The emergence of recent SARS-CoV-2 has become a global health issue. This single-stranded positive-sense RNA virus is continuously spreading with increasing morbidities and mortalities. The proteome of this virus contains four structural and sixteen nonstructural proteins that ensure the replication of the virus in the host cell. However, the role of phosphoprotein (N) in RNA recognition, replicating, transcribing the viral genome, and modulating the host immune response is indispensable. Recently, the NMR structure of the N-terminal domain of the Nucleocapsid Phosphoprotein has been reported, but its precise structural mechanism of how the ssRNA interacts with it is not reported yet. Therefore, here, we have used an integrated computational pipeline to identify the key residues, which play an essential role in RNA recognition. We generated multiple variants by using an alanine scanning strategy and performed an extensive simulation for each system to signify the role of each interfacial residue. Our analyses suggest that residues T57A, H59A, S105A, R107A, F171A, and Y172A significantly affected the dynamics and binding of RNA. Furthermore, per-residue energy decomposition analysis suggests that residues T57, H59, S105 and R107 are the key hotspots for drug discovery. Thus, these residues may be useful as potential pharmacophores in drug designing. This virus family has a large genome (30 kb RNA genome) that encodes four structural proteins, small envelope (E), matrix (M), nucleocapsid phosphoprotein (N), spike (S), and sixteen nonstructural proteins (nsp1-16) that together, ensure replication of the virus in the host cell The first 66.66% part (two-thirds) of SARS-CoV-2 genome is known as ORF1a/b region and encodes for the non-structural proteins, whereas the remaining one-third part of genome encodes the accessory proteins and four structural proteins In corona viruses the multifunctional N protein is essential for transcription as well as replication. N protein binds to the viral genome and contributes in packing it to get long helical nucleocapsid structure Since the role of Nucleocapsid Phosphoprotein to recognize the RNA is crucial The NMR structure of the SARS-CoV-2N-terminal and C-terminal domains of nucleocapsid phosphoprotein has recently been reported but the role of N-terminal domain in recognizing the RNA is not clear 22.1) was extracted from Protein Data Bank For docking studies, the recently submitted the solution NMR structure of the SARs-CoV-2 nucleocapsid phosphoprotein , ensembles were applied to the system for the MD simulation studies. Particle Mesh Ewald (PME) SHAKE algorithm was used for hydrogen interactions The WT and mutant type complex were subjected to molecular dynamics (MD) simulation studies using the Amber package 2.5Principal Component Analysis (PCA) 2.6A time subordinate movements of Cα atoms was obtained by using dynamics cross-correlation maps (DCCM) approach Cij) represents the time-correlated data of protein between the i and j atoms. Cα atoms from the 20,000 snapshots were chosen to construct the matrix at 0.002 ns intervals. In the plot, the positive values specify correlated motions, whereas negative values indicate anti-correlated motion during the simulation.The matrix  implicit solvent method with the solvent-accessible surface area SASA term. Furthermore, we also performed per-residues energy decomposition analysis to understand the energy contribution of each residue to the whole energy.Each component of the total free energy was estimated using the following equation:33.1A recently reported NMR structure of the N-terminal domain of the SARS-CoV-2 nucleocapsid phosphoprotein was retrieved from RCSB using the PDB ID: 6YI3 reported by Dinesh et al. 3.2A computational mutagenesis approach was used to determine the impact of each alanine substitution. Alanine substitution defines the role of a specific residue to the stability or function of a given protein. Due to its distinguishing features like chemically inert, non-bulky, and methyl functional group attachment, alanine is considered as the best choice to calculate the impact of each residue. Herein, using multiple algorithms, the significance of each interacting residue was determined. Among the total 19 interactions, utilizing the dStability, dAffinity, and change in the binding affinity, ten substitutions were reported to increase the stability. While using the defined criteria, nine substitutions including T51A, H59A, K61A, S105A, R107A, K169A, G170A, F171A, and Y172A, was found to reduce the stability and binding affinity upon substitution. However, substitutions reported by all three tools, including MOE, DrugScorePPI, and mCSM-NA, were selected for further analysis. Using this criterion, two substitutions K61A and K169A, were excluded. The remaining seven substitutions significantly affected the binding and stability of the Protein-RNA complex. Among these four substitutions, T57A, H59A, G170A, and F171Achanged the protein-RNA in the greater fold. While the other substitutions such as S105A, R107A and Y172A were reported to affect the protein-RNA complex comparatively in the lower fold. As shown in Molecular dynamics simulation of wild and seven mutant systems was performed. Different analysis such as RMSDs for stability, RMSF for residual flexibility, Total energy, Principle component Analysis for protein motions, Free energy landscape for protein states transition, DCCM for residues correlated and anti-correlated while binding free energy for the affinity of RNA toward the protein was performed. These analyses significantly increased the understanding of RNA-protein interaction.3.3A comparative study of MD properties on variants and the WT protein complexes was performed to check the stability of MTs during the simulation period. We repeated each simulation run three times. The trajectory was analyzed, and RMSDs were calculated after 400 ns. As given in 3.4The residual flexibility was calculated by mean of RMSF. It can be seen that the wild type and mutant systems exhibit more similar pattern of flexibility. The average RMSF for all the systems was observed to be 2.8 Å. As given the WT, H59, T57, S105 and R107 showed similar pattern of flexibility while the G170, F171 and Y172 possess lower flexibility than the others. The increased flexibility at different regions is due to the loops in the structure. In case of the lower flexibility shown by G170, F171 and Y172 is due to the differential dynamics upon the binding of RNA. The secondary structure given above the RMSF graph justifies the residual flexibility. Overall the residues fluctuation among MTs was detected in difference when compared with WT .Fig. 3RMThe total energies of all the mutants revealed a more similar pattern ranging from −80,800 kcal/mol to −82,600 kcal/mol. On the other hand, the wild type exhibited different total energy as given in 3.5The impact of predicted mutations on N-NTD dynamics could be observed in Furthermore, to obtain conceivable attributed motions, the first two eigenvectors were plotted against each other. The depiction of the blue to red color indicates the flipping over of conformations during the simulation period. Each dot starting from blue and ends at red represent specific frame. Trajectories have been mapped into a two-dimensional subspace using PC1 and PC2 to grasp the complexes conformational transformations. It can be seen that all the complexes attained two conformational states on the subspace differently colored (blue and red) 3.6. The color red is more prevalent in MTs , seems unstable compared to WT. The highest transition states have been observed in H59A, S105A, R107A, and F171A, showing the impact of these residues’ mutation on RNA bindings. WT exhibited two states and separated by an energy barrier. It can also be seen that the WT remained in one energy state for most of the time. G170A and Y172A also attained a more intermediate state (yellow). However, the difference is evident between WT and MTs, depicting the impact of these mutations on FEL. The result specifies the more conformational transition in the MTs compared to WT. Multiple metastable states have been observed in MTs during their structural evolution. These have been separated by low and high-energy barriers. The changes in different structural ensemble at different time nanosecond are given in cartoon structures while the critical regions are shaded. The x and y coordinates, their respective frame number and time (ns) is given in The free energy landscape (FEL) depicts the transition states. To understand the transition mechanism of MTs and WT complexes from metastable to native states, the first two eigenvectors were considered for computing and plotting the FEL of trajectory time. For better understanding the structural evolution, low energy states have been mined. WT demonstrated a significant difference in FEL when compared with MTs, as shown by colors in the plot . The col3.7To investigate the functional displacements of the interaction protein atoms as a function of time, we constructed and analyzed a dynamics cross-correlation matrix (DCCM). During the simulation time (400 ns) wild type showed a more positive correlated motion with a negative strand correlation of loop (ϒ2). All mutants demonstrated variation in correlated motions where the maximum of the residues exhibited positive correlations than wild type complex. All the correlation plots are given in It can be seen that overall the motions are dominated by the correlated motions. In case of the T57A when compared to the wild type the loop (ϒ1) showed a negative correlation while the β3, ϒ5 and ϒ6 showed a positive correlation. On the other hand, H59A showed a positive correlation at ϒ5 region. Here a weak negative correlation at β3 site was observed. S105A possess strong negative correlation except the regions ϒ5 and ϒ6, which showed a positive correlation when compared to the wild type. R107A showed positive correlation at regions β4 and ϒ2 while the rest a similar pattern was observed. Furthermore, G170A showed a weak negative correlation at regions where the wild type showed strong negative correlation. The region ϒ6 was reported to possess positive correlation. In case of F171A and Y172A a more similar pattern of correlation was observed where the region ϒ6 showed strong positive correlation while the other regions showed strong negative correlation. Thus, the substitutions affect the internal dynamics of the interacting proteins and ultimately the biology of binding with the RNA. These results signify that the substitution has brought conformational and dynamical variability and, therefore discloses the structure–function relationship specifically the affinity for binding the RNA molecule.3.8(MMPBSA). The MMGBSA and MMPBSA results for replicate 2 and replicate 3 are given in Free energy computation and analysis were performed to compare the interaction changes in wild type and mutant systems quantitatively. To compute the total free energy, we used 20,000 snapshots from the last 400 ns of the MD simulation trajectory. Both MMGBSA and MMPBSA for each run (three replicates) were calculated. Each contributing term such as van der Waals (vdW), electrostatic, polar solvation, and solvent accessible surface area (SASA) energies were calculated and are given in The MM-GBSA results  also revΔelec energy as shown in The MM/PBSA results shows that WT-RNA complex exhibited the highest binding energy 41.54 ± 12.30), as compared to the MTs complexes . The hig3.9Furthermore, to understand the impact of each residue on the binding of RNA we calculated the energy contribution from each residue to the total energy. Our analysis suggests that among the seven residues T57, H59, S105 and R107 contributes more to the total energy. As given in 4The nucleocapsid phosphoprotein (N) is playing a role in linking the viral + RNA to the membrane. There are two domains, N-terminal RNA binding domain (N-NTD) that binds the RNA. In contrast, the C-terminal domain (CTD), after interaction with the M protein, is involved in anchoring the ribonucleoprotein to the viral membrane In conclusion, residues T57, H59, S105, R107, G170, F171, and Y172 are playing a significant role in binding with RNA of SARS-CoV-2. Alanine scanning further supported the role of these residues when subjected to comprehensive MD simulation. The overall structural dynamics, including RMSD, RMSF, DCCM, and PCA, have been found, influenced by alanine MTs. Binding free energy further supported that these residues might have a role in binding with RNA. Drug development and screening against these residues may be useful for better management of SARS-CoV-2 infections. The fluctuations and changes observed in the longer and repeated simulation could provide better understanding. The observed variations in different replicas are significantly correlated and could aid to design small molecule inhibitors which could target the N-terminal domain of SARs-CoV-2N-NTD protein and may halt the RNA recognition to aid the treatment process.AK, MTK, SS and MJ, conceptualized the study and did the analysis. AA, SSA, MK wrote the manuscript. AA, SSA and MK also contributed to the methodology. AK revised the manuscript and did all the additional analysis. AK contribution is major. DQW is an academic supervisor. He supervised the study.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


In this review, we retraced the ‘40-year evolution’ of molecular docking algorithms. Over the course of the years, their development allowed to progress from the so-called ‘rigid-docking’ searching methods to the more sophisticated ‘semi-flexible’ and ‘flexible docking’ algorithms. Together with the advancement of computing architecture and power, molecular docking’s applications also exponentially increased, from a single-ligand binding calculation to large screening and polypharmacology profiles. Recently targeting nucleic acids with small molecules has emerged as a valuable therapeutic strategy especially for cancer treatment, along with bacterial and viral infections. For example, therapeutic intervention at the mRNA level allows to overcome the problematic of undruggable proteins without modifying the genome. Despite the promising therapeutic potential of nucleic acids, molecular docking programs have been optimized mostly for proteins. Here, we have analyzed literature data on nucleic acid to benchmark some of the widely used docking programs. Finally, the comparison between proteins and nucleic acid targets docking highlighted similarity and differences, which are intrinsically related to their chemical and structural nature. Nowadays computational methods are routinely applied in drug discovery campaigns and its positive impact in research is recognized in the scientific community. Computer-aided drug discovery (CADD) raised in the years 1970s and its continuous progress, together with the advancement in computer technologies, made its usage an indispensable tool. CADD methods are usually divided into two main groups: ligand-based and structure-based. The first approach builds structure-activity models based on ligand structure information, whereas the second method takes advantage of the three-dimensional structure of the biomolecular target to investigate ligand binding. Among the structure-based methods, molecular docking is a well-known tool for the identification of ligand-target recognition. In this review, we will explore the evolution of molecular docking from a single ligand-protein calculation to more recent and sophisticated applications with a particular emphasis on docking applied to nucleic acids (NA) as emerging therapeutic targets.https://www.rcsb.org/) is a repository of experimental macromolecular structures, which is constantly updated. By May 2020, the PDB counted ~163′633 experimental structures of proteins, RNAs, and DNAs belonging to different organisms. The majority of the structures are solved by X-ray crystallography (~145′437) (https://www.rcsb.org/stats/summary) but also nuclear magnetic resonance (NMR) and electron microscopy (EM) techniques strongly contribute in increasing the collection. The introduction of novel protocols and methods in x-ray crystallography enormously ameliorate structure resolution if compared to the first solved myoglobin structure in 1960 . In. In25]. Recent works highlight how large screening protocols involving millions of compounds will positively influence early drug discovery programs and will allow the identification of novel chemotypes belonging to their relative target . The truJust 1.5% of the human genome encodes for proteins, only a 0.05% has been successfully drugged with existing small molecules . If the Small molecules interact with nucleic acids using different mechanisms: intercalation, cross-linkage, strand-cleavage, and reading-molecules. In particular, DNA-binders can interfere with the replication process, which consequently affects the transcription phase, gene expression regulation, and cell proliferation. Similarly, RNA-binders might interfere during either the transcription and translation process, which could affect the splicing machinery. Consequently, they appear as suitable targets for various diseases, not only for the chemotherapeutical area including antivirals and antibacterial , but theDNA is considered as one of the main molecular targets in chemotherapy . The disThe transcription and translation process can be regulated also at the RNA level and its targeting has appeared to be a suitable approach for anti-bacterial and anti-viral therapy. Riboswitches are a regulatory part of the mRNA, which control gene expression and consequently protein biosynthesis B. NaturaThe splicing event consists in introns removal from the pre-mRNA sequence generating the mature form of the mRNA, which will then constitute the template for protein translation. The spliceosome machinery is composed by multiple proteins specifically recognizing RNA motifs. A sophisticated mechanism of interactions among the different constituents precisely rules this process . Indeed,Since the time of the development of molecular docking, the majority of the therapeutic targets investigated were proteins, the refinement of the docking programs was focusing mainly on these. A number of docking programs were modified and retrained in order to be applied also to nucleic acids (NA), whereas others were newly designed. Huge advances have been made to ameliorate algorithm search and scoring functions including different aspects as target flexibility, ligand geometry, and solvent effect. However, molecular docking applied to nucleic acids presents its own set of challenges and certain features might sometimes differ from the ones used for protein docking.Similar to proteins, nucleic acids present their own set of geometrical and structural features, which characterize and distinguish them. DNA is mostly found as a double strand helix, for which three forms exists A, B, and Z. RNA can be found also as a double strand helix for which the A-form is the most present at physiological pH, whereas DNA privileges the B-form. This double helix forms two shallow cavities, the major and minor groove, which travel all along the length of the sequence. Interestingly, it has been seen that the DNA major groove is wider and accessible to large molecules as proteins and peptides. Whereas, DNA minor groove results in being narrow and more suitable to bind small molecules upon water displacements. Contrary, RNA major groove is more prone to interact with small molecules because highly electrostatic and narrower, while the RNA minor groove binds proteins via Van der Waals forces. Moreover, RNA has the characteristic to fold into different secondary structures as bulges, hairpin stem loops, G-quadruplex etc. Overall, similar to proteins, nucleic acids tertiary structures can be distinguished by specific and sophisticated geometrical motifs that form suitable drug-binding pockets able to recognized unique small molecules .If from a structural point of view nucleic acids results in being suitable for target-based drug discovery, the high prevalence of charges and the metal ions poses a major challenge, especially when scoring the free energy of the ligand-NA binding. This is clearly evidenced by the comparison of the electrostatic potential surface of a single nucleic acid base with the one of a neutral or charged amino acid .+. Their mobile nature results indeed difficult to handle with molecular docking and often the strategy of choice is to add to the phosphate a +1 partial charge, implicitly considering the counterions [posC-acc), which describes a peculiar ligand-RNA or protein-RNA interaction occurring between the positive charge of a guanidine moiety  and the partially negatively charged carbonyl oxygen counterpart present in the nucleobases . The nature of this interaction is still debated, as it might be considered electrostatic instead of π-stacking [In a solution, the negative phosphates are normally neutralized by counterions as Nanterions . The hignterions . In partstacking .RNA when applied to RNA [The presence of the phosphate negative charges brings along a multitude of metal ions and water molecules strongly interacting to each other. Therefore, to disrupt the hydration shell ligands needs high polarity when considering the polyanionic character of the nucleic acid molecules. Site-bound ions together with waters are essential for stabilizing and shaping nucleic acids structure as shown for G-quadruplex metal-network  Analogoud to RNA . The latd to RNA . Recentld to RNA  or the Sd to RNA  allowingd to RNA .RNA scoring function [As seen already for proteins, a not-negligible aspect is the intrinsic flexibility of nucleic acids structure, often ignored by docking algorithms. The binding of the ligand to the corresponding RNA or DNA is causing either an induced-fit effect , or a cofunction , as prevfunction . They cofunction . While tfunction .Finally, we want to rationalize the advances and performances of docking programs applied to nucleic acids along the history, which refers to works retrieved from the literature ,72,73,74The first benchmark studies date back to 2004, the original DOCK and Autodock programs were tested against a dataset of 16 RNA complexes. Both programs perform well with rigid/aromatic ligands with an average accuracy  reaching the 78% pose prediction accuracy . Nevertheless, a major difficult task linked to the presence of metal ions and the continuous fast charge exchange between water molecules and ions remains to be solved.In conclusion, this review reports on how molecular docking and its applications have evolved over time, the strategies adopted for partially overcoming the problems linked to ligand-macromolecule recognition, and it points out the remaining challenges to perfectly recapitulate virtually the complexity of intermolecular interactions.


Perceptual decisions are biased toward previous decisions. Earlier research suggests that this choice repetition bias is increased after previous decisions of high confidence, as inferred from response time measures , but als Perceptual decisions not only are based on current sensory evidence but are also influenced by the choice history. Across a wide range of perceptual decision-making tasks, observers tend to repeat their decisions more than is expected by chance . This chWhy does choice history bias occur? This is an especially good question given that, in most laboratory experiments, stimuli are uncorrelated across trials. Repeating previous choices is consequently detrimental to task performance; choice history biases are maladaptive in the contexts of such tasks. However, they are likely adaptive in natural conditions, as our environment usually remains relatively stable over short timescales . CrucialBayesian theories of perceptual decision-making prescribe how previous information should be integrated with current information in a probabilistically optimal manner . Such thSurprisingly, however, it has also been reported that observers are more likely to repeat a previous choice that was based on low, compared to high, sensory evidence . This palow confidence (inferred from low sensory evidence), whereas Urai et al. . In other words, although strong sensory evidence is associated with high confidence on average, choice repetition is smallest after strong sensory evidence and largest after high confidence. It is unknown whether these paradoxical findings can be attributed to variation in confidence within levels of evidence or whether it must be attributed to other causes. For example, other elements of the previous trial, such as the direction of evidence , may play a role in addition to the role of the previous choice. That is, there may be several, possibly interacting, factors that jointly determine the presence and strength of serial choice biases.Crucially, there is an apparent contradiction: Akaishi et al.  found thi et al.  and Braui et al.  found thWe set out to isolate the effects of choice history and evidence history on serial choice bias by examining how different factors modulate choice repetition probability. Participants performed a motion coherence discrimination task, identifying test stimuli as either more or less coherent than a reference stimulus, while also reporting their subjective decision confidence. Stimulus evidence was parametrically varied using six levels of evidence strength. This allowed us to examine the effect of previous decision speed and previous decision confidence, as well as previous stimulus evidence, on choice repetition.We found that choices were biased toward the previous choice, and that this bias was stronger for confident, as well as fast, previous choices. This is in line with previous findings using response times and pupil dilation as proxy measures for confidence . In addihttps://doi.org/10.34973/1wad-3171.All data and code used for stimulus presentation and analysis are available from the Donders Institute for Brain, Cognition and Behavior repository at Thirty-eight naïve participants  recruited through the university pool took part in the experiment. Subjects were paid 8 euros an hour for their participation. All participants reported normal or corrected-to-normal vision and provided written informed consent before the start of the study. The study was approved by the local ethical committee  and was in accordance with the tenets of the Declaration of Helsinki.n = 34 to obtain 80% power for detecting at least a medium effect size (d ≥ 0.5) with a two-sided paired t-test at an alpha level of 0.05. Four participants were excluded from our original sample: one did not complete all sessions, one was excluded after training due to failure to follow task instructions, and two were excluded due to technical errors during the experiment. These participants were replaced with new participants.We performed an a priori power analysis that resulted in requiring Visual stimuli were generated with the Psychophysics Toolbox  for MATL2. A red fixation cross was displayed at the center of the screen at all times. The population of dots was split into signal dots and noise dots. The signal dots moved in the motion direction of the trial with a velocity of 11.5°/s. If signal dots left the aperture, they were redrawn on the opposite side. Three different sequences of dot motion (at the same coherence and direction) were presented in an interleaved fashion, making the effective speed of signal dots 3.83°/s. The noise dots changed position randomly from frame to frame. The percentage of signal dots defined the motion coherence, a measure of motion strength.All stimuli were random dot kinematograms composed of 769 white dots on a black screen, moving within a central circular aperture . The dot density was 1.7 dots per degreeIn each trial of the experiment , two whiParticipants were asked to give two responses in order. First, they indicated whether the test stimulus had lower or higher coherence than the reference (coherence response), and, second, they reported how confident they were about their decision on a scale from 1 to 4 (confidence report). For the coherence response, they used their right hand to press either the “J” or “K” button on the keyboard. The button mapping for indicating lower or higher coherence of the test stimulus was counterbalanced across participants. For the confidence report, participants used their left hand to press the corresponding 1 to 4 digit buttons on the left-hand side of the keyboard. Participants had 4.75 seconds to give both responses, starting from the onset of the test stimulus. If they failed to give both responses in the correct order within the time limit, they received auditory feedback consisting of a low tone, played through headphones during the inter-trial interval. The sequence of coherence differences between the reference and test stimuli was pseudorandomized across trials, such that every coherence difference was preceded equally often by every other coherence difference .Participants completed three sessions—one practice session and two data collection sessions. During the practice session, participants received instructions about the coherence discrimination task and performed one or more simplified practice blocks of 48 trials each, in which they only had to judge the coherence difference without rating their confidence. Next, a staircasing procedure was used to estimate an individual threshold of 70% accuracy in the coherence discrimination task using the QUEST algorithm . ParticiParticipants received auditory feedback about the correctness of their decision during the practice blocks and refresher blocks only. This feedback consisted of a brief high or low tone for correct and incorrect decisions, respectively, played through headphones during the inter-trial interval. Participants always received on-screen written feedback about their general performance  in each block.Trials in which one or both responses were missing and trials where participants gave coherence responses within ≤300 ms from the onset of the test stimulus were removed from further analyses. Consequently, 184 out of 48,960 trials  were discarded.In order to quantify the choice repetition bias and its modulation by previous evidence, response time, and confidence and to qualitatively compare our findings to those of previous studies, we first employed a psychometric function fitting approach. We estimated choice repetition independently for each condition, following the analytical approach of earlier studies .P(tr = 1), as a function of the signed coherence difference between the reference and test stimulus (λ is the probability of stimulus-independent errors (lapses), g is the logistic function, α is perceptual sensitivity, and δ is a bias term. The free parameters λ, α, and δ were estimated by minimizing the negative log-likelihood of the data (using the MATLAB fminsearchbnd function).We first expressed the probability of a higher coherence response, function a (Wichmafunction  of the fts–1) within these bins, we further split the data by previous response time  or previous confidence . For each of those subsets of trials, we fit the psychometric function as described above. In order to compute the choice repetition bias, the resulting bias terms, δ, were transformed from log-odds into probabilities by the inverse logit function P = eδ/(1 + eδ). This probability reflects p(repeat), across bins, we performed repeated-measures analyses of variance (ANOVAs) using SPSS Statistics 23 for Windows .For the quantification of serial choice bias, we first split the data into two bins corresponding to the previous choice such that one bin contained all trials for which the participant previously reported higher coherence, and the other bin contained all trials for which they reported lower coherence. For each level of previous absolute evidence strength  with a binomial link function to predict the current choice based on current and previous stimulus evidence and response variables, as well as their interactions. The factors in this regression model can be conceptually split into current-trial factors and history factors, where the current-trial factors describe the stimulus information  on the current trial, and the history factors describe the stimulus information and response characteristics  of the previous trial.prev choice) as a factor to the model. To examine whether the influence of the previous choice was larger when participants were confident about that choice, we included an interaction factor (prev choice × prev confidence) to the model. Similarly, to examine whether the influence of the previous choice was greater when participants had responded quickly, we added another interaction factor (prev choice × tprev r). Furthermore, as the influence of the previous choice could scale with the strength of absolute evidence for that choice , we included yet another interaction factor (prev choice × prev |evidence|). Note that these three interactions are all theoretically related to decision confidence: More evidence leads to a more confident decision, just as a lower response time and higher reported confidence reflect a more confident decision.We were interested in the influence of the previous choice on current choice. Accordingly, we added the effect of previous choice (prev evidence dir) to the model, as well as all interactions equivalent to those we included for previous choice. This included interactions with previous confidence (prev evidence dir × prev confidence), previous response time (prev evidence dir × tprev r), and previous absolute evidence .It is important to note that, due to the difficulty level being staircased, there was an ∼70% correlation of previous choice and previous evidence direction . This raises the question of whether it is the previous choice or the previous evidence direction that influences the current perceptual decision. To investigate this, we added the previous evidence direction (curr evidence dir × curr |evidence|). Finally, we included the main effects of all variables in the aforementioned interactions . Accordingly, we included prev confidence, tprev r, prev evidence, and curr evidence as factors in the model. Note that these main effects by themselves provide no information about the identity of either the previous or current trial nor information about the previous choice; therefore, they were unlikely to provide information about current choice. Consequently, they were not expected to be significant factors in the model. The reason they were nevertheless added was to prevent an unexpected significant modulation expressing itself as an interaction and hence be misinterpreted.All factors included thus far describe history effects; however, observers’ decisions are primarily based on the bottom-up information present in the current trial. To account for this, we included the signed evidence of the current trial in the model (choice and evidence dir were coded using effect coding (–1/1). Confidence was subject-wise centered and subject-wise scaled by its standard deviations. For the response times, we used a robust z-score and removed the subject-wise median and scaled by the subject-wise median absolute deviation (constant = 1.48). We scaled the unsigned evidence to range between 0 and 3, to accommodate smaller parameter estimates to prevent numerical floating-number overflow.Before constructing the model, variables were recoded as follows. Categorical predictors Z test, which is valid only in the asymptotic regime assuming a multivariate normal sampling distribution of parameters and a proportional sampling distribution of the log likelihood to χ2. Therefore, we were very conservative in our interpretation of the reported p-values when the effects were not obvious from effect sizes alone. An overview of the model output can be found in We used the R lme4 package  to fit aTo check whether the model could adequately capture our data, we plotted and compared fitted marginal against aggregated raw marginal data. Mimicking posterior predictive tests, we simulated new datasets from our model and compared the observed simulated data distributions with the observed one. We simulated new responses with the following procedure: For each trial, we took the probability for a more coherent response for this trial as predicted from the GLMM and simulated a coin toss with that probability  to generate a discrete response . We repeated this procedure to create 1000 simulated datasets and compared the patterns in these datasets to the patterns in the empirical data. We generally found our data to be well captured see .SD = 3.8%). Lapses were infrequent for all participants, as indicated by very high accuracy on trials with the largest coherence difference . Except for two participants with accuracies of 95.3% and 96.3%, respectively, all participants had over 97% correct responses on these trials. As expected, stronger absolute evidence resulted in higher accuracy  M = 0.506, SD = 0.061; one-sample t-test t(33) = 0.58, p = 0.56. One explanation for this could be idiosyncrasies in sequential choice biases. Many studies have found that, although some observers tend to repeat choices, others tend to alternate (p(repeat) is influenced by covariates, such as the previous evidence direction. To investigate the effect of previous choice on current choice while accounting for other variables, we used a history-dependent regression model (GLMM). The GLMM clearly showed that current choices were biased toward the previous choice . Moreover, the single-subject parameter estimates of the GLMM revealed little variability in the effect of the previous choice. For 31 out of 34 participants, the prev choice parameter was estimated to be positive, signifying an attractive bias; that is, observers repeated their previous choice  = 32.709 and p < 0.001, with increased choice repetition for previous fast compared to slow choices. This main effect of response time was confirmed by our history-dependent regression model, indicating that previous response times negatively modulated the impact of the previous choice on the current choice   g. In othF = 2.961, p = 0.014, indicating that the effect of previous response time was not equal across all levels of previous evidence .In addition, our ANOVA revealed a significant interaction between previous response time and previous evidence, ence see b. As we evidence . This suF = 7.918, p < .001, but no main effect of previous confidence F = .444, p = .510   g. In othF = 13.550, p < 0.001   g, contrap(repeat evidence dir), we observed a relationship between the current choice and the direction and strength of the previous evidence  (SD = 3.8% across subjects) of choices corresponded to the evidence direction. Yet, the coefficients have opposing signs. We also found that the repulsion away from the previous evidence direction increased when this evidence was stronger   g. This i< 0.001) g. This r< 0.001) ; however< 0.001) b may in < 0.001) g.Perceptual choices not only are based on current sensory information but are also systematically biased toward the recent history of previous choices. In the current study, we set out to test how the choice repetition bias is modulated by aspects of the choice history, as well as evidence history. Specifically, we investigated the role of decision confidence on the probability to repeat the same choice on successive trials. Confidence deduced from response times and pupil dilation suggests that people are more likely to repeat previous confident choices , in lineWe found that observers were more likely to repeat confident and fast choices. This is in line with the previous findings from indirect measures of decision confidence and confirms the role of decision confidence in positively modulating choice repetition. Furthermore, we found that choice repetition decreased with increasing evidence strength on the previous trial, in line with According to Bayesian theories of perceptual decision-making, prior information is integrated with sensory input in a probabilistically optimal manner . Such thAn open question is what underlying mechanism is modulated by decision confidence. One candidate mechanism would be the process of evidence accumulation, as recent findings show that choice history biases are explained by a history-dependent change in the evidence accumulation . ConfideOur findings add to the literature describing choice history effects of series of forced choices between two alternatives; however, most perceptual decisions are not binary but rather continuous. In continuous estimation tasks, choices are serially dependent, as observers are biased toward previous choices . It has Previous studies of the influence of confidence on choice repetition in forced-choice paradigms have often used proxy measures for confidence, such as pupil dilation, response times, and evidence strength. Notably, a recent study by In this study, we assessed confidence using a subjective report measure and also measured response times, and we found that both modulate choice repetition. An open question that remains is whether subjective confidence and confidence as assessed with response times make independent contributions to choice repetition probability. It should be noted that, in our data, confidence reports and response times were correlated with each other and were both correlated with evidence strength, which modulated the influence of the previous stimulus evidence on the current choice. One may wonder whether this multicollinearity in our data affects the interpretability of our model estimates; however, the reported confidence intervals of the parameter estimates suggest that the influence of these variables is robust, pointing toward the interpretation that all of these variables make independent contributions to choice repetition modulation. Further research must be conducted to investigate this interpretation.difference between a reference stimulus and a test stimulus.At first glance, our finding that observers’ choices are biased away from the previous evidence direction and that this bias grows with evidence strength resembles a sensory adaptation effect frequently described in the literature . HoweverOur history effects cannot be explained by sensory adaptation to motion. The main reason for this is that we changed the motion direction at least 30° from one trial to the next. The varying motion direction should have prevented any patterns of motion adaptation across trials. Sensory adaptation, however, can explain the within-trial effect of a general response bias toward perceiving the test stimulus as less coherent than the reference stimulus a, as witAs our findings resemble but cannot be explained by sensory adaptation, this raises questions regarding from which neural population(s) and at what stage of the decision formation process our adaptation-like modulation arises. We hypothesize that the adaptation to the evidence direction arises not from a population of sensory neurons that encode the motion coherence, but rather from a neural population that encodes the accumulated (difference in) motion coherence. Also, we hypothesize that neural adaptation away from this difference should occur at a stage after this difference is computed from the bottom-up sensory evidence but before this evidence is converted into the final choice. After all, an adaptation to the choice itself would predict choice alternation, whereas we found choice repetition. Follow-up research should investigate these hypotheses about the neural and temporal characteristics of the evidence adaptation we observed.Some previous research has described both attractive choice biases and repulsive stimulus biases in perceptual decision-making. Although we observed strong and consistent choice repetition biases, other studies have observed alternation biases; for example, a primate study by In addition, although we observed a clear choice bias away from the direction of evidence on the previous trial, some studies have reported an attractive bias toward previous stimulus evidence. For example, the aforementioned study by Furthermore, whereas the literature describes idiosyncrasy in serial choice biases, we found little or no idiosyncrasy in the choice history bias. Several studies  report oWe found that perceptual choices were biased toward the previous choice, a modulation that grew with previous decision confidence and previous response times. At the same time, choices were biased away from the direction of previous evidence, a modulation that grew with previous evidence strength. These findings suggest that previous choice and previous stimulus evidence induces separate biases on subsequence choices through distinguishable and complementary mechanisms, pointing toward a complex process of decision formation.


Chemical modifications of viral RNA are an integral part of the viral life cycle and are present in most classes of viruses. To date, more than 170 RNA modifications have been discovered in all types of cellular RNA. Only a few, however, have been found in viral RNA, and the function of most of these has yet to be elucidated. Those few we have discovered and whose functions we understand have a varied effect on each virus. They facilitate RNA export from the nucleus, aid in viral protein synthesis, recruit host enzymes, and even interact with the host immune machinery. Chemical modifications of viral RNA are an integral part of the viral life cycle and are present in most classes of viruses. To date, more than 170 RNA modifications have been discovered in all types of cellular RNA. Only a few, however, have been found in viral RNA, and the function of most of these has yet to be elucidated. Those few we have discovered and whose functions we understand have a varied effect on each virus. They facilitate RNA export from the nucleus, aid in viral protein synthesis, recruit host enzymes, and even interact with the host immune machinery. The most common methods for their study are mass spectrometry and antibody assays linked to next-generation sequencing. However, given that the actual amount of modified RNA can be very small, it is important to pair meticulous scientific methodology with the appropriate detection methods and to interpret the results with a grain of salt. Once discovered, RNA modifications enhance our understanding of viruses and present a potential target in combating them. This review provides a summary of the currently known chemical modifications of viral RNA, the effects they have on viral machinery, and the methods used to detect them. The presence of large RNA modifications, e.g., 2-methylthio-N6-threonylcarbamoyladenosine in tRNA, can even stop these processes , it is clear that viruses pose a major threat and there is still much to discover about their life cycles and molecular mechanisms. Understanding viral RNA modifications and learning to exploit them may lead to the creation of attenuated vaccines or specifically targeted drugs that could give us an edge in dealing with the next viral pandemic when it strikes.6-methyladenosine (m6A) , a novel protein (KIAA1429), a splicing factor (Wilms’ tumor associated protein [WTAP]), and two other as-yet-unidentified subunits  , which hne (m6A) –40. The subunits  The modiein KIAA19, a splisubunits –45. The ubunits –. It has ntiation .6-methyladenosine is recognized by cytoplasmic readers, the YTHDF proteins (YTHDF1 to YTHDF3). In general, these proteins bind to the modified RNA through their C-terminal YTH domain. YTHDF1 facilitates the translation of modified mRNA and YTHDF2 localizes it to RNA decay sites, while YTHDF3 has a synergistic effect on both . An. An6-metnscripts . Yet ano release . On the fe cycle . This ef cytosol  51). Th. Th6-metn by Rev , 51–54. y on m6A . It is a unclear .6A during a flaviviral infection is more unambiguous. Based on current studies, m6A has an inhibitory effect on flaviviruses such as the hepatitis C virus (HCV) and the Zika virus (ZIKV). An increase in the amount of m6A in the viral RNA hinders viral replication and, consistently with this effect, a lowering of m6A leads to an increase in viral production  caused an overall decrease in Gag protein expression, proving that the presence of m5C positively regulates viral replication  is an essential modification created through the deamination of adenosine in a process called RNA editing . This is70–in vitro-prepared RNA containing this modification also elicits an immune response. The ssRNA with this modification induces a stronger inflammatory cytokine response , inosine acts as an innate immune recognition element. An response . It faciin vitro . It has in vitro .Inosine has been shown to play a major role in the life cycle of hepatitis delta virus (HDV). HDV is a negative-strand RNA virusoid that exists in the form of a satellite associated with hepatitis B virus (HBV) . HDV proO-methylations (Nm) (the addition of a methyl group to the 2′-OH of a ribose) of RNA have been a subject of interest since the 1960s, when they were discovered and observed by means of radioactive labeling of RNA  is strongly immunogenic. The cytoplasmic pattern recognition receptor Mda5 is activated through binding to the Cap0 RNA .–97.O-metAnother type of molecule capable of recognizing the Cap0 structure belongs to the IFIT family (interferon-induced proteins with tetratricopeptide repeats) . These mO-methylation is present in internal RNA sites. These methylations are added to the viral RNA by hijacking the cellular methyltransferase FTSJ3. Cells in which the FTSJ3 methyltransferase is knocked down produce HIV-1 RNA with fewer methylations, and the virus induces higher expression of IFN-α and IFN-β (The second type of 2′-nd IFN-β .in vitro and in mouse models that some RNA viruses may be attenuated by creating mutants lacking the Nm modification. This is done by creating recombinant viruses with a specific defect in the S-adenosylmethionine (SAM) binding site of the methyltransferase responsible for 2′-O-methylation. An infection with this recombinant virus elicits strong humoral and cellular immune reactions , often called the fifth nucleotide, is created by the isomerization of uridine. It is present in all RNA and in very high quantities in noncoding RNA . While toduction . The comoduction . As it m1-methyladenosine (m1A) was also detected in all the tested viruses  analysis of viral RNA from ZIKV, dengue virus, HCV, poliovirus, and HIV-1 reported that the genomic RNA of these viruses contains, respectively, 32, 39, 42, 41, and 36 various chemical RNA modifications. Apart from numerous RNA modifications that were never before reported in mammalian systems, N viruses . Shortlytain m1A . This ishat rare .1A, m1G, m5C, or m7G are present in viral RNA. These modifications, however, are present in tRNALys and tRNAPro, which serve as primers for the start of the reverse transcription of HIV-1 or MLV, respectively (6-threonylcarbamoyladenosine (mS2t6A) causes a complete abortion of reverse transcription, and all the cDNA reads from tRNALys have an approximate length of only 36 nucleotides and thus are not included in the library  analysis of the purified genomic viral RNA of two retroviruses, HIV-1  and muriectively . It can ectively , which d library . TherefoBefore a thorough study of the functions of a particular RNA modification, its existence and sequence position must be determined. Known viral RNA modifications and the methods of their detection are summarized in 6A, including m6A-seq (5C (m5C-RIP)  and then amplified. The majority of methods rely on selective antibodies against m m6A-seq ; MeRIP-s m6A-seq ; miCLIP  m6A-seq ; and m5Cm5C-RIP) . The maim5C-RIP) . To overlymerase  or, morelymerase . Other tn of m6A . Another RNA-seq . The dev5C, bisulfite sequencing is also frequently used. It relies on the selective chemical reaction of canonical cytidine and 5-methyl cytidine and is a functional alternative to the aforementioned antibody-based techniques  are sometimes mistaken for m5C. Moreover, the standard RNA bisulfite protocol has been shown to generate false-positive results when working with highly structured RNA  and m5C (Aza-IP  and miCL (Aza-IP ). In genEven though there are currently no antibody-based methods to detect inosine, a comparison of genomic sequences with the corresponding cDNA reveals its position within the RNA molecule. Inosine pairs with cytidine, and the cDNA thus contains a guanosine in its place . HoweverO-methylation, and the modification is fairly unreactive. There are also two types of 2′-O-methylations distinguished by their position within the RNA molecule, where one is a part of the 5′ cap (O-methylation within the cap structure can be detected mainly using UPLC-MS/MS (4) and β-elimination (RiboOxi-seq [There are no antibodies against 2′-e 5′ cap  and the LC-MS/MS . IdentifoOxi-seq  and Nm-soOxi-seq ). It was6A, by comparing the target RNA with a nonmodified (or severely depleted) control RNA, or by employing artificial intelligence (AI)  , 147.Conclusion and outlook. While internal RNA modifications in mRNA or viral genomic RNA and mRNA do exist, they are not as diverse and abundant as many believed in 2012, when the field of epitranscriptomics was established. Nevertheless, the chemical modifications of viral RNA described above obviously play a role in the viral life cycle, in interactions with host innate immunity, and in the distinction between self and nonself RNA. Despite that several attempts have been made to exploit one of these modifications in order to create an attenuated vaccine in several viruses, to the best of our knowledge, no attempts to target the other modifications are currently being made. In comparison with internal modifications, new discoveries of modifications, such as the 5′ diphosphate termini in reoviruses, have shown that there is still much to be learned about the 5′ RNA moieties. The 5′ diphosphate RNA is recognized by RIG-I-like receptors in the cytoplasm and starts an antiviral cascade like the one described for the cap0 structure (7Gpppm6A (tructure . Recentl7Gpppm6A . We have7Gpppm6A . Given t7Gpppm6A , 150. Th7Gpppm6A , 122, AI


Coronaviruses are able to establish persistence. However, how coronaviruses react to persistence and whether the selected viruses have altered their characteristics remain unclear. In this study, we found that the persistent infection of bovine coronavirus (BCoV), which is in the same genus as SARS-COV-2, led to alterations of genome structure, attenuation of gene expression, and the synthesis of subgenomic mRNA (sgmRNA) with a previously unidentified pattern. Subsequent analyses revealed that the altered genome structures were associated with the attenuation of gene expression. In addition, the genome structure at the 5′ terminus and the cellular environment during the persistence were responsible for the sgmRNA synthesis, solving the previously unanswered question regarding the selection of transcription regulatory sequence for synthesis of BCoV sgmRNA 12.7. Although the BCoV variants (BCoV-p95) selected under the persistence replicated efficiently in cells without persistent infection, its pathogenicity was still lower than that of wild-type (wt) BCoV. Furthermore, in comparison with wt BCoV, the variant BCoV-p95 was not able to efficiently adapt to the challenges of alternative environments, suggesting wt BCoV is genetically robust. We anticipate that the findings derived from this fundamental research can contribute to the disease control and treatments against coronavirus infection including SARS-CoV-2. Coronavirinae, family Coronaviridae, order Nidovirales [cis-acting RNA elements associated with coronavirus gene expression. The 5′ two-thirds of the genome encode replicase-related nonstructural proteins (nsps), and the other one-third of the genome mostly encodes structural proteins [betacoronavirus [Coronaviruses (CoVs), which are single-stranded, positive-sense RNA viruses with a genome size of 26–32 kilobases (kb), belong to the subfamily ovirales ,2,3. Theproteins . In addiproteins , are synproteins ,8,9. Manonavirus , containonavirus . Becauseonavirus . HoweverIn addition to acute coronavirus infection, several lines of evidence have shown that coronaviruses including SARS-CoV-2 are able to establish persistence in vitro and in vivo ,16,17,18betacoronavirus) as SARS-COV-1, SARS-CoV-2, and MERS-CoV, was used to explore the effects of persistence on the genome structure and subsequent gene expression, pathogenicity, and adaptation capability. The results derived from the study may enable us to further understand the mechanism of gene expression and coronavirus infection, thus contributing to the disease control and treatments for coronaviruses.Coronaviruses including SARS-CoV-2 are able to establish persistence ,16,17,182.BCoV strain of Mebus (GenBank accession no. U00735), which was obtained from David A. Brian , was plaque-purified ,26 and g7.7 pfu/mL for wt BCoV; however, almost no virus plaque could be detected for BCoV-p95 (101.4 pfu/mL) at VP0. In order to determine whether BCoV-p95 could gradually adapt to the challenge, we performed blind passage until VP10. On the other hand, the collected wt BCoV at VP0 was passaged to fresh HRT-18 cells (VP1) at a MOI of 1 in the presence of poly IC with final concentration of 1 μg/mL. The wt BCoV passage step was repeated until VP10. At each passage of virus, virus, cellular RNA and lysates were collected for the subsequent assays. In addition, for the adaptation experiments of BCoV-p95 and wt BCoV in ML cells, ML cells were respectively infected with the aforementioned viruses at a MOI of 1 for the first time of infection. The titer was 105.2 pfu/mL for wt BCoV and 103.8 pfu/mL for BCoV-p95 at VP0. Therefore, for VP1-VP10 infection, 0.001 MOI was used for both viruses. At VP10, virus, cellular RNA, and lysates were collected for subsequent assays.For the establishment of coronavirus persistence, HRT-18 cells were infected with wild type (wt) BCoV at a multiplicity of infection (MOI) of 1. The surviving cells (<5%) at 3 days postinfection (dpi) were thereafter passaged at every fourth day. The virus and cellular RNA were collected at each passage and the virus collected at 95 days (d) of persistent infection was designated BCoV-p95. For the experiment of BCoV-p95 in fresh HRT-18 cells, HRT-18 cells were infected with wild-type (wt) BCoV or BCoV-p95 at a MOI of 1 for VP0-VP10. For the adaptation experiment of BCoV-p95 in HRT-18 cells treated with polyinosinic:polycytidylic acid (poly IC), HRT-18 cells were first treated with poly IC with final concentration of 1 μg/mL and after 4 h of treatment, HRT-18 cells were infected with wt BCoV or BCoV-p95 at a MOI of 1. The virus was collected at 48 hpi and virus at this stage is defined as virus passage 0 (VP0). The titer was 10cis-acting RNA located in the 5′ UTR were predicted using the Mfold algorithm [To determine the terminal sequence including poly(A) tail length for BCoV genomic RNA, a head-to-tail ligation method was employed as described previously . The healgorithm . To deteNgoMIV and XbaI and cloned into NgoMIV- and XbaI- linearized pDI-Wt to create the aforementioned constructs. Constructs for translation assay were similarly generated but using constructs pDI-Wt with EGFP gene as described previously [NgoMIV and XbaI and cloned into NgoMIV- and XbaI- linearized pSgm-DI-12.7. The overlap PCR was also applied to generate pS-DI-E and S-DI73C-E and the PCR product was digested with NgoMIV and MluI and cloned into NgoMIV- and MluI- linearized pDI-Wt. For in vitro transcription, capped transcripts using MluI-linearized plasmid DNA constructs as templates were prepared with a T7 mMessage mMachine kit  according to the manufacturer’s protocol.An overlap PCR was employed to create defective interfering (DI) RNA mutants derived from wt DI RNA and has been described previously . In brieeviously . The coneviously  and thus2 for 72f h and viral plaques were visualized by haemadsorption with mouse red blood cells. The virus titer was determined by scoring the number of haemadsorption foci.The plaque assay for BCoV was performed in 6-well Costar plates  . Virus w32P and bound to BCoV 3′ UTR. The probed blot was exposed to Kodak XAR-5 film .Ten μg of total cellar RNA was electrophoresed through a formaldehyde-agarose gel. By vacuum blotting, RNA was transferred from the gel to a Nytran membrane, and BCoV RNA was detected with the oligonucleotide, which was 5′-end labeled with The collected cell lysates were separated using 12% sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) gels and electrotransferred onto nitrocellulose membranes . An antibody against BCoV nsp1, N protein, enhanced green fluorescent protein (EGFP) or β-actin was used as the primary antibody followed by goat anti-mouse IgG conjugated to horseradish peroxidase (HRPO) as the secondary antibody . Detected protein(s) was visualized using a Western Lightning™ Chemiluminescence Reagent  and Kodak XAR-5 film .® green amplification mix  and oligonucleotides were used according to the manufacturer’s protocol. In these experiments, dilutions of plasmids containing the same gene as the detected genome, subgenomes, DI RNA, or sgm DI RNA were always run in parallel with the quantitated cDNA for use in standard curves (dilutions ranged from 108 to 10 copies of each plasmid). The amount of synthesized RNA was normalized to the levels of internal controls, including helper virus genomic RNA, 18S rRNA, or input DI RNA where is needed.To measure the synthesis of genome and subgenome, 2 μg of TRIzol-extracted total cellular RNA was used for the RT reaction. For measurement of genome synthesis, oligonucleotides binding to the leader sequence and sequence in the nsp1 gene were used. For measurement of subgenome synthesis, oligonucleotides binding to the leader sequence and sequence downstream of TRS for each subgenome gene were used. For comparison of the replication efficiency between DI RNAs with 5′ terminal sequence alterations, oligonucleotides binding to N gene and reporter gene of DI RNA were employed to differentiate the DI RNA from the helper virus. For comparison of the efficiency of sgubgenomic DI RNA synthesis between the constructs Sgm-DI-12.7 and Sgm-DI-73C-12.7, oligonucleotides binding to the leader sequence and reporter gene downstream of TRS were employed to differentiate the sgm DI RNA from the helper virus as described previously [t test using Prism 6.0 software . The values in the study are presented as the means ± standard deviations (SD) (n = 3); * p < 0.05, ** p < 0.01 and *** p < 0.001.Data were analyzed with Student’s To determine whether the genome structure of BCoV was altered after the establishment of viral persistence, the BCoV RNA genome and subgenomes from HRT-18 cells after 95 days (d) of persistent infection were sequenced and analyzed. In comparison to wild type (wt) BCoV, the sequence alterations of both nucleotides (nt) and amino acids (aa) were identified and are illustrated in 7.34 pfu/mL, 8.35 pfu/mL, To determine whether BCoV replication was altered during persistent infection, a plaque assay was performed to determine the virus titer. The virus collected from HRT-18 cells after 95 d of BCoV infection was designated BCoV-p95. The viral titer of BCoV-p95 was high  F. HoweveTaken together, the results suggest that the alterations of genome structures in cis-acting elements located at 5′ and 3′ termini and leader TRS B–I cause8.4 pfu/mL and 107.7 pfu/mL, respectively) in fresh HRT-18 cells at VP10  cells (13), a mouse cell line established from subcutaneous connective tissue, was used. ML cells were respectively infected with wt BCoV and BCoV-p95, and after 24 h of infection, RNA was extracted, and virus was collected to infect fresh ML cells (VP1). The virus passage step was repeated until VP10, and Northern blot analysis was performed to detect the synthesis of viral RNA. For the adaptation of wt BCoV in ML cells, as shown in Together, the results suggest that BCoV-p95 with altered genome structures cannot adapt to the environment with poly IC-induced innate immunity. In addition, although BCoV-p95 can adapt to new host cells (ML cells), the adaptation capability is lower in comparison with that of wt BCoV in ML cells. The results suggest that BCoV-p95 has altered its characteristics even though it can replicate efficiently in regular HRT-18 cells. Since coronavirus nsp16 can lead to reduced recognition of viral RNA by sensor molecules of cell innate immunity  and S prbetacoronavirus) as SARS-COV-2, as a model to understand how coronavirus responded to the selection pressure of persistence by analyzing the alterations of whole genome structure and subsequent virus fitness. The results may have implications for coronavirus gene expression, pathogenicity, and evolution with medical importance and are discussed below.We in this study employed BCoV, which is in the same genus  with a previously unidentified pattern in persistently infected HRT-18 cells. The altered genome structures are associated with the attenuation of gene expression during persistence. In addition, the genome structure at the 5′ terminus and cellular environment are responsible for the sgmRNA synthesis, solving the previously unanswered question regarding the selection of TRS for synthesis of BCoV sgmRNA 12.7 and thus further extending our knowledge of the coronavirus transcription mechanism. Although the resultant BCoV (BVoC-p95) still replicates with high efficiency in regular host HRT-18 cells, it still displays reduced gene expression and pathogenicity in comparison with those of wt BCoV. In addition, when compared with wt BCoV, the BCoV-p95 cannot rapidly adapt to the environment with innate immune and to other host cells with different tissue origins, suggesting that the selected BCoV-p95 has altered its characteristics. Although different selection pressures may lead to different outcomes, these previously unidentified features may provide important information contributing to disease control and clinical treatments against coronavirus infection including SARS-CoV-2.


Drosophila ventral nerve cord (VNC) is composed of thousands of neurons born from a set of individually identifiable stem cells. The VNC harbors neuronal circuits required to execute key behaviors, such as flying and walking. Leveraging the lineage-based functional organization of the VNC, we investigated the developmental and molecular basis of behavior by focusing on lineage-specific functions of the homeodomain transcription factor, Unc-4. We found that Unc-4 functions in lineage 11A to promote cholinergic neurotransmitter identity and suppress the GABA fate. In lineage 7B, Unc-4 promotes proper neuronal projections to the leg neuropil and a specific flight-related take-off behavior. We also uncovered that Unc-4 acts peripherally to promote proprioceptive sensory organ development and the execution of specific leg-related behaviors. Through time-dependent conditional knock-out of Unc-4, we found that its function is required during development, but not in the adult, to regulate the above events.The  How does a complex nervous system arise during development? Millions to billions of neurons, each one essentially unique, precisely interconnect to create a functional central nervous system (CNS) that drives animal behavior . Work ovDrosophila ventral nerve cord (VNC), like the vertebrate spinal cord, also manifests a lineage-based organization. The cellular complexity of the VNC arises from a set of segmentally repeated set of 30 paired and one unpaired neural stem cells (Neuroblasts [NBs]), which arise at stereotypic locations during early development , the neurons of the sibling hemilineage undergo cell death  sites in the same orientation flanking the 2nd and 3rdunc-4 exons as well as an attP site immediately 5’ to the second exon. We used this parental unc-4FRT stock to generate all mutant lines and the GAL4/split GAL4 reporter lines. To generate the unc-4null mutant line, we used Flippase (FLP) to excise the 2nd and 3rd exons of unc-4 in the germline, generating an unc-4 allele that lacks the homeodomain . When crossed to appropriate transgenes, each of these alleles faithfully recapitulated Unc-4 expression in the VNC and brain in the larval and adult CNS . Leveraging these transgenes, we tracked Unc-4 expression in the peripheral nervous system (PNS) and found that Unc-4 is expressed in all progenitors of leg chordotonal neurons  and head sense organs in the larvae as well as many adult sensory neurons including chordotonal and bristle sensory neurons in the leg and Johnston’s organ and olfactory neurons in the antenna  exhibited semi-lethality in the hemizygous or homozygous state, with many pharate adults failing to eclose from the pupal case. Escaper unc-4 null flies emerged as adults with a frequency of 13% of the expected Mendelian rate. Adult unc-4 null mutant males were fertile, but females were infertile. Examination of unc-4 females revealed that they were impaired in egg laying and their ovaries were dramatically enlarged due to egg retention (not shown), a phenotype that may arise due to defective functioning of sensory neurons in the female reproductive tract, some of which express Unc-4  due to falling or being extremely slow . Unc-4, therefore, functions during development to regulate this suite of specific behaviors.Unc-4 is expressed in both the developing and adult nervous system. To determine if T system  to removFunc4RT line to remove Unc-4 function in both the CNS and PNS or just the CNS. We used sca-GAL4 to remove Unc-4 function in both the CNS and PNS . To assess walking, we challenged flies to walk horizontally in small-diameter tubes. Control animals walked in a coordinated manner without falling, but unc-4 null mutants and ato-GAL4 F>unc4 RT flies were slow and fell often . Unc-4, therefore, appears to regulate the patterning and dendritic projections of chordotonal neurons in the leg, with this function likely underlying the observed defects in three-leg rubbing, walking, and climbing.To ascertain whether Unc-4 function during chordotonal organ development may underlie the observed behavioral defects, we assessed Unc-4 function on adult femoral chordotonal organ (feCO) neurons, the major chordotonal organ in the leg. We visualized them in control and he adult . In conthe adult . In the he adult  and theihe adult . Of noteunc-4DBD line with the ubiquitous tubAD line to visualize all Unc-4+ neurons in control and unc-4 mutant animals. As shown in + neurons in the absence of Unc-4 function, indicating Unc-4 is not required for its own expression nor is it required for the survival of these neurons.The central expression of Unc-4 is striking because that seven hemilineages that express it are all cholinergic . To deteunc-4 mutant background by intersecting unc-4 split GAL4 lines with neurotransmitter specific split-GAL4 lines expressed in cholinergic, glutamatergic, or GABAergic neurons  express Unc-4 in the VNC  in the control VNC were marked with the split-GAL4 combination of unc-4AD-ChATDBD, confirming the cholinergic identity of the Unc-4+ hemilineages. In the unc-4 mutant VNC, the expression of this split-GAL4 combination appeared grossly normal and marked all seven Unc-4+ postembryonic hemilineages, indicating that Unc-4 function is not necessary for the cholinergic fate of most  neurons in these hemilineages.We then determined the neurotransmitter profile of these neurons in control and  neurons . We prev the VNC . To conf ChATDBD . As expeVGlutDBD, which labels glutamatergic neurons, with unc-4AD. Here, unc-4AD-VGlutDBD driven GFP expression identified several glutamatergic Unc-4+ motor neurons in thoracic and abdominal segments in addition to a few occasional interneurons in the thoracic segments . Unc-4, thus, is expressed in embryonic-born remodeled adult motor neurons and functions to promote their growth.The relationship of Unc-4 expression to the glutamatergic phenotype was determined by combining segments . Based osegments . Most ofsegments . Compari lineage . In the unc-4DBD with gad1AD, a line that is expressed in all GABAergic neurons, to assess whether Unc-4 regulates GABA fate. In control animals, we failed to detect any GABAergic Unc-4+ neurons in the VNC  th neurons , (iii) t neurons , and . Thus, most of these 11A neurons switch from a cholinergic to a GABAergic fate. Moreover, most of these converted neurons show GABA production as well as the gad1 mRNA  together with NB intersected reporter immortalization technique  in NB3-2 . PCR amplified DNA blocks were cloned into pHD-DsRed-attP vector via Aarl and SapI enyzme sides sequentially as previously described (Our donor construct contained three major elements: (i) the left and (ii) right homology arms, which are immediately adjacent to Cas9 cutting sites, and between them, (iii) the replacement arm which contained two FRTsites, an attp site, 3xP3-dsRED mini gene and the intervening unc-4 sequence to keep escribed .Primes used to generate the block 1, which contained the left homology arm (~1.6 kb) and the FRT sequence (underlined).AGCCACACCTGCGAATTCGCTTCCAGTTGTCGGGCACTCCAAAT.Forward primer (with Aarl site): GAAGTTCCTATACTTTCTAGAGAATAGGAACTTCGAAAATTACCCAAAAATGGAAAACGCCCAACACCTGCAAACCTAC. The amplified DNA was inserted to the pHD-DsRed-attP vector via Aarl enzyme site.Reverse primer (with Aarl and FRT sites):nd and 3rdunc-4 exons and some intronic sequence. Forward primer (with SapI and XbaI sites): TTTCTCTAGATGGGGCTCTTCCTATGTCCCATGTGTGTGGAGTTCGGT. Reverse primer (with BamH1 site): ATTCGGGATCCAGTTGAGACTTTGGTATAGCTTTTAAATTGC. Primes used to generate the block 2B, which contained the right homology arm (~1.6 kb) and the FRT sequence (underlined). Forward primer (with BamH1): GAAGTTCCTATTCTCTAGAAAGTATAGGAACTTCCCCATCGAATATCTGATTATTAACACGGTGGGATCC. Reverse primer (with SapI and HindIII sites): TTCACAAAGCTTCACACTGCTCTTCAGACTGTCCTTAGTCAATAGACTTCTATTAC.Two PCR products (blocks 2A and 2B) were ligated to generate Block 2. Primes used to generate the block 2A, which contained 2Block2A and Block2B were conjugated via BamH1site and inserted into a pUC19 vector via HindIII and XbaI sites in the same ligation reaction. Block 2 was recovered with SapI digestion and inserted into Sap1 site of the previously built construct, Block 1 in pHD-DsRed-attP.https://www.rainbowgene.com).The content of the donor and guide RNA vectors was verified by Sanger sequencing. A mixture of these vectors was injected into vas-Cas9 flies VK00027) by Rainbow transgenics -T2A-Gal4-Hsp70, pBS-KS-attB2-SA(1)-T2A-Gal4DBD-Hsp70, pBS-KS-attB2-SA(1)-T2A-p65AD-Hsp70 vectors were microinjected into Unc-4nullunc-4 line. To do that, we crossed FRTunc-4 line with hsFLP1 flies, and resultant larval progeny were heat shocked at 37°C for an hour. Adult female progeny was later crossed individually to FM7c males to isolate and generate nullunc-4 lines.Second and third unc-4 exons were removed in the germline to generate unc-4 locus over FM7 balancers showed a low rate of recombination/chromosomal rearrangement. When unc-4 mutant animals over FM7 balancer were outcrossed to males carrying a wild type X chromosome, we observed occasional non FM7 male flies, which were not unc-4 mutants. These flies lacked 3XP3-dsRED expression, which marks edited unc-4 locus and behaved like wild-type. Wild type unc-4 locus in the FM7 chromosome is located close to the Bar locus which is known to exhibit rare chromosomal arrangements  and fixed with 2% paraformaldehyde in PBS for an hour at room temperature and then washed several times in PBS-TX (PBS with 1% Triton-X100) for a total 20 min. Tissues were incubated with primary antibodies (Key Resources Table) for two to four hours at room temperature or overnight 4°C. After three to four rinses with PBS-TX to remove the primary antisera, tissues were washed with PBS-TX for an hour. After wash, tissues secondary antibodies were applied for two hours at room temperature or overnight at 4°C. Tissues were washed again with PBS-TX for an hour and mounted in Vectashield or in DPX after dehydration through an ethanol series and clearing in xylene .Hybridization chain reaction-based RNA in situ hybridization was performed with commercially purchased probes as described before .unc-4 mutant background were generated by crossing NB specific GAL4 lines to the following lines respectively:  and .NB intersected reporter immortalization clones  in contrey-AD;dbxDBD], , , and [UAS-FLP.D].Reporter immortalization clones without NB intersection  line with R57C10Flp2::PEST; ; HA_V5_FLAG_OLLAS/MCFO-7 (Multi-Color Flipout (MCFO) clones were stochastically generated from the progeny of the cross of SS20852-GAL4 . Flies were used 2–10 days post-eclosion. Flies with damaged legs and wings were excluded from the tests. Animal behaviors were recorded with a USB or iPad Pro camera except for stimuli induced take-off behaviors for which we used high speed cameras. Please see Flies were individually observed under the microscope for three leg-rubbing behavior that involves either pairs of front or hind leg and one mid leg. Three episodes were quantified for each fly; success or failure was called based on the majority. If two initial episodes result in failure or success, flies were not tested for the third episode.Flies were put individually into a 5 ml serological pipette with a 5 mm diameter and the pipette was banged and hold vertically to induce climbing. The event on which a fly climbed 14 cm in 1 min or under was called a success and the climbing time was documented. Events with the climbing time over 1 min was considered as a failure.Flies were put individually into sleep assay vials with a 4 mm dimeter and ends of the horizontally placedvials were plugged with cottons to give approximately 6 cm length for flies to walk. The locomotion of the flies was recorded with a USB camera. Walking speed were measured from the recorded locomotion tracts that were continuous i.e., not interrupted by fall or grooming via wrMTrck pluggin on ImageJ .: http://imagej.nih.gov/ij/ and wrMTrck: http://www.phage.dk/plugins/wrmtrck.html.ImageJFlies individually were put on top of a large white surface (top of a chest freezer) and observed with naked eyes whether they take-off to fly away. The flies that were able to fly away was scored as successful.FRTunc-4 flies; 0 and 16 flies showed take-off interruption, respectively. The looming stimulus was represented to 47 control and 60 NB3−2 > FRTunc-4 flies; 0 and 24 flies showed take-off interruption, respectively. Quantification in Two kinds of visual stimuli were used to induce jumping in flies as described earlier : (i) theInsect pins were glued to the thorax dorsally and brief air puffs were blown to the flies to induce wing flapping. Flies that showed high frequency wing flapping were considered successful. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:This study by Lacin and colleagues is a fine example of leveraging genetic reagents to incisively study the role of a gene  in the development and function of neuronal lineages. The work is robust and beautifully illustrated, focused on two hemi-lineages. There is lots to like about this study, particularly the clear logic and rigorous application of genetic techniques designed to squeeze out as much specificity as possible. The authors provided a clear, and perhaps technically the, as yet, most rigorously demonstrated example. This is not a new concept, so the question is around novelty. Yet, this type of work needs to be done and appreciated. Its rigour is impressive and it makes it clear that to understand how combinations of transcription factors regulate cellular properties, which then combine to shape specific behavioural outputs, remains a complex and challenging task.Decision letter after peer review:Drosophila CNS" for consideration by eLife. Your revised article has been evaluated by K VijayRaghavan as the Senior Editor, a Reviewing Editor, and two reviewers.Thank you for submitting your work entitled "Unc-4 acts to promote neuronal identity and development of the take-off circuit in the A consolidated review is attached. The authors will see that they need to do next to nothing before acceptance, except read the words of praise and highlight better a significant finding and deal with the minor comments.Summary and consolidated reviews:Drosophila to characterize the expression and function of the conserved Unc-4 transcription factor during the development of the adult CNS. They show that Unc-4 is expressed in about half of the hemilineages that generate the adult ventral nerve cord. They use hemilineage specific Gal4 lines to determine the lineage-specific function of Unc-4, finding lineage-specific LOF phenotypes in two hemilineages. In the 11A hemilineage Unc-4 is required for promoting cholinergic identity and suppressing GABA identity, although Unc-4 is not capable of repressing GABA identity when ectopically expressed in other hemilineages. Thus, this is a lineage-specific phenotype. Similarly, Unc-4 LOF in hemilineage 7B results in failure to innervate T2 leg neuropil and a highly specific flight take-off defect (no jump).This report uses the powerful genetic tools of Overall, the experiments are beautifully documented; the text is clearly written, and the conclusions are well supported. The positives of this paper are the importance of characterizing a highly conserved transcription factor, the quality of the experiments and conclusions, and the identification of an entry point for subsequent characterization of an adult flight "jump" neural circuit. The only negative, perhaps, is the lack of a single coherent story – which is the direct consequence of having lineage-specific phenotypes, and thus hard to avoid.There is lots to like about this study, particularly the clear logic and rigorous application of genetic techniques designed to squeeze out as much specificity as possible. The results are clear: that in different hemilineages Unc-4 regulates different aspects of development, cell specification, and function. While here the authors provided a clear, and perhaps technically the as yet most rigorously demonstrated example, this is not a new concept. So the question is around novelty. Regardless, it is important that this type of work is done. Its rigour is impressive and it makes it clear that to understand how combinations of transcription factors regulate cellular properties, which then combine to shape specific behavioural outputs, remains a complex and challenging task. Here, the discussion is helpful in highlighting the importance to consider the evolutionary timeline of anatomical-developmental features, such as the conserved ground-plan of neuroblasts relative to genes such as Unc-4 having been harness in the diversification of hemilineages.In summary, we see that the methodological and scientific rigour of this work allow the authors to interpret the data with clarity and decisiveness that would otherwise not be possible:a) on distinguishing that only some hemilineages have a clear  requirement for Unc-4;b) that for most that do require Unc-4 this is developmental rather than later/post-mitotic . So this paper would be directly relevant to that big picture issue and this could be highlighted in copyediting with a well-crafted sentence);c) that Unc-4 is required for very different aspects in different lineage contexts;Together, demonstrated with such clarity, these observations help us think about how transcription factors shape nervous system development and function.Reviewer #1 Minor Comments:- The finding that removal of Unc-4 in post-mitotic neurons has no phenotype is very interesting; I would consider adding that finding to the Abstract and Discussion.larval hemilineages or both embryonic and larval hemilineages in the Introduction and Results. For example, does the term "individual hemilineages" refer to both embryonic and post-embryonic hemilineages? For example, the last paragraph of the Introduction mentions hemilineages multiple times without distinguishing embryonic and post-embryonic hemilineages.– I think it is important to say whether you are mentioning + motor neurons in the larva  so it would be nice to add this information for the adult neurons.– Is it known whether the 7B neurons that project to the leg neuropil are direct premotor neurons? One of this lineage (A07f2) is directly premotor to Eve+ hemilineages contain only Unc-4+ neurons, or also contain some Unc-4- neurons; please clarify.– It is not clear from the text whether the Unc-4+ or if some are Unc-4-; please clarify.– It is also not clear whether all cholinergic neurons are Unc-4+. To my knowledge, the only lineages that are Eve+ are 1-1, 3-3, 4-2, and 7-1.– Subsection “Unc-4 and neurotransmitter expression”, please add a citation for the statement that lin7 (NB3-2) neurons are Eve– Sometimes the Unc-4 gene is italicized and sometimes not, please be consistent.– Could add Skeath 1998 to the reference in the second paragraph of the Introduction.– The first paragraph of the subsection “Unc-4 function is required for proper neuronal projections in 7B neurons” says "see Materials and methods" but I can't find the data in the Materials and methods.– The first paragraph of the subsection “Unc-4 function is required for proper neuronal projections in 7B neurons” has a broken reference that needs correction.– I would appreciate a thin dashed line around the leg neuropil in the relevant figures.Reviewer #2 Minor Comments:I have only very minor points to raise:Correct "axion projections"Figure 2 – legend: there is some confusion with referring to panels E and F and then G and H.Figure 7: panels C and D to replace "o" with a proper zero. Reviewer #1 Minor Comments:– The finding that removal of Unc-4 in post-mitotic neurons has no phenotype is very interesting; I would consider adding that finding to the Abstract and Discussion.We thank for the reviewer for this suggestion. As suggested, we edited the Abstract and Discussion to reflect this point as shown below.Part of the edited Abstract:“Through time-dependent conditional knock-out of Unc-4, we found that its function is required during development, but not in the adult, to regulate the above events.”Part of the edited Discussion:+ lineages throughout adult life, suggesting that Unc-4 function is dispensable in mature neurons after eclosion under standard lab conditions. Future work will be required to ascertain whether Unc-4 functions during adult life or in more than two of its expressing hemilineages during development. Nonetheless, our work shows that Unc-4 executes distinct functions in the 7B and 11A lineages.”“Similarly, pan-neuronal deletion of Unc-4 specifically in the adult did not lead to any apparent behavioral defect even though Unc-4 expression is maintained in all Unc-4– I think it is important to say whether you are mentioning larval hemilineages or both embryonic and larval hemilineages in the Introduction and Results. For example, does the term "individual hemilineages" refer to both embryonic and post-embryonic hemilineages? For example, the last paragraph of the Introduction mentions hemilineages multiple times without distinguishing embryonic and post-embryonic hemilineages.We appreciate this point and have added the following sentence to address it and clarify that our study is based entirely on postembryonic hemilineages.Edit to the Introduction:“In this paper, we focus only on postembryonic hemilineages, which from this point on in the paper we refer to as hemilineages for simplicity.”+ motor neurons in the larva  so it would be nice to add this information for the adult neurons.– Is it known whether the 7B neurons that project to the leg neuropil are direct premotor neurons? One of this lineage (A07f2) is directly premotor to EveLife paper. It is possible that larval motif is retained in the adult CNS. Unfortunately, we do not have any data for or against a premotor function of 7B neurons in the adult. Future work will investigate whether 7B neurons synapses with jump related motor neurons such as TTMn and TLMn.We are aware of the recently published Zarin et al., 2019, e+ hemilineages contain only Unc-4+ neurons, or also contain some Unc-4- neurons; please clarify.– It is not clear from the text whether the Unc-4We clarified this ambiguity by editing the Introduction as shown below:“Unc-4 expression in these hemilineages is restricted to postmitotic neurons and it appears to mark uniformly all neurons within a hemilineage during larval and adult life .”+ or if some are Unc-4-; please clarify.– It is also not clear whether all cholinergic neurons are Unc-4We edited the related Result section to indicate that Unc-4 marks half the cholinergic lineages as shown below:+ postembryonic hemilineages are cholinergic and that half of all cholinergic hemilineages (7 of 14) express Unc-4 in the VNC .”“We previously showed that all of the Unc-4+. To my knowledge, the only lineages that are Eve+ are 1-1, 3-3, 4-2, and 7-1.– Subsection “Unc-4 and neurotransmitter expression”, please add a citation for the statement that lin7 (NB3-2) neurons are EveWe believe the reviewer meant 11B neurons from NB7-2. We added the references  that demonstrated Eve expression in postmitotic 11B neurons.– Sometimes the Unc-4 gene is italicized and sometimes not, please be consistent.unc-4 throughout the text.We now italicized – Could add Skeath 1998 to the reference in the second paragraph of the Introduction.We added the indicated reference.– The first paragraph of the subsection “Unc-4 function is required for proper neuronal projections in 7B neurons” says "see Materials and methods" but I can't find the data in the Materials and methods.We thank to the reviewer for indicating this. We now created a subsection in the Materials and methods with a title “Lineage-specific GAL lines” to make it easier for the reader to identify these reagents.– The first paragraph of the subsection “Unc-4 function is required for proper neuronal projections in 7B neurons” has a broken reference that needs correction.We corrected it.– I would appreciate a thin dashed line around the leg neuropil in the relevant figures.Demarcating the leg neuropils is a helpful suggestion. We outlined the leg neuropils in Figure 6 as suggested.Reviewer #2 Minor Comments:I have only very minor points to raise:Correct "axion projections"Figure 2 legend: there is some confusion with referring to panels E and F and then G and H.Figure 7: panels C and D to replace "o" with a proper zero.We thank for the reviewer for catching these typos and errors. We have corrected all of them.


The point mutation in unc-108(csn2) is identical to that in the previously characterized loss-of-function allele unc-108(n3263), substituting a glutamine in place of a glycine that is conserved among Ras superfamily members . Similar to other unc-108(lf) mutants, csn2 animals move slowly (not shown). Here we show that unc-108(csn2) as well as previously characterized unc-108 alleles are SIS-defective . While the majority of wild-type N2 animals cease head movement, locomotion and pharyngeal pumping following exposure to damaging conditions, unc-108(lf) animals retain all of these activities. This coordinated impairment of sleep-associated behaviors argues against a role for UNC-108 downstream of the SIS-promoting ALA neuron, which acts via the collective action of neuropeptides with overlapping but distinct effects on the sub-behaviors of sleep .In a genetic screen for mutants defective in stress-induced sleep (SIS) we isolated unc-108(csn2) animals are resistant to EGF-induced sleep (Panel C), indicating that UNC-108 functions downstream of EGF signaling within the SIS pathway. Together these results suggest that UNC-108 functions within ALA.SIS is dependent on Epidermal Growth Factor Receptor (EGFR) activation within ALA, and sleep can be triggered not only by noxious conditions but also by forced overexpression of LIN-3/EGF . We found that C. elegans nervous system and is implicated in the recycling of receptors through the endocytic pathway  as well as in dense core vesicle (DCV) maturation . We speculate that the UNC-108 SIS defect arises from deficits in EGFR trafficking or in the maturation of DCVs within the ALA neuron.UNC-108 is widely expressed within the unc-108(n777), ZH382 unc-108(n3263), PS5970 syIs197[hs::LIN-3c(cDNA) + myo-2p::DsRed + pha-1(+)];him-5. Strains available upon request: CVB30 unc-108(csn2), CVB31syIs197;unc-108(csn2).Strains available from the CGC: N2 Bristol, MT1656