. These isoforms may replace SNT-1 and function similarly but not very efficiently, and an increased number of SNARE complexes by open syntaxin can compensate for this defect.Why can open syntaxin almost fully rescue the 0) Figs.  or unc-1unc-2e5 null muunc-13 phenotypes by the open syntaxin KI  mutation  mutant better than open syntaxin , but not in the absence of Munc18-1 , which may imply that the diffusion time of neurotransmitter glutamates to reach receptors is short, allowing detection of small changes in the kinetics of vesicle fusion. The rise time in C. elegans neuromuscular junctions is significantly slower at ~0.6 ms. However, the effects of synaptobrevin cleavage by tetanus toxin on the amplitude and kinetics were clearly observed in hippocampal cultured neurons in which the rise time is 1-2 ms69. It might be possible to find synaptic mutants which can slow down the kinetics of vesicle fusion events at the appreciable level in C. elegans in the future.Does open syntaxin enhance fusion pore opening kinetics of individual vesicles? Several mechanisms to control fusion pore opening have been suggested, including the copy number of SNARE complexes. Nevertheless, there were almost no synaptic mutants known that affect the fusion kinetics of synaptic vesicle fusion. Using Calyx of Held synapses in mice, Acuna et al.78. Similarly, mutations in proteins involved in the trafficking of postsynaptic neurotransmitter receptors such as Shank381, and neuroligin-3 and -482 are strongly implicated with ASD. Thus, small chemicals that facilitate opening of syntaxin-1 have the potential to alleviate many neurological diseases derived from defects in synaptic transmission by increasing synaptic transmitter release.Taken together, our results show that open syntaxin can suppress a wide range of exocytosis defects but not those of Munc18/UNC-18 mutants. Recent studies show that mutations in syntaxin-1B, Munc18, Munc13, and Tomosyn underlie a wide spectrum of childhood epilepsy and autism spectrum disorders (ASDs)CTGTACCTGCCTACAAGGcgg-3′ sequence and 5′-AAGACGAACCCAGAGAACATcgg-3′ sequence within the intron of unc-64 genomic region  and downstream (right arm) sequences of the CRISPR target site were amplified by PCR using pTX21 (a kind gift from Dr. Michael Nonet), which contains the genomic sequence of the unc-64 gene26. The left arm PCR product (~1.1 kb) was digested with SacI and NotI, whereas the right arm PCR product (~1.7 kb) was digested with SpeI and ClaI. Each of the digested products was ligated into pBluescript, followed by sequencing of the ligated products. To generate a KI mutant allele, site-directed mutagenesis was conducted on pBluescript containing the right arm. The mutagenesis product was verified by sequencing. The dual-marker selection cassette (~5.4 kb) was digested with SpeI and NotI and ligated into pBluescript containing both arms34. Third, multiple plasmids were injected into N2 animals: a vector encoding Cas9, the repair vector, the DNA product of sgRNA, and several injection markers (Pmyo-3-mCherry and Prab-3-mCherry). Fourth, screening for KI animals began by applying neomycin to the progeny of the injected animals. Then, animals that were neomycin resistant, GFP positive, and mCherry negative were selected as KI candidates and genotyped for verification, resulting in the selection of unc-64(sks3) worm. We then injected Cre-recombinase gene into unc-64(sks3) worms to remove GFP and neomycin-resistant gene. The genomic sequence of the resulting worm unc-64(sks4) was shown in Supplementary Fig. The strategy is shown in Supplementary Fig. Escherichia coli, as a food source. The C. elegans strains used were listed in Table unc-10(md1117), unc-13(e51), (e1091), (n2813), unc-31(e928), unc-2(e55), unc-18(md299), and snt-1(md290) worms were purchased from the Caenorhabditis Genetics Center (University of Minnesota); VC223 strain with a genotype of tom-1(ok285) was provided by the C. elegans Reverse Genetics Core Facility at the University of British Columbia; and unc-2(hp647) was generated in Mei Zhen’s lab40. We crossed these mutants with unc-64(sks4) to generate double and triple mutants. Strains with zxIs6 background were cultured in the dark at 22 °C on OP50-seeded NGM plates supplemented with all-trans retinal (0.5 mM). Fifteen to 20 adult worms from each plate were dissolved in worm lysis buffer to extract their DNA for PCR. PCR was conducted to confirm the genotype of double or triple mutants using primers purchased from IDT DNA. PCR primers used to verify unc-64(sks4) LE open mutant allele in comparison with WT allele are SS1727 (5′-GGTGTAAGGGACGAATTCAGAG-3′) and SS1728 5′-CAAACCTGTTGGCTATCTGTGA-3′).All strains used in the study were maintained at 22 °C on 30 mm agar NGM plates seeded with OP50, a strain of unc-64(sks4) worms on 3.5 or 6 cm NGM plates. When the plates were full of worms with little OP50 left, worms were harvested and washed three times with a buffer containing 360 mM sucrose and 12 mM HEPES. These worms were resuspended in ∼5 times volume of the buffer and frozen at −80 °C until use. The defrosted worms were sonicated on ice 10 times with a 5 s burst. The resulting lysate was centrifuged for 15 min to pellet the cuticle, nuclei, and other debris. After centrifugation, the supernatant  was transferred to a clean microcentrifuge tube with an equal volume of sample buffer (2×). Fifty micrograms of samples were subjected to SDS-polyacrylamide gel electrophoresis followed by immunoblotting. The immunoblot signal was detected with ECL Prime Western Blotting Detection Reagent  and a Chemidoc XRS + Imaging System (Bio-Rad), and quantified by ImageJ program. After the first round of immunoblotting to detect UNC-64 with rabbit polyclonal anti-syntaxin-1 antibody 18, the membrane was re-used for a second immunoblot assay with a mouse monoclonal anti-β-tubulin antibody  to correct for sample loading.Protein extract was prepared by culturing N2 and C. elegans in liquid medium. Briefly, worms were bleached to release their eggs and were then synchronously grown to young adulthood. Young adult worms were placed in a 60 μL drop of M9 buffer on a 30 mm petri dish cover. After a 2 min recovery period, worms were video-recorded for 2 min using an OMAX A3580U camera on a dissecting microscope with the OMAX ToupView v3.7 software. The number of thrashes per minute were manually counted and averaged within each strain. A thrash was defined as a complete bend in the opposite direction at the midpoint of the body. At least 40 worms for each strain was measured in each analysis.Motility of each strain was determined by counting the thrashing rate of Aldicarb sensitivity was assessed using synchronously grown adult worms placed on non-seeded 30 mm NGM plates containing 0.3 mM or 1 mM aldicarb. All assays were done in 1 mM aldicarb plates unless specified otherwise. Over a 4 or 24 h period, worms were monitored for paralysis at 15 or 30 min intervals. Worms were considered paralyzed when there was no movement or pharyngeal pumping in response to three taps to the head and tail with a platinum wire. Once paralyzed, worms were removed from the plate. Six to 7 sets of 10–20 worms were examined for each strain.Growth speed was assessed by eye using an OMAX A3580U camera on a dissecting microscope. Briefly, 15 eggs were extracted from adult worms into OP50-seeded NGM plates and placed along the edge of the bacterial lawn roughly equidistance from each other. Photos of the plates were taken daily at ×1 magnification with the OMAX ToupView v3.7 software for up to 7 days for N2 worms, and up to 9 days for the other strains. Growth speed and body size were compared by eye based on photos taken on day 9.C. elegans was described previously . Briefly, 1 or 2 days old hermaphrodite adults were glued to a sylgard -coated cover glass covered with bath solution. The integrity of the neuromuscular junction preparation was visually examined via DIC microscopy, and anterior muscle cells were patched using fire-polished 4–6 MΩ resistant borosilicate pipettes . Membrane currents were recorded in the whole-cell configuration by HEKA EPC-9 patch clamp amplifier, using the PULSE software (Version 8.74) and processed with Igor Pro 6.21 (WaveMetrics) and Clampfit 10.2 . Data were digitized at 10 kHz and filtered at 2.6 kHz.The dissection of the zxIs6 was performed with an light-emitting diode lamp at a wavelength of 460 ± 5 nm (3.75 mW/mm2), triggered by the PULSE software for 10 ms. Muscle cells were recorded with a holding potential of −60 mV. The recording solutions were as described in our previous studies83. Specifically, the pipette solution contains (in mM): K-gluconate 115, KCl 25, CaCl2 0.1, MgCl2 5, BAPTA 1, HEPES 10, Na2ATP 5, Na2GTP 0.5, cAMP 0.5, cGMP 0.5 pH 7.2 with KOH, ~320 mOsm. The bath solution consists of (in mM): NaCl 150, KCl 5, CaCl2 5, MgCl2 1, glucose 10, sucrose 5, HEPES 15 pH 7.3 with NaOH, ~330 mOsm. All chemicals were from Sigma. Experiments were performed at room temperatures (20–22°C).Light stimulation of 2AB fragment (residues 131–421), full-length Chinese hamster NSF, full-length Bos Taurus αSNAP, and a rat Munc13-1 C1C2BMUNC2C fragment  were described previously (ref. 84 and references therein). We note that full-length rat syntaxin-1A was purified in buffer containing dodecylphosphocholine to prevent its aggregation85.Bacterial expression and purification of full-length rat syntaxin-1A, the rat syntaxin LE mutant, a cysteine-free variant of full-length rat SNAP-25a, a full-length rat synaptobrevin-2, full-length rat Munc18-1, rat synaptotagmin-1 C52. Briefly, vesicle (V)-liposomes with reconstituted rat synaptobrevin-2  contained 39% palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 19% 1,2-dioleoyl-sn-glycero-3-phospho-L-serine (DOPS), 19% palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), 20% cholesterol, 1.5% 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine-N- (NBD-PE), and 1.5% Marina Blue DHPE. T-liposomes with reconstituted rat syntaxin-1A or open syntaxin-1A LE mutant together with rat SNAP-25A  contained 38% POPC, 18% DOPS, 20% POPE, 20% cholesterol, 2% L-α-phosphatidylinositol-4,5-bisphosphate, and 2% palmitoyl-2-oleoyl-sn-glycerol. Lipid solutions were then mixed with respective proteins and with 4 μM Phycoerythrin-Biotin for T-liposomes or with 8 μM Cy5-Streptavidin for V-liposomes in 25 mM HEPES pH 7.4, 150 mM KCl, 1 mM tris(2-carboxyethyl)phosphine, 10% glycerol (v/v). V-liposomes (0.125 mM lipids) were mixed with T-liposomes (0.25 mM lipids) in a total volume of 200 μL in the presence of 2.5 mM MgCl2, 2 mM ATP, 0.1 mM EGTA, 5 μM streptavidin, 0.4 μM NSF, 2 μM α-SNAP, 1 μM Munc18-1, 1 μM synaptotagmin-1 C2AB, and 1 μM excess SNAP-25 with or without 0.2 μM Munc13-1 C1C2BMUNC2C. Before mixing, T-liposomes were incubated with NSF, MgCl2, ATP, EGTA, streptavidin, NSF, αSNAP, and Munc18-1 at 37 °C for 25 min. CaCl2 (0.6 mM) was added at 300 s to each reaction mixture. A spectrofluorometer  was used to measure lipid mixing from de-quenching of the fluorescence of Marina Blue-labeled lipids  and content mixing from the development of Förster resonance energy transfer between PhycoE-Biotin trapped in the T-liposomes and Cy5-streptavidin trapped in the V-liposomes . All experiments were performed at 30 °C. Lipid and content mixing were normalized as the percentage values of the maximum signals obtained by addition of 1% b-OG at the end to each reaction mixture (for lipid mixing) or to controls without streptavidin to measure maximal Cy5 fluorescence (for content mixing).Assays that simultaneously measure lipid and content mixing were performed as previously describedp-value < 0.05 as the threshold for statistical significance. For comparison of multiple groups, one-way analysis of variance was conducted, followed by Tukey’s range test, with a significance level of 0.05.Statistical analyses were done in OriginPro2018 using the independent t-test for two-group experiments with a Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary