RNA is a functionallyrich molecule with multilevel, hierarchicalstructures whose role in the adsorption to molecular substrates isonly beginning to be elucidated. Here, we introduce a multiscale simulationapproach that combines a tractable coarse-grained RNA structural modelwith an interaction potential of a structureless flat adsorbing substrate.Within this approach, we study the specific role of stem-hairpin andmultibranch RNA secondary structure motifs on its adsorption phenomenology.Our findings identify a dual regime of adsorption for short RNA fragmentswith and without the secondary structure and underline the adsorptionefficiency in both cases as a function of the surface interactionstrength. The observed behavior results from an interplay betweenthe number of contacts formed at the surface and the conformationalentropy of the RNA molecule. The adsorption phenomenology of RNA seemsto persist also for much longer RNAs as qualitatively observed bycomparing the trends of our simulations with a theoretical approachbased on an ideal semiflexible polymer chain. An importantmode of these interactions is related to RNA adsorption to proteinaceoussubstrates, such as the capsid shells of viruses, where the RNA–capsidinteractions are important for the efficiency of virion assembly andnanoparticle stability.19 In this context, the fundamentalquestion is whether the self-assembled RNA conformation is modifiedas a result of the adsorption or, equivalently, whether differentRNA structural motifs modify its adsorption phenomenology.In the past decades,the ability of ribonucleic acid (RNA) to influencebiological processes occurring inside living cells23 molecular simulations have offeredimportant insights into the adsorption of semiflexible macromoleculesto a molecular substrate,24 while the adsorptionof macromolecules with either the annealed or quenched internal structureonto a molecular substrate remains much less understood. The latterproblem is particularly relevant in the context of RNA-virus and RNA-nanoparticleassembly phenomena,32 where the soft, malleable RNA structure can respond to the adsorptionprocess. The shortage of theoretical conceptualization and predictionmakes it difficult to convert the observed RNA adsorption phenomenologyinto a robust parametrization of the underlying adsorption interactionpotential and consequently modify and/or control the RNA–substrateinteractions. Such insight into the adsorption characteristics wouldbe especially valuable for the optimization and control of RNA assemblyinto carrier vesicles or virus-like nanoparticles for efficient RNA-cargodelivery,36 which could potentially speed up high-throughput RNA nanocarrierfabrication for applications in nanomedicine.Froma fundamental polymer theory point of view,38 induced byspecific internucleotide interactions, and their modification as aresult of the adsorption process, induced by less specific interactionswith the adsorbing substrate, is a challenge whose general aspectswe aim to address in this work. We performed an extensive study ofRNA–substrate interaction using a tractable multiscale41 model to understand the adsorption mechanisms of RNA in proximityto a flat, featureless model of an adsorbing substrate. To elucidatethe role of the secondary structure on the adsorption mechanisms ofRNA, we performed coarse-grained molecular simulations of RNA fragmentsextracted from the satellite tobacco mosaic virus (STMV) genome.42 One particular question we address is the roleof different soft RNA secondary structure motifs in the adsorptionphenomenology and the connection between the inherent RNA structureand the structure imposed by the adsorption itself. To this end, wecompare the adsorption phenomenology of RNA fragments in two distinctconfigurations, with and without a secondary structure. The modelinteraction potential between the adsorbing substrate and the proximalstructured or unstructured RNA molecule is allowed to vary in a noninvasivemanner so that the original secondary structures, if they exist, remainfixed.The lack of asolid understanding of the connection between self-assembledstructures of biopolymers such as RNA,We identify a transition between two interaction regimesfor structuredand unstructured RNA as the attractive substrate strength is varied.For structured RNA (with secondary structure), base-paired regionsare preferentially adsorbed at lower surface interaction strengthswhen compared to the unstructured RNA. For unstructured RNA (withoutsecondarystructure), the opposite is true, and they are preferentially adsorbedat larger adsorption strengths compared to structured RNA. While itis difficult to scale up our simulations to significantly longer RNAsequences, we do simulate the adsorption behavior for different RNAsizes and compare their adsorption behavior to the ground-state behaviorof ideal polymer chains with the same adsorption potential. Finally,we discuss the possible role that the different adsorption regimescould play in the nanomedicine applications that can be complementedwith our simulations.44 It is important to remark thatthe three fragments of this work represent archetypal structures ofthe entire STMV genome, as previously obtained by chemical probingmethods.42 Our coarse-grained model generatesa 3D representation of the three RNA fragments and supports secondarystructure restraints based on the primary sequence and interactionsdeconvolved from an X-ray structure database  and unstructured (“noss”—nosecondary structure) versions of the first two fragments, S1 and S2,while the third fragment complements the set by introducing a multibranchsecondary structure , and λD = 1 nm, considering RNA under typicalphysiological conditions as described in refs ,which have been extensively sampled in our simulations. Hence, theinfluence of the Debye–Hückel-like interaction potentialmay affect only the substrate, which is in our case featureless, asdescribed before.We aim to investigatethe general role of the RNA secondary structure in adsorption processes.For this purpose, we model the substrate as a flat, featureless surface.Excluding topographical and molecular features of the substrate, whichcould possibly intervene in the interpretation of the results, allowsus to isolate the influence of the RNA secondary structure in itsadsorption. We model the attraction of the RNA phosphate groups tothe adsorbing substrate by a Debye–Hückel-like interactionpotential, which can be rationalized as stemming from the electrostaticinteractions between the dissociated RNA phosphates and the substratecharges. in refs , 47. The48 The latter Lennard-Jones-based potential canbe rationalized as stemming only from the van der Waals interactions.The results are reported in the Supporting Information.For comparison, we also considered a scenarioin which the RNA interacts with the substrate via the Mie 9-3 potential.Supporting Information). dCM.Temperature and structural restraints of the system are chosenin such a way that they do not destroy the secondary structure imposed,corresponding to a scenario below the melting temperature  as a function of the surface attraction strengthεsurf, for both structured and unstructured RNA fragments.Two regimes are immediately identifiable: the first for εsurf < 0.89 kBT, where the fragment with the secondary structure adsorbs more stronglythan the unstructured one (regime I), while for εsurf > 0.89 kBT, theunstructuredfragment is the one exhibiting a stronger adsorption free energy (regimeII).Figures S1 and S2 in theSupporting Information). This suggests that the existence of the twoadsorption regimes is not specific to the Debye–Hückelpotential but may be considered a more general phenomenon, commonto other substrate architectures as well. In addition, because ofthe generalizable character of the model, further comparison of fragmentswith and without the secondary structure shall remain qualitativelyunchanged also for models with higher resolution representation ofthe RNA molecules and the substrate.An interesting question is howgeneral is the existence of thetwo adsorption regimes. To provide a rough answer, we performed simulationsusing a different type of attractive potential, namely, a Lennard-Jones-basedpotential for a planar wall . The outcomes of thismuch shorter-ranged potential are qualitatively the same as for theelectrostatically driven, longer-ranged Debye–Hückelpotential  = min{0, Usurf(z)}, εmin is the minimum of the surface potential,and ρ(z) is the monomer distribution for boundconformations normalized as ∫0∞ρ(z) dz = 1 . 23We quantify the numberof contacts of RNA with the surface basedon the normalized energy of the RNA–substrate interactionsurf = 0.6 kBT, which is below the point where the adsorption free energies Fm coincide . In Rg⊥2⟩)and parallel (⟨Rg∥2⟩) contributions to the radiusof gyration of fragment S1 in contact with the surface is shown todecrease monotonically as the substrate attraction gets stronger.A slower decrease in ⟨Rg⊥2⟩/⟨Rg∥2⟩ is observed in the structurally constrained fragmentgiven its flexible loop, while for unstructured RNA, the values fallwell below 0.32, in agreement with theoretical predictions for semiflexiblepolymer chains.23 Representative snapshotsof fragment S1 are shown as a side view in xy plane for the unstructured fragment and a reorganizationof structural constrains for the structured fragment. The flatteningof the unstructured RNA fragments reflects also in the decrease ofthe ratio between the normal and parallel radii of gyration with increasingsurface attraction strength .We obtain further insight into the structural configurations ofthe RNA molecules by looking at the parallel and perpendicular contributionsto the radius of gyration , illustrated in surf forwhich the interaction of the unstructured fragment S2-noss becomesmore favorable than the structured S2-wiss is shifted toward largervalues (εsurf/kBT ≈ 0.97) when compared to the smaller fragment S1.Such a shift is consistent with a point of balance between more rigid(base-paired) and more flexible (loops) regions, where, for longerunstructured molecules, a higher conformational barrier is present.The value of the transition point between the two regimes dependson the shape of the secondary structure of RNA, as seen for fragmentsS1 and S2. Moreover, the differences in adsorption free energies betweenstructured and unstructured RNAs in regime I grow with the fragmentsize , 60% (S2), and 61% (S3), and we can thus concludesuch an overlap only for this particular base-pair fraction.Thelast fragment with the secondary structure addressed in this workis a multibranch fragment (S3-wiss), which is comprised of two hairpinsjoined together by a single unpaired nucleotide hinge see 1. The nokBT for lowvalues of εmin, the adsorption properties, shownhere for smaller and larger fragments, indicate that such a differencegrows with the fragment size. This difference is therefore expectedto become large for very long RNA fragments, for instance, in thecase of the whole genome of a virus.min, the behavior of fragmentswith the secondary structure resembles a straight line with a slopeapproximately given by εmin/2  is ΔFm ≈ 1.0 kBT, and for the longer bulged-hairpin (fragment S2)it is ΔFm ≈ 1.5 kBT.Our results,based on the comparison between bulged-hairpin andmultibranch RNA fragments, show that the total fraction of base pairsin the secondary structure determines the adsorption behavior in regimeI rather than the exact topology of the RNA motifs and the additionalfreedom given by relative positions and orientations of the stems,at least when it comes to adsorption onto flat substrates. As forthe difference of adsorption energies between structured and unstructuredRNA fragments with the same sequence under regime I, it increaseswith the number of contacts. For instance, for a weak surface interactionwith adsorption strength εFm increases monotonically with the number of contacts(after the conformation barrier is overcome) and depends instead onthe number of contacts formed with the substrate .For stronger attractions in regime II, ΔWe studied the roleof the RNA secondary structure in its adsorptionto planar substrates. We use a simple and general coarse-grained RNAmodel interacting with the surface via a Debye–Hückelpotential, which captures the basic electrostatic part of the dominantinteraction in the adsorption processes on charged surfaces. Our investigationhighlights the existence of two adsorption regimes concerning theRNA structure and the substrate attraction. In the first regime, operativeat a weak surface attraction, base-paired segments of structured RNAbehave as rigid objects and attach more easily to the substrate thanunstructured, undulating RNA fragments . Increasing surface attraction leads to a second regime,which favors the adsorption of unstructured RNA fragments over structuredones. The existence of this turning point in adsorption does not dependon the exact nature of the interaction potential but appears to bemore general. Namely, we demonstrated that the Mie potential, basedon the van der Waals interaction, yields a similar behavior in adsorption.We rationalized the origin of the two adsorption regimes as an interplaybetween the conformational entropy of the RNA fragments and the surfaceattraction. We complemented our simulations with an analytical scalingtheory of the ideal chain, which provides deeper insight into thequalitative trends of adsorption of long polyelectrolytes as a functionof a wide range of substrate attraction strength. Based on the theoreticaland simulation trends, we expect that the two observed adsorptionregimes should persist even for very long RNA molecules .51 A particularly noticeable example is RNA packagingin viral capsids, where it has been observed that unstructured RNAmolecules can compete with the native RNA genome when simultaneouslypresent in the solvent.52Our results, which indicate a selectivityin adsorption betweensingle- and double-stranded regions of RNA, underline the importanceof the RNA structure in regulating its adsorption to various substrates.We expect that the selective adsorption of one RNA structure overthe other could be experimentally controlled by tuning the interactionstrength, for instance, by changing the salt concentration or pH.Moreover, the lower interaction free energies of unstructured RNAscompared to structured, double-stranded ones at high attractions suggestthat possibly highly attractive surfaces may promote the unfoldingof a double-stranded RNA structure. This would add an additional layerof complexity to the RNA–substrate interactions, differentiatingthe behavior of RNA and DNA information carriers when interactingwith biological substrates. These observations can have crucial andfar-reaching biological implications since RNA adsorption is linkedto numerous biological functions, including phosphate positioningin virus shells, stability of RNA nanocarriers, and transfection ofshort RNAs.In the future,it would be insightful to extend the studies toother (longer) RNA structures and different specific molecular substrateinteractions and geometries. Further optimization of our code willallow us to extend and test those predictions. As for short RNA molecules,we already demonstrated that our computational model is versatileenough and generalizable to tackle more complex interaction potentialsbetween RNA bio-macromolecules and molecular substrates.53 RNA structure modeling combined with computational methodology isthus quickly developing and reaching higher precision/resolution,with our computational efforts fitting nicely into this newly emergingparadigm, providing additional insights into the interpretation ofphenomenology as well as all the way to improving the assessment ofsecondary structure candidates.Weemphasize this point because several experimental techniquesfor the secondary RNA structure characterization can be much improvedby connecting them with reliable computational modeling when combinedwith high-throughput experimental data.54 that offers a good balance between computational efficiency andstructural detail, as shown for the 3D domain reconstruction of theSTMV genome.55 In our model, we implementedthe potential of the flat substrate (S1) and further analysisfor the conformational sampling (see the Supporting Information for details). The resulting multiscale method isavailable in this work and hence could be further implemented in models/codes60 of preference. 14 metric withrespect to a structured template, which is referred to as the A-form.The definition of the metric and the parameters used can be foundin the Supporting Information.To simulate the RNA fragments,we adopt a coarse-grained representationubstrate 1 and S1 61 Monte Carlosimulations together with the weighted histogram analysis method (WHAM).62 The employed collective variable (CV) was theminimum distance between the center of mass of the RNA molecule andthe surface. In this specialized procedure, each distance is consistentlysampled by an individual simulation using a harmonic restraint, whichimproves sampling and convergence of the PMF. Histograms of the distance dCM were used to define the PMF63 The error bars were estimated by the bootstrappingmethod after carefully determining the auto-correlation time of eachMonte Carlo simulation by means of blocking analysis. Additional parametersof the simulations can be found in the Supporting Information. Tables S6–S8 in the Supporting Information contain details on the CV constraintparameters of each run. Histograms of the CV are given in Figures S8 and S9 in the Supporting Information,which highlight the quality of the systematic sampling used in ourcalculations. Further simulation scripts and analysis files can befound at https://zenodo.org/record/4646934.The potential of meanforce (PMF) was obtained systematically bymeans of Umbrella Sampling


Stable social relationships are conducive to well-being. However, similar effects are not reported consistently for daily social interactions in affecting episodic  subjective well-being (ESWB). The present investigation suggests that the choice of being in a social context plays an important moderating role, such that social interactions increase ESWB only if taken place by one's choice. Moreover, it is argued that choice matters more in a social context than in an alone context because experiences with others are amplified. These ideas were tested and supported in two studies: An experiment that manipulated social context and choice status, and a 10-day experience-sampling study, which explored these variables in real-life settings. Results showed that being with others by one’s choice had the strongest positive association with ESWB, sense of meaning, and control, whereas being with others not by one’s choice—the strongest negative association with ESWB. Effects of being alone on ESWB also varied by choice status, but to a lesser extent. The findings offer theoretical and practical insights into the effects of the social environment on well-being. Modern days present individuals with ever-growing possibilities for managing their social lives. Developments in computing, communication, and transportation, introduce novel channels for social interactions, alongside increased opportunities for spending time alone productively  SWB  reflects the mood and emotions that people experience in a given context  is based on general and static  estimations of the variables, such as in the association between one's marital status and general satisfaction with life Myers, . These fUsing diary, day reconstruction, and experience sampling methods, research has started to explore the association of daily social interactions with ESWB. Nezlek et al.  reportedHowever, other studies have indicated that social interactions do not always bring about greater ESWB. Hudson et al.  emphasizDoes time alone contribute systematically to well-being? Recent years have seen a surge in research on solitude, and with it in findings associating solitude to well-being . Notwithstanding, these factors oftentimes do not convey systematic variations in experience. For example, as emerging from the findings of Kahneman et al.  and EpleA factor that has not attracted much attention but holds a potential to play an important role as a moderator is whether the setting is elected or imposed. That is, whether the person is in social interaction  by personal choice or because of external circumstances. Research involving real-life data has addressed the question of choice with only a handful of studies, whereas lab-based experimental data is almost entirely focused on imposed social settings. Tentative evidence for the role of elected social contacts on ESWB comes from an experience sampling study by O'Connor and Rosenblood . Their ra different impact on well-being when one chooses to be alone versus when one chooses to be with others—a question at the core of the present investigation. Reason has it that volition plays a stronger effect in the 'with others' context. Research indicates that relative to alone experiences, social interactions are highly arousing  has a more substantial impact on ESWB in a ‘with others’ context than in an alone context. Study 1 was an experiment that sought to control for exogenous variables. Study 2, our main study, applied an experience-sampling method to test our prediction in real-life dynamics.https://osf.io/tukwe/Sample size considerations and statistical power calculations are reported at the introduction of each study. All materialsIn Study 1 we sought to test the effect of choice to be alone/'with others' on ESWB in a controlled setting . We specifically sought to control for the physical setting, because people’s (chosen vs. not) social experiences are often attached to specific environments . To this end, we asked participants to report about their ESWB while instructing them to consider a fixed physical environment (“at home”). If, as outlined in the Introduction, choice is more consequential to well-being 'with others'  because of the psychological impact of others’ company, its differential effect should show even when controlling for the physical environment. To further substantiate this idea, we also asked the participants to consider another environment (“at work”), which often introduces a different probability of being alone (and with others) by choice (or not) than the home setting. We expected to repeat the interaction of choice by social context from the “at home” setting in the “at work” setting.d = 0.50 with 80% power in the (2-by-2) within-subject design of the present study requires a sample size of N = 34. Given that we were mainly interested in the interaction of choice and social setting, we followed with another power analysis using simulation-based software  with 80% power. Our final sample has exceeded this.A-priory power analysis  were recruited via the Prolific Academic platform (https://www.prolific.co) to a study on 'life experiences and subjective well-being'. The sample comprised of 52 Females, 33 Males, Mage = 32.85 (SDage = 12.50), residents of the United Kingdom (n = 83) and the USA (n = 2). All respondents were included in the analysis.Participants . On entering the study, participants signed a consent form and proceeded to the main part, which comprised of two questionnaires asking them to rate their ESWB. After completing their ratings, participants were thanked and compensated.Two 4-item questionnaires were presented in random order.at home. Next, they read 4 scenarios (presented in random order) depicting social context  and choice status for being in this context . For example: “[At home] alone, by your choice” or “[At home] with other people, because of external circumstance ”. For each of the 4 scenarios, participants rated their level of satisfaction on a 1 = not satisfied to 7 = very satisfied scale.Participants were instructed to think of themselves while The same 4 scenarios from the ‘at home’ setting, this time instructing participants to think of themselves while at work.SDs of the satisfaction ratings across the different settings. As seen in Table Table F = 207.68, p < 0.001, η2p = 0.712, with satisfaction higher in the 'my choice' condition  compared with 'not by my choice' . No effect was found for social context, F = 0.18, p = 0.68, η2p = 0.002, addressing the difference between the alone context  and the 'with others' context .To formally test our prediction about the differential effect of choice in the 'with others' context as compared with the alone context, we conducted a 2  by 2 (my choice/not my choice) repeated measures ANOVA. Focusing first on the 'at home' setting, the analysis revealed a main-effect for choice, F = 6.48, p = 0.013, η2p = 0.072, reflecting a larger discrepancy between the two choice conditions in the 'with others' context  than in the alone context . That is, results from the 'at home' context indicated that choice makes a larger difference in a 'with others' context than an alone context, even when the physical setting is controlled.Importantly, the analysis revealed a significant interaction between social context and choice status, F = 100.65, p < 0.001, η2p = 0.545, with satisfaction higher for the 'my choice' condition  compared with 'not by my choice' . No effect was found for social context, F = 1.84, p = 0.18, η2p = 0.02, addressing the difference between the alone context  and the 'with others' context .We followed with another repeated measures ANOVA, focusing on the 'at work' setting. The analysis revealed a main-effect for choice, F = 7.12, p = 0.009, η2p = 0.078, reflecting a larger discrepancy between the two choice conditions in the 'with others' context  than in the alone context . That is, results 'at work' replicated the findings from the 'at home' setting in terms of the greater impact of choice on ESWB 'with others' than alone.2Importantly, the analysis yielded a significant interaction between social context and choice status, Taken together, results based on two different physical settings indicate that choice matters more in affecting ESWB in a 'with others' context than in an alone context. These findings indicate that the amplifying impact associated with choice in a 'with others' context reflects the psychological experience and not variation (or lack of) in physical settings. That is, people appear to experience being with others  as more consequential to their well-being. In Study 2, we sought to test these ideas over an extended period, across many events, and by looking at a wider range of expressions of ESWB.sense of meaning in their current activities. To the extent that actions are magnified in social contexts  social contexts by sampling within and across days. To this end, participants reported 3 times a day for 10 days (5 days a week for two weeks) about their social context and their choice of being in this context. They then reported about their ESWB, which included items about satisfaction with life and positive and negative affect. Participants also reported their r ≥ 0.09). Our final sample (N = 155) is consistent with that and is also in line with current norms in studies utilizing a similar design  were Israeli students recruited through a university bulletin board to participate in a broad experience sampling research, aimed at learning about the implications of daily experiences on psychological states. As part of this broader study, personality questionnaires , demographic data, and contact information were collected at a start-up session.Participants in this study (Episodic data were collected by prompting participants (with text messages to their phones) to report three times a day  for 10 consecutive days (weekends excluded). Episodic reports started by asking about the current social context  and whether this social context was a result of one's choice or not. Participants then reported about their ESWB  and their sense of meaning and control.currently alone (coded 0) or with other people (coded 1). 'With others' was defined as being in the same space with other people, and/or actively communicating with other people. Alone was defined as being physically alone while not actively communicating with other people.Participants reported with one question whether they are Participants reported with one question whether they are in their respective social condition  by their choice (coded 0) or not by their choice .strongly disagree to 5 = strongly agree scale) based on their experiences in the past few minutes (α = 0.75).Satisfaction with life was measured with 2 items (“I am satisfied with my life” and “The conditions of my life are excellent”) taken from the Satisfaction with Life Scale  and two items were used to measure negative feelings .Participants were presented with 4 items representing positive and negative feelings. Ratings were made with reference to very little or not at all to 5 = extremely scale (α = 0.79).Participants were presented with 2 items (“My actions in the past few minutes have meaning” and “My actions in the past few minutes fill me with interest”) adapted from the Meaning in Life Questionnaire .Participants reported along 2 items  from the Pearlin Self-Mastery Scale , results were analyzed by multilevel modeling with SPSS Mixed procedure, and jamovi's  reports per participant out of 30 potential reports, reflecting a high response rate (92.38%). Across all momentary reports, participants were alone 37.1% of the time and with other people 62.9% of the time. Participants were in a social condition of their choosing 64.3% of the time and in a social condition that is the result of external demand 35.7% of the time. When with others, participants were in 59.2% of the episodes by their choice (and in 40.8% not by their choice), whereas when alone, they were in 72.8% of the episodes by their choice (and in 27.2% not by their choice).The 155 participants provided 4296 momentary reports, yielding a mean of 27.71  and choice status (my choice/not my choice) in affecting ESWB. In all analyses, our predictors were social condition  and choice status condition , followed by their interaction term . We present the results by our dependent variables: Expressions of ESWB , sense of meaning, and control/mastery.b = 0.09, SE = 0.01, 95% CI , t(4151) = 5.919, p < 0.001, indicating that participants reported greater satisfaction in the company of others, compared to when they were alone. A main effect was also found for choice status, b = − 0.05, SE = 0.02, 95% CI , t(4158) =  − 3.275, p = 0.001, indicating greater satisfaction when the social context was a result of choice, compared with a result of external constraints. Table b = − 0.09, SE = 0.02, 95% CI , t(4154) =  − 4.84, p < 0.001, but it made little difference alone, b = 0.03, SE = 0.03, 95% CI , t(4156) = 1.25, p = 0.21. Put simply, choice was more consequential in affecting episodic satisfaction with life 'with others' than alone.Step 1 of the analysis (without an interaction term) yielded a main effect for social context, b = 0.26, SE = 0.03, 95% CI , t(4198) = 10.33, p < 0.001, indicating more positive feelings in the company of others . A main effect was also found for choice status, b = -0.38, SE = 0.03, 95% CI , t(4223) = − 14.47, p < 0.001, indicating more positive feelings when the social context was by one's choice (vs. not). Table b = − 0.48, SE = 0.03, 95% CI , t(4209) =  − 15.35, p < 0.001, than in the alone condition, b = − 0.16, SE = 0.05, 95% CI , t(4219) =  − 3.48, p < 0.001.Step 1 of the analysis yielded a main effect for social context,  0.31], t198 = 10.b = − 0.13, SE = 0.02, 95% CI , t(4185) =  − 6.15, p < 0.001, indicating reduced negative feelings in the company of others . A main effect was also found for choice status, b = 0.17, SE = 0.02, 95% CI , t(4208) = 7.31, p < 0.001, reflecting stronger negative feelings when the social context was not by one's choice. Table b = 0.21, SE = 0.03, 95% CI , t(4195) = 7.55, p < 0.001, than in the alone condition, b = 0.08, SE = 0.04, 95% CI , t(4204) = 2.02, p = 0.04. Therefore, for negative feelings as well, choice was more consequential in affecting episodic feelings 'with others' than alone.Step 1 of the analysis yielded a main effect for social context, In sum, whether it was in reporting about their experiential satisfaction with life or their momentary affect ratings, choice had a notably stronger effect when people were with others as compared to when they were alone. In our next set of analyses, we have looked at additional variables, which shed more light on the overall experience.b = 0.35, SE = 0.03, 95% CI , t(4205) = 11.99, p < 0.001, indicating a stronger sense of meaning to activities occurring in the company of others . A main effect was also found for choice status, b = − 0.29, SE = 0.03, 95% CI , t(4232) =  − 9.72, p < 0.001, showing that actions taking place by one's choice are subjectively more meaningful. Table b = − 0.34, SE = 0.04, 95% CI , t(4218) =  − 9.53, p < 0.001, than when alone, b = − 0.18, SE = 0.05, 95% CI , t(4228) = − 3.44, p < 0.001. Taken together, being with others was experienced as more meaningful especially when this was by one's choice.This set of analyses explored how meaningful participants experienced their time 'with others'/alone, when it was by their choice (vs. not). Step 1 of the analysis yielded a main effect for social context,  0.29, 0.0, t = 1.543, p = 0.123. A main effect showed for choice status, b = − 0.096, SE = 0.018, 95% CI , t(4182) =  − 5.31, p < 0.001, indicating that actions taking place in a social context of one's choice induced greater sense of control. Table b = − 0.13, SE = 0.02, 95% CI , t(4174) = − 6.18, p < 0.001, but it made no difference in affecting sense of control alone, b = − 0.01, SE = 0.03, 95% CI , t(4179) =  − 0.44, p = 0.658. That is, sense of control was experienced as stronger with others, mostly when it was by one's choice.Our final set of analyses was focused on how much control participants experienced in the situations sampled. Step 1 of the analysis yielded no main effects for social context, By studying participants’ experiences in their natural environment, this study affirmed our previous findings that ESWB is shaped by an interaction between the social context and choice of being in this context. Across the different expressions of ESWB, choice was more consequential 'with others' than alone, corroborating approaches that suggest that social contexts act to amplify and intensify experiences  carries important short-term . These are important aspects of our social lives, but the knowledge acquired only via a 'stable relations' lens does not capture the dynamics of our social lives as they unfold across the scenes that comprise our daily experiences , which sampled more than 4200 episodes across 10 days, uncovered some of the dynamics of (young) individuals’ daily social lives. Participants reported being with others in about 63%  of the sampled episodes (which were throughout the day), and regardless of the social context, they were also in a setting of their choice in most (64%) of the episodes. These frequencies are consistent with findings reported in previous studies  episodic social interactions that emerges from the present findings concerns the sense of meaning. Social contacts were constructive when they were experienced as meaningful. Interestingly, low meaningful contacts  were nonetheless associated with a relative reduction in ESWB, highlighting an often-neglected aspect in our daily social life. Furthermore, our findings imply that choosing (and perhaps initiating) social interactions is central in affecting ESWB, thus accounting for both—the reason why many people do not initiate such relations , and why they may gain if acted to initiate  interactions  emerged as a setting of relative stability, with participants experiencing their different alone conditions quite similarly. Therefore, solitude might not present immediate benefits to well-being, but it does appear to offer a more predictable experience, and if utilized effectively could be a source of personal growth  in determining ESWB, sense of meaning, and control. This finding showed in controlled settings (Study 1) and real-life data (Study 2). This finding is in line with approaches stemming from laboratory research, which associate social presence with polarizing effects , participants were nonetheless from Western cultures (UK and Israel), and Study 2 participants were  college students. Perceptions and experiences of aloneness and of being with others may differ by culture and over the lifespan. Marital status, family composition, and work status could affect not only the likelihood of being with others  by choice (or not) but also one’s experience in these conditions. Future research could extend the present findings beyond the sampled populations and systematically consider the role of different life conditions.3Second, the present studies were focused on transient situational variables, yet individual differences in personality may also affect the experiences in these settings. For example, being alone is experienced differently by individuals varying in neuroticism  and solitude take different forms under extreme conditions, and this warrants separate investigations. Moreover, choice was considered in our study a (subjectively judged) dichotomy. It could be argued that situations are often a mix of choice and constraints. Future research could address this issue by considering different levels of experienced choice. In addition, although our Study 2 sampled a large number of episodes across and within days, it addressed experiences resulting from being in a given situation, but not dynamics resulting from these situations. Future research could address such dynamics by looking at situational contingencies , time spent in each situation, and variations in ESWB over extended periods. Additionally, we did not ask about the specific activities that participants were doing (nor about their level of engagement with other people in the ‘with others’ setting). Future research could extend the present findings by emphasizing the type of activities people pursue under these settings.Relatedly, the present research was focused on self-related constructs. Future research could address implications associated with interpersonal variables , and objective outcomes . An additional extension concerns intervention aiming to modify the perceptions of choice in (imposed) social contexts  and their impact on ESWB.Social contexts and choice of being these contexts affect ESWB. The present findings reveal that their interaction matters, and that choice is associated with a stronger difference in ESWB when one is with other people than when one is alone. In terms of our momentary experiences, sensing that we are in the company of others by our choice is associated with the greatest boost to our well-being, sense of meaning, and control, whereas our time alone embodies an experience of relative stability.


Upon SARS-CoV-2 infection, viral intermediates specifically activate the IFN response through MDA5-mediated sensing and accordingly induce ADAR1 p150 expression, which might lead to viral A-to-I RNA editing. Here, we developed an RNA virus-specific editing identification pipeline, surveyed 7622 RNA-seq data from diverse types of samples infected with SARS-CoV-2, and constructed an atlas of A-to-I RNA editing sites in SARS-CoV-2. We found that A-to-I editing was dynamically regulated, varied between tissue and cell types, and was correlated with the intensity of innate immune response. On average, 91 editing events were deposited at viral dsRNA intermediates per sample. Moreover, editing hotspots were observed, including recoding sites in the spike gene that affect viral infectivity and antigenicity. Finally, we provided evidence that RNA editing accelerated SARS-CoV-2 evolution in humans during the epidemic. Our study highlights the ability of SARS-CoV-2 to hijack components of the host antiviral machinery to edit its genome and fuel its evolution, and also provides a framework and resource for studying viral RNA editing. Editing sites show up when a sequence is mapped to the genome: while the unedited sequence reads A, sequencing identifies the inosine in the edited site as guanosine (G), thus A-to-G variants are indicative of A-to-I editing sites. Although signatures of ADAR activity have been previously inferred in the consensus genome sequences of various RNA viruses , includiWe used the complete genome sequence SARS-CoV-2 Wuhan-Hu-1 strain  as the reference genome.https://www.ncbi.nlm.nih.gov/sars-cov-2/). A list of sample IDs is shown in RNA-seq data were downloaded from NIH SARS-CoV-2 resource website . The original (four-letter) sequences of the reads that aligned (after the transformation) were recovered, and RNA variants between the reads and the reference genome were examined. For multiple mapped reads, only the best hits were retained. Next, we grouped RNA variants into three categories:  A-to-G/TTo determine the specificity of our pipeline, we repeated it when searching for other types of variant sites , which involved modifying the transformation and the definition of the editing mismatches accordingly, but was otherwise identical to the A-to-G screen. There are 12 possible single-nucleotide mismatches. However, since the RNA-seq reads could be either sense or antisense, we could not distinguish between a given mismatch and its complementary one. We therefore reported results for six categories of variant types.We used a widely used pipeline for conventional RNA variant calling . In brieWe first merged the bam file containing clustered read mapping results with the bam file containing the mapped reads. Next, we inspected all editing positions using samtools for editing level quantification. We required that the minimal base quality was 30, and only sites covered by at least 30 reads were retained.617 nasopharyngeal swab samples from the New York City metropolitan area during the COVID-19 outbreak in spring 2020  were useIFIH1 gene) expression. Reads were mapped to the human reference genome GRCh38 using Hisat2 (Version 2.0.4) (TPM (transcripts per million) was used to represent ADAR1 and MDA5 (n 2.0.4)  with defn 2.0.4)  was usedThe effects of recoding sites in spike protein on RBD expression and ACE2 binding were measured based on deep mutational scanning data . The effTo examine the overlaps between recoding editing sites in spike protein and variants of concern, we downloaded variant watch lists using the GISAID ‘Emerging Variants’ portal.We selected seven recoding editing hotspots located in the NTD and generated mutants with individual editing sites. As negative and positive controls, we generated wild type spike gene and a deletion mutant that is known to affect the binding of a neutralizing antibody targeting the NTD . Vero E6Indirect immunofluorescence was performed as previously reported . In brieThe in vivo structure of SARS-CoV-2 was obtained from a previous study . For eacet al. (http://www.pymol.org/).The spike protein sequence diagram was created by IBS 1.0.3 . Spike pet al.  , butOne hallmark of ADAR-mediated editing is that editing sites are clustered together, and such a feature has been successfully used to develop a pipeline to call hyper-editing sites . MoreoveTo verify our pipeline, we applied it to RNA-seq data from a cell culture model of SARS-CoV-2 infection . In brieHaving established the method for virus-specific editing calling, we analyzed RNA-seq data from diverse types of samples for a global characterization of A-to-I RNA editing events in SARS-CoV-2. A total of 7622 published RNA-seq samples, including nasopharyngeal swabs of COVID-19 patients, autopsy tissue samples of donors who died of COVID-19, and organoids and cell models infected with SARS-CoV-2, were collected Figure . 1727 2, of whicNext, we investigated the landscape of A-to-I RNA editing in SARS-CoV-2. Similar numbers of editing sites in + and - strands were identified, and both were relatively evenly distributed across the genome Figure . This reTo ask whether editing hotspots were present in the viral genome, we examined the number of edited samples at each editing position. We found 2271 sites present in multiple samples, ranging from 3 to 41 Figure . As a grTo understand the dynamics of RNA editing, we performed three analyses. First, we compared the overall editing levels between samples and found that they varied Figure , which wThe trimeric spike protein decorates the surface of coronavirus and plays a key role in the receptor recognition and cell membrane fusion process . The spiTo experimentally examine the impact of RNA editing on altering antigenicity, we selected seven recoding editing spots located in the N-terminal domain (NTD) of the spike protein. We generated spike mutants with individual sites and assessed the impact of RNA editing on antibody binding. We also included a deletion mutant that is known to affect the binding of 4A8 mAb, a neutralizing antibody targeting the NTD . Cells wThe RNA editing events may occur in both strands of sgRNAs and gRNAs. Those in sgRNAs may only affect the characteristics of the viruses within the infected individual; while those in gRNAs might transmit, thus fueling viral evolution in humans. Given the overall low-level editing in SARS-CoV-2, we expect that A-to-I editing may have a low or moderate effect on the infected individual. However, RNA editing introduced substitutions might provide a new source of mutation and contribute to SARS-CoV-2 evolution in human populations. Extensive global sampling and sequencing of SARS-CoV-2 have enabled us to examine the impact of A-to-I RNA editing on its evolution. Because A-to-I editing tended to be clustered, we reasoned that if A-to-I editing contributes to virus evolution, such cluster signature could be found in viral sequences. Thus, we searched the GISAID sequence database  for sequIf A-to-I RNA editing accelerates SARS-CoV-2 evolution in humans, we would expect that the A positions with editing events observed  may be more likely fixed as Gs during the epidemic. We thus compared the frequencies of A-to-G mutations inferred using sequences in GISAID between editable and uneditable As in the genome. We found that editable As tended to have higher frequencies, particularly for the sites in the intergenic regions Figure , which aKnowledge of the host immune response factors that introduce mutations is important for the simple reason that RNA viruses, particularly (+)ssRNA viruses, are major pathogens of humans. In this study, we developed an approach to robustly identify A-to-I RNA editing in RNA viruses. By applying our approach to SARS-CoV-2, we characterized the landscape of RNA editing in the SARS-CoV-2 genome and the association between viral editing and intensity of host innate immune response. The comprehensive lists of SARS-CoV-2 A-to-I editing sites and hotspots identified here present a resource for the study of SARS-CoV-2 biology, evolution and spread. Moreover, when applying our approach to four other human (+)ss RNA viruses , we found the presence of A-to-I RNA editing in all four viruses investigated , suggestIn combination with an integrative analysis of GISAID sequence database  and our Compared with replication error-introduced substitutions, A-to-I editing-introduced substitutions have distinct features Figure . First, While this paper was being revised, Picardi et al.  publishewww.gsaid.org; see https://github.com/SYSU-zhanglab/RNA-virus-editing).All raw sequencing data were downloaded from NIH SARS-CoV-2 resource website . All othgkac120_Supplemental_FilesClick here for additional data file.


UNC-45A (Protein unc-45 homolog A) is a cytoskeletal-associated protein with a dual and non-mutually exclusive role as a regulator of the actomyosin system and a Microtubule (MT)-destabilizing protein, which is overexpressed in human cancers including in ovarian cancer patients resistant to the MT-stabilizing drug paclitaxel. Mapping of UNC-45A in the mouse upper genital tract and central nervous system reveals its enrichment not only in highly proliferating and prone to remodeling cells, but also in microtubule-rich areas, of the ovaries and the nervous system, respectively. In both apparatuses, UNC-45A is also abundantly expressed in the ciliated epithelium. As regulators of actomyosin contractility and MT stability are essential for the physiopathology of the female reproductive tract and of neuronal development, our findings suggest that UNC-45A may have a role in ovarian cancer initiation and development as well as in neurodegeneration. UNC-45A (Protein unc-45 homolog A) is a member of the UCS (UNC-45/CRO1/She4p) protein family , with duIn light of the role played by UNC-45A in regulating cell proliferation and of its role as a MAP with MT-destabilizing properties, the objective of this study was to determine the pattern of UNC-45A expression in cells of the mouse genital tract with different proliferative and remodeling capacities and in the mouse central nervous system (CNS).We found that UNC-45A is enriched in the highly proliferating and prone to remodeling cells of the mouse reproductive system, in the microtubule-rich regions of the mouse central nervous system and in the cilia of both, the mouse reproductive system and the brain. Taken together, these findings suggest that UNC-45A may play a role in the physiology and pathology of the female reproductive apparatus and the central nervous system.Ovaries, fallopian tubes, brains, and spinal cords from adult C57BL/6 mice were preserved in 10% formalin buffer solution for 24 h followed by 70% ethanol to prevent the tissue from decomposing, and embedded in paraffin. At least two different mice were used to evaluate the UNC-45A expression level in CNS and mouse upper genital tract. The phase of the estrous cycle was determined by histological evaluation as previously described ,31.Anti-UNC-45A Rabbit Polyclonal antibody  was used for IHC and IF. The specificity of this antibody has been previously validated by us and others by Western Blot, IF, and IHC analyses [Five μm formalin-fixed; paraffin-embedded (FFPE) tissue sections were subjected to hematoxylin and eosin staining and immunohistochemistry (IHC) for UNC-45A. Slides were deparaffinized with 100% xylene and rehydrated with gradient ethanol . Antigen retrieval was then carried out with 1X Reveal Decloaker  in a vegetable steamer for 30 min at 100 °C, before blocking the slides with Background Sniper  for 13 min at room temperature. Sections were subsequently incubated with anti-UNC45A antibody at a dilution of 1:100 for mouse brain and spinal cord and 1:200 for mouse upper genital tract overnight at 4 °C, followed by Biotin-SP-conjugated AffiniPure Goat Anti-Rabbit IgG  at a dilution of 1:200 for 30 min at room temperature and incubation with horseradish peroxidase streptavidin at a dilution of 1:125  for 30 min at room temperature. After the staining was developed with 3,3′-diaminobenzidine  for 3 min, the slides were counterstained with Harris’ hematoxylin.Brightfield images were acquired with a Zeiss Axio Scan.Z1 system  at 40× magnification. Images of details were taken with a BX40 light microscope, DP72 camera, and cellSens Standard v1.16 imaging software .For immunofluorescence analysis of UNC-45A and NeuN  in a mouse brain, 5 μm formalin-fixed; paraffin embedded (FFPE) tissue sections were deparaffinized, rehydrated, retrieved, and blocked similarly to what described in the immunohistochemical staining section. Sections were then incubated with anti-UNC45A and anti-NeuN at the indicated concentration overnight at 4 °C. Secondary antibodies were used at the indicated concentration for 1 h at room temperature and sections were mounted with mounting media containing DAPI  . Images were obtained on an Axiovert 200 microscope  equipped with a high-resolution CCD camera.Quantification of immunohistochemistry was done on ImageJ using a slightly modified version of a previously described protocol . BrieflyWe and others have previously shown that UNC-45A is expressed in human ovarian surface epithelial cells and human breast cells and overexpressed in highly proliferative cells of ovarian and breast cancers as compared to their normal counterpart ,25. HereFurthermore, UNC-45A is strongly expressed in the oocytes  with MT-severing properties ,7, whichWe found that in the cerebellum UNC-45A is most strongly expressed in the white matter A. As shoNext, we performed H&E and UNC-45A staining of the mouse spinal cord B, i. thaTaken together, this suggests that UNC-45A may play a relevant role in nervous system physiology. In particular, considering the crucial roles of MTs and their MAPs in neuronal biology ,36, the Here, we found that in the mouse upper genital tract UNC-45A is enriched in proliferating and prone to remodeling cells as compared to quiescent cells. When we took into account possible variabilities in the expression of UNC-45A following the hormonal and structural changes that accompany the progression of the estrous cycle, we found no significant differences in UNC-45A expression pattern in diestrus vs. proestrus. Given that the transition from diestrus to proestrus occurs with an important hormonal shift from progesterone to estrogens, these findings suggest that UNC-45A expression could be only indirectly related to female hormones. On the other hand, considering UNC-45A known roles, minor changes may more likely be explained by the differences in proliferation that naturally occur during phase transition. Indeed, if compared to diestrus, during proestrus we found higher levels of UNC-45A in the more mature follicles, which are also more proliferative in this phase, but smaller differences were found in the corpus luteum, where UNC-45A may be still required for the cytoskeletal remodeling that occurs during cellular degeneration. Of note is that we found that UNC-45A is strongly expressed in both the oocyte and the ciliated epithelium, which plays a crucial role during fertility, as it allows for the progression of the oocyte along the fallopian tube after ovulation. These findings, along with the fact that UNC-45A is overexpressed in ovarian cancer  and thatWe also found that UNC-45A is expressed in neurons in the mouse nervous system and is particularly enriched in areas containing axons and dendrites. Interestingly, Tau, a MAP that stabilizes MT via preventing MT severing , is largUNC-45A cause a syndrome characterized by diarrhea, cholestasis, bone fragility, and impaired hearing [Lastly, we found that UNC-45A is abundantly expressed in both the ciliated columnar epithelium of the fallopian tube and the cilia of the ependymocytes. Interestingly, congenital loss-of-function mutations in  hearing , all of  hearing ,58,59. F hearing . Althoug hearing . Taken t


Viral RNA from virus was recovered 88.10 ± 8.03% from the surface and free RNA fragment was removed by 99.75 ± 0.19% from the final eluted solution. When we tested the developed method under laboratory conditions, a 10-fold higher viral detection sensitivity (Detection limit: 1 pfu/100 cm2) than the current commercial protocol was observed. Using our new sample preparation protocol, we also confirmed that the virus was effectively removed from surfaces after chemical disinfection; we were unable to measure the disinfection efficiency using the current commercial protocol because it cannot distinguish between viral RNA and free RNA fragments. Finally, we investigated the presence of SARS-CoV-2 and bacteria in 12 individual negative pressure wards in which patients with SARS-CoV-2 infection had been hospitalized. Bacteria (based on 16 S DNA) were found in all samples collected from patient rooms; however, SARS-CoV-2 was mainly detected in rooms shared by two patients.It is highly important to sensitively measure the abundance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on various surfaces. Here, we present a nucleic acid-based detection method consisting of a new sample preparation protocol that isolates only viruses, not the free RNA fragments already present on the surfaces of indoor human-inhabited environments, using a graphene oxide-coated microbead filter. Wet wipes (100 cmThe online version contains supplementary material available at 10.1186/s40580-021-00281-8. The outbreak of coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in China at the end of 2019 and has become a pandemic . AntivirNucleic acid (NA)-based diagnosis, using ribonucleic acid (RNA) amplification, is currently one of the most popular methods to measure the viral abundance in both patients with suspected infections and the environment, because this method is more sensitive than antigen or antibody-based tools as it directly utilizes and amplifies the target viral RNA , 13. NevSwab protocols utilizing guanidine-based technology are presently the most commonly used method of collecting target pathogens from patients or environments and extracting and purifying NA –18. Howe2) and aliphatic (sp3) domains that facilitate interactions at its surface interface  was inoculated and incubated with shaking every 10 min for 1 h at 37 °C in 5% CO2. The virus culture medium was then removed. The infected MRC-5 cells were cultivated in 4 mL of Dulbecco’s MEM containing 2% FBS at 37 °C in 5% CO2 for 5 days. When 90% of the cells detached from the bottom, the virus was isolated by centrifugation at 3200×g for 10 min.HCoV-229E was provided by the BioNano Health-Guard Research Center. MRC-5  cells were grown to a concentration of 1 × 10g, 3 min). The RNA from the virus adsorbed onto the GO surface was extracted by adding 300 µL of lysis buffer  into the column and soaking for 3 min. The solution containing the extracted RNA was released into the elution tube by centrifugation .Wet wipes (10 cm × 10 cm) were used to collect the virus from the surface (1 m × 1 m). After collection, the wipes were soaked in 10 mL of desorption buffer  with 5% ethanol) and shaken for 1 min, such that the collected virus was transferred to the desorption buffer. When 1 mL of adsorption buffer  was added to the recovered desorption buffer, the virus was adsorbed onto the GO surface as the solution was passed through the GO bead column by centrifugation . After collection, the swab was soaked in 200 µL of phosphate buffer saline and shaken for 1 min. It was treated with a QIAamp viral RNA mini kit  for RNA extraction.® 480 Instrument II, Roche, Basel, Switzerland); reactions were assembled with TaqPath™ 1-Step RT-qPCR Master Mix .RT-qPCR was performed to analyze the RNA of SARS-CoV-2, HCoV-229E, and Influenza A virus subtype H1N1 on a thermocycler . Detailed information regarding nucleic acid amplification is summarized in Additional file 2) was cleaned with 70% ethanol solution three times and sterilized with UV light (50 W) for 30 min. A target solution, containing various concentrations of a combination of intact HCoV-229E virus  or Influenza A virus subtype H1N1 RNA  in which COVID-19 patients were hospitalized. Four sampling points  in the negative pressure ward were selected , 31. Sam−1 corresponding to Si–O–Si were detected among all of samples and was decreased by GO coating. Peaks corresponding to the carbon groups  were observed at both of GO-coated surfaces, however there were no significant difference depending on the GO treatment conditions [Glass beads were coated with GO to separate viral RNA and free RNA fragment. Surface modification was confirmed with FTIR, XPS and AFM. The FTIR spectra of bare glass surface and GO-coated surface were shown in Fig. nditions , 33.FigThe XPS spectrum of the carbon region (C1s) was used to confirm the chemical composition of the surface, as shown in Fig. The morphology of GO-coated surface was confirmed with AFM image, as shown in Fig. g). Most of the virions and free RNA fragments were adsorbed onto the GO surface as shown in Fig. GO-coated glass beads  were packed into the isolation column as shown in Fig. 1–104 pfu) were spread on a PMMA surface (1 m2) and fully dried for 30 min. As shown in Fig. To confirm the detection efficiency of the new protocol developed in the current study, various amounts of HCoV-229E solution 101–10 pfu wereFigure This new sample preparation protocol was introduced to measure SARS-CoV-2 surface contamination in an environmental test at the negative pressure ward in a hospital where COVID-19 patients were hospitalized. The performance of the new sample preparation protocol was compared to that of the current commercial protocol using environmental samples collected before and after disinfection. The samples were collected from the patient beds, walls, and toilets (seats) in negative pressure wards  samples collected in negative pressure wards. When free RNA fragments were largely removed by mopping, the cycle threshold value for the inner lavatory samples increased significantly, regardless of the sample preparation method. This also implies that on the patient bed, although viruses were not found, free RNA fragments pre-released from SARS-CoV-2 were present.Using the new sample preparation protocol consisting of wet wipes and a GO bead column, we investigated 12 individual negative pressure wards (not disinfected for 24 h) in which patients had been hospitalized, to detect SARS-CoV-2 and total bacteria. As shown in Fig. In contrast, in single-person and double-shared rooms in which patients could move and communicate, SARS-CoV-2 was found in various environmental samples. In particular, SARS-CoV-2 was found in most samples  in double-shared rooms rather than in single-person rooms. Interestingly, the virus was found on surfaces in close proximity to (bed or toilet) or frequently used by patients (cell phone). The virus was found only on a cell phone in a single-person room in which the patient could move . It is likely that this patient had used the cell phone frequently. Thus, we conclude that without disinfection, SARS-CoV-2 can often be found around patients when they move and/or speak.In the current pandemic situation, numerous studies are being conducted worldwide with molecular diagnosis technology , false-positive signals that occur because of free RNA fragments, which has already been released and cannot be distinguished from that of infectious viruses, has always presented major problems for the field of diagnostics. In this study, surfaces found in hospital wards, including surfaces of cell phones, walls, and toilets, were investigated using a novel sample preparation method that could differentiate the virus alone from free RNA fragments. Consequently, it was possible to isolate and measure only the abundance of the virus itself, not the free RNA fragments . We believe that this protocol and a simple kit can be directly applied to the medical and quarantine industries, including for the re-selection of asymptomatic infected patients and determination of quarantine termination for confirmed infected patients.Additional file 1: Table S1. PCR primer set of each RNA and DNA. Figure S1. SARS- CoV-2 RNA stability in environmental surface condition. Figure S2. Result of SARS-CoV-2 detection by using new sample preparation protocol and commercial protocol ). Figure S3. Layout of sampling area in (a) single-person room and (b) double sharing room. Figure S4. Calibration curve of (a) HCoV-229E, (b) SARS-CoV-2 (triplicated).


Immunotherapy and, in particular, immune checkpoint inhibitors (ICIs), have transformed non-small cell lung cancer treatment options. Although many patients are treated with ICIs, a large number do not respond. Thus, there is a need to identify biomarkers of response. In this study, we evaluated the value of multiple routinely collected variables  as biomarkers of response to ICIs. Our data indicates that, although several characteristics are associated with response, many present strong interrelations, which should be taken into account when creating compendiums of biomarkers to maximize their predictivity. Finally, we describe a collection of characteristics  that, in our group of patients, had the best predictive value.p < 0.005), LDH (HR 1.24 (95% CI 1.03 to 1.48), p = 0.02)) and PD-L1 negativity were associated with decreased progression-free survival (PFS) (HR 1.92 (95% CI 1.03 to 3.58), p = 0.04), whereas presentation of immune-related adverse events (irAEs)  or females  had longer PFS. Additionally, numerous clinicopathological indicators were found to be interrelated. Thus, we searched for features that provide non-redundant information, and found the combination of LDH levels, irAEs, and gender to have a better association with ICIs treatment response . We concluded that several clinicopathological features showed prognostic value in our real-world cohort. However, some are interrelated, and compendiums of features should therefore consider these interactions. Joint assessment of LDH, irAEs, and gender may be a good prognostic compendium.Immune checkpoint inhibitors (ICIs) have transformed non-small cell lung cancer (NSCLC) treatment. Unfortunately, only some patients benefit from these therapies. Thus, certain clinicopathological characteristics of the patients have been proposed as biomarkers of ICIs response. We assembled a retrospective cohort of 262 NSCLC patients treated with ICIs, compiled relevant clinicopathological characteristics, and studied their associations with treatment outcome using Cox proportional-hazards survival models. Additionally, we investigated the interrelations between clinicopathological features and devised a method to create a compendium associated with ICIs response by selecting those that provide non-redundant information. In multivariate analyses, ECOG performance status (hazard ratio (HR) 1.37 (95% CI 1.11 to 1.68),  Immune checkpoint inhibitors (ICIs) have become fundamental to treat advanced non-small cell lung cancer (NSCLC) patients in recent years and are now included as a standard of care. Nevertheless, many patients do not exhibit benefit derived from these treatments. Hence, the biomedical community has intensively attempted to identify biomarkers of response. A tumor’s molecular features, such as Programmed Death-Ligand 1 (PD-L1) expression or tumor mutational burden (TMB), are associated with positive response to ICIs and remain the most prominent biomarkers ,3,4. In However, despite the effort to identify predictive biomarkers, the use of these parameters has not yet been established to discriminate patients who may not receive ICIs because of the lack of benefit.Notably, treatment with ICIs may cause a wide range of immune-related adverse events (irAEs) that can compromise treatment continuation and, in some cases, threaten a patient’s life. Interestingly, few studies have associated irAEs with better response and overall survival in NSCLC. This is likely due to the fact that these undesired side-effects are intrinsically related to the ICIs’ mechanism of action, and thus appearance of irAEs may be a surrogate of its effectiveness ,11,12,13Because ICIs treatment is widely used, cohorts with a larger number of patients evaluating multiple clinicopathological variables in real-world settings can be assembled. The study of these variables can become a useful tool to investigate unselected large patient datasets, and associations between ICIs response (and irAEs), baseline clinical variables and concomitant medications, and to assess their utility as prognostic and predictive biomarkers. Outcomes from these real-world studies can support the medical oncologist community and potentially aid clinicians in their daily decision-making process. In this study, we retrospectively collected clinicopathological information from a cohort of ICIs-treated NSCLC patients, studied the interplay between these clinicopathological features, and associated them with clinical outcomes. Additionally, we designed a method to generate a compendium of features that maximizes the prognostic value while minimizing the number of parameters included.We conducted a real-world, unicentric, retrospective, observational study to determine the interplay between clinical outcomes in advanced NSCLC patients treated with ICIs and different features .Inclusion criteria were: age ≥ 18 years; diagnosis of metastatic NSCLC; treatment with anti PD-1 or anti PD-L1 at any treatment line (at least one cycle administered of ICIs). Exclusion criteria were other concomitant malignancies or loss of follow-up.https://ctep.cancer.gov/protocoldevelopment/electronic_applications/docs/ctcae_v5_quick_reference_5x7.pdf, accessed on November 2017).We investigated 262 consecutive patients diagnosed with advanced NSCLC and treated with ICIs as a first or subsequent line at Vall d’Hebron University Hospital between January 2013 and December 2019. The data source was digital clinical records of the patients, selected by type of treatment, and the data collection was performed using Microsoft Excel, anonymizing personal information. Patients’ characteristics, such as age, sex, performance status, comorbidities, concomitant treatment, and smoking history, were recorded. Similarly, cancer-related features, such as histology, molecular status, PD-L1 expression (in tumor cells), stage at diagnosis, and metastases localization were monitored . Additionally, we recorded other variables: blood biomarkers prior to ICIs treatment ; number of previous systemic treatments; and immune-related adverse events (defined according to Common terminology criteria for adverse events (CTCAE) version 5.0. Department of Health and Human Services, National Institutes of Health, National Cancer Institute).  and overall survival (OS) to measure clinical outcomes. Patients’ outcomes were evaluated by radiological assessment in clinical practice, i.e., with a CT scan each 8–14 weeks according to RECIST criteria V1.1 [For 14 of the 262 patients the reason for the termination of ICIs treatment was not available. Therefore, these patients were not included in the survival analyses.Patients were stratified into three age categories: those under 55 years old were labeled as “young”, those between 55–75 years old were considered “middle”, and those over 75 years old were classified as “elder”. In those patients in which the PD-L1 assessment was qualitative, it was transformed into “positive” or “negative”. Thus, patients with a PD-L1 assessment of 0 were considered to be “negative”, whereas patients with any value greater than 0 were considered to be “positive”. PFS was computed as the number of days between the start of the first line of ICIs administered to the patient and the end of treatment. When treatment was terminated due to progression, the event was considered to have occurred. If treatment termination was due to other reasons , the patient was censored at the time of ICIs termination. For deceased patients, the OS was computed as the number of days between the beginning of the first line of ICIs and the exitus date, and the event was considered to have occurred. For the remainder of the patients, the OS was computed as the number of days from the start of the first line of ICIs and the date of the patient’s last follow-up. The OS of these patients was censored at this date.Univariate and multivariate Cox proportional-hazards models were built using the lifelines Python library (doi:10.5281/zenodo.4579431) with a step-size parameter set to 0.5. Categorical variables were transformed into dummy variables, and numerical variables were standardized.All features were combined in a pairwise manner. When both features were numeric, their association was assessed via Pearson regression. When both features were categorical, their association was assessed using a chi-squared test. When one feature was categorical and the other numerical, a Kruskal–Wallis test was performed.A Cox proportional-hazards survival model for each feature was performed using patients’ PFS as a measure of ICIs benefit. To evaluate the predictive potential of each model, 3-fold cross validation was performed using the k_fold_cross_validation function of the lifelines Python library. This process was repeated 10 times for each feature, using seeds from 0 to 9 defined using the seed function of the random Python library. Thus, 3-fold cross-validation performed 10 times led to 30 Cox proportional-hazards survival models per feature. For each of these models, the Harrell’s Concordance Index was retrieved and the mean concordance per feature was computed, and the feature with the highest mean concordance was selected. Then, additional models with this feature combined with the remainder in a pairwise manner were built, again performing a 3-fold cross-validation 10 times and retrieving the concordance index. Thus, the feature that combined with the previously selected feature led to the greatest increase in concordance, and was selected and included in the model. This procedure was repeated iteratively until no feature led to a concordance increase of at least 0.01.p = 0.69; ICIs vs. CT + ICIs, p = 0.26; TKI + ICIs vs. CT + ICIs, p = 0.58)).Our cohort included a total of 262 advanced NSCLC cancer patients. Their characteristics are summarized in Univariate and multivariate Cox proportional-hazards models revealed that multiple clinicopathological features were associated with ICIs clinical outcome (PFS and OS) . p < 0.005), higher levels of LDH (HR 1.24 (95% CI 1.03 to 1.48), p = 0.02)) and PD-L1 negativity (HR 1.92 (95% CI 1.03 to 3.58), p = 0.04)) were associated with decreased PFS. The presence of metastasis in different sites (prior to ICIs treatment) was also included, with bone metastasis being the only one associated with shortened PFS (HR 1.47 (95% CI 1.0 to 2.17), p = 0.05). By comparison, smoking habit, considered as a continuous variable (packs-year), was associated with increased PFS (HR 0.78 (95% CI 0.62 to 0.98), p = 0.03)), but not when considered as a categorical feature (smoker/non-smoker) . Female gender was also associated with extended PFS . Finally, patients exhibiting irAEs had substantially longer PFS . None of the other parameters were statistically significantly associated with ICIs PFS. In a multivariate analysis, ECOG performance status (HR 1.37 (95% CI 1.11 to 1.68), p < 0.005), LDH levels (HR 1.23 (95% CI 1.01 to 1.48), p = 0.04), and bone metastasis (HR 1.94 (95% CI 1.29 to 2.92), p < 0.005), whereas PD-L1 negativity was nearly statistically significant (HR 2.08 (95% 0.99 to 4.35), p = 0.05). Additionally, neutrophil-to-lymphocyte (NLR) ratio, as a continuous variable (HR 1.46 (95% CI 1.02 to 2.09), p = 0.04) and the presence of liver metastasis (HR 1.84 (95% CI 1.13to 3.00), p = 0.01) were also associated with decreased OS. Notably, from the features associated with increased PFS, only irAEs was also associated with longer OS (HR 0.31 (95% CI 0.18 to 0.52), p < 0.005). Most of the features associated with decreased PFS were also associated with diminished OS in a multivariate analysis: ECOG performance status (HR 1.39 (95% CI 1.12 to 1.74), p = 0.04). By comparison, patients who received corticoids prior to ICIs treatment exhibited lower OS, although this only reached statistical significance in the univariate analysis . Concomitant medications were also included in our analysis. Patients treated with statins exhibited extended OS (HR 0.59 (95% CI 0.37 to 0.96), None of the other variables analyzed  were associated with PFS or OS in the multivariate analysis . NeverthThe differences observed between the univariate and multivariate analyses could be due to the fact that some of the features included in the analyses have a high degree of collinearity. Thus, we decided to study their putative associations . UnsurprBecause many features interact with each other, the combination of some of these features in a compendium may not improve their prognostic value if they provide redundant information. Therefore, we devised a method to create a compendium of features that would maximize the predictive value, while using the minimum number of features. For this purpose, we begun by selecting the clinical feature that, when incorporated in a Cox proportional-hazards model , led to a higher concordance index. Next, we combined this feature with the remaining features in a pairwise manner, constructed new Cox proportional-hazards models, and selected the feature that led to a greater increase in the concordance index in combination with the previously selected feature, and repeated this step iteratively by adding new features to the model until none of them increased the concordance index by more than 0.01. Thus, we observed that the combination of LDH levels, irAEs, and gender offered the best prognostic value based on PFS A. The imIn this study, we assembled a large cohort of advanced NSCLC patients treated with ICIs at the Vall d’Hebron Hospital, and integrated relevant clinicopathological data to investigate their prognostic value, using both PFS and OS as measurements of treatment benefit. Additionally, we studied the interplay between features, which showed that some of the features that were associated with response to ICIs strongly correlate with each other. Taking this into account, we devised a method to generate a compendium of features  that, in combination, better associate with PFS, and retain their prognostic value when considering OS.We analyzed different routinely assessed molecular and cellular peripheral blood markers, and studied them in the context of ICIs. NLR was first described as prognostic marker of OS , which wp = 0.06); thus, it is possible that statins might have a different prognostic value across different tumor types. Corticoids are one of the most well-studied concomitant drugs in the context of ICIs, and previous studies have indicated that patients who received corticoids prior to ICIs treatment exhibit lower OS, but no differences in PFS were observed. [We also incorporated information regarding different concomitant medications into our survival models. Notably, statins statistically significantly associated with OS but not with PFS, indicating that treatment with statins is likely a prognostic marker rather than a predictor of ICIs response. Recent data from a pan-cancer cohort found that statins are not associated with PFS nor OS ,18. Nevebserved. ,20,21. OOur analysis encompassed a wide range of other clinical features. irAEs—regardless of grade—were strongly associated with positive response to ICIs, either considering PFS or OS. This result is consistent with previously published studies ,11,12,13Whether the presence of metastasis in certain organs prior to ICIs treatment is an indicator of limited efficacy of ICIs remains elusive. Our results indicate that the presence of bone metastasis has a negative effect on the response to ICIs (both in terms of OS and PFS), and this observation aligns with recent studies . In contp = 0.07). Nevertheless, the association between sex and PFS was statistically significant only in the multivariate analysis, which may suggest that sex associates with other clinicopathological features included in the model. Thus, further studies may be required to assess the effect of sex in the response to ICIs treatment. Of note, some studies have suggested that females have higher levels of immune infiltration and others have described a larger benefit from the addition of chemotherapy to ICIs in women [Interestingly, females had statistically significant extended PFS compared to males, and although the impact on OS did not reach statistical significance, it was nearly significant  was the appearance of irAEs. Conversely, bone metastasis, and higher levels of LDH and ECOG performance status, were negative indicators of response to ICIs (both in PFS and OS). Our study also indicated strong interactions existed between some features. Thus, we devised a compendium of features  with additive prognostic value; however, a validation in a prospective cohort is required.


Recent discovery of the gene editing system - CRISPR  associated proteins (Cas), has resulted in its widespread use for improved understanding of a variety of biological systems. Cas13, a lesser studied Cas protein, has been repurposed to allow for efficient and precise editing of RNA molecules. The Cas13 system utilizes base complementarity between a crRNA/sgRNA (crispr RNA or single guide RNA) and a target RNA transcript, to preferentially bind to only the target transcript. Unlike targeting the upstream regulatory regions of protein coding genes on the genome, the transcriptome is significantly more redundant, leading to many transcripts having wide stretches of identical nucleotide sequences. Transcripts also exhibit complex three-dimensional structures and interact with an array of RBPs (RNA Binding Proteins), both of which may impact the effectiveness of transcript depletion of target sequences. However, our understanding of the features and corresponding methods which can predict whether a specific sgRNA will effectively knockdown a transcript is very limited.Here we present a novel machine learning and computational tool, CASowary, to predict the efficacy of a sgRNA. We used publicly available RNA knockdown data from Cas13 characterization experiments for 555 sgRNAs targeting the transcriptome in HEK293 cells, in conjunction with transcriptome-wide protein occupancy information. Our model utilizes a Decision Tree architecture with a set of 112 sequence and target availability features, to classify sgRNA efficacy into one of four classes, based upon expected level of target transcript knockdown. After accounting for noise in the training data set, the noise-normalized accuracy exceeds 70%. Additionally, highly effective sgRNA predictions have been experimentally validated using an independent RNA targeting Cas system – CIRTS, confirming the robustness and reproducibility of our model’s sgRNA predictions. Utilizing transcriptome wide protein occupancy map generated using POP-seq in HeLa cells against publicly available protein-RNA interaction map in Hek293 cells, we show that CASowary can predict high quality guides for numerous transcripts in a cell line specific manner.Application of CASowary to whole transcriptomes should enable rapid deployment of CRISPR/Cas13 systems, facilitating the development of therapeutic interventions linked with aberrations in RNA regulatory processes.The online version contains supplementary material available at 10.1186/s12864-022-08366-2. Gene editing technologies have played an increasingly important role in numerous life science domains in the recent years, especially in the fields of biology, biotechnology, and medicine . At the One such class of protein, Cas13, has been modified to directly edit RNA transcripts . Much liWhile the Cas13 system does offer some distinct advantages over the Cas9 system, it also poses some unique challenges. First and foremost, most of the transcriptome remains unknown, owing to poor understanding of various post transcriptional processes. RNA molecules can also adopt a variety of complex three-dimensional structures through networks of inter/intramolecular interactions. This irregular complex structure acts to the number of stretches available for complementary base pairing. Therefore, a tool to predict the efficacy of a given sgRNA is desirable.To that end, CASowary was developed as a novel approach for sgRNA efficacy prediction , 7. Althp-values from Kruskal Wallis test less than 0.05 were correlated with nucleotides that were over or under-represented at a particular location  of HEK293 cells from Schueler et al., SRR1330461 and SRR1330462 . Reads wIn addition to the k-mer composition and occupancy features, a variety of other features were also included. These include guide spacer percent composition for each nucleic acid, guide location along the length of the transcript, with 0 at the 5` end and 1 at the 3` end, and the observed number of complementary sequences in the reference transcriptome obtained from tophat alignment. A previous study  has showThe occupancy and composition features were then combined with several sets of k-mer features , and random forest Gini) and tested using a variety of machine learning algorithms. Each framework was evaluated based on their ability to accurately classify guides into one of four classes (0–3), based upon the quartile of transcript expression. This was tested by utilizing two different methods of cross-validation: 3-fold and 5-fold. For the 3-fold cross-validation, the experimental replicates were divided into separate folds, with two replicates serving as the testing data, and the other serving as an independent data set. For the 5-fold cross-validation the data from all 3 replicates were randomized, with 80% selected as training data and 20% selected for testing. The average values of the three different 3-fold experiments are presented in Table i = xj and yi ≠ yj, divided by the size of the set , and subtracting that value from 1 . The total model accuracy was then divided by the noise-normalized maximum to create the noise-normalized accuracy value.Due to the experimental noise native to the data source methodology, a significant amount of the experimental replicates for a specific guide differed significantly in transcript expression, often by more than 25%. This discordance in the training data lead to the model receiving different labels for the same set of training features, imposing a hard cap to the model’s cross-validation performance. To account for this, the models were evaluated based upon noise-normalized accuracy. The noise-normalized maximum was calculated by counting the number of occurrences where one experimental replicate differed in transcript expression quartile, with another replicate of the same experiment. Put more formally by, computing the size of the set of tuples  such that xOnce the optimal model architecture and feature set was determined, the importance of each feature was studied. To this end, the model was evaluated using 5-fold cross-validation 100 times, to establish a background. A single feature was removed from the model, and the model was evaluated another 100 times. The difference in model performance between the mean model accuracy and the background was taken to be the result of the removed feature Fig. D.Briefly, a total of 20 million cells were subjected to three variants of POP-seq including UV crosslinking, Formaldehyde crosslinking and No-crosslinking approaches . Cells RNA purity and concentration were assessed at each step using Nanodrop, based on the absorbance ratio 260/280 > 2. RNA integrity was evaluated using Agilent 2100 Bioanalyser system. Atleast 50 ng of r-RNA depleted RNA was used to generate sequencing libraries using the True-seq small RNA library prep kit (Illumina). All libraries were barcoded and sequenced in parallel on a Next-seq platform for 400 million reads to obtain 75 bp single end reads.CASowary takes a list of gene names  curve for the model was created Fig. . CalculaTo confirm the accuracy and robustness of the model, we conducted a series of characterization experiments using an orthogonal RNA-targeting system, CIRTS (CRISPR-Cas-inspired RNA targeting system) , 33. NumDuring the development of CASowary, we observed that specific classes of guides exhibited preferential patterns across the length of the target transcript. To confirm this trend, a comprehensive analysis of the predictions for a random assortment of 5000 gene transcripts was performed, resulting in 12.7 million mapped guides. All guides of a specific class were then grouped and plotted against their corresponding location in the transcript, from 5` to 3` direction, by normalizing the length to understand positional preferences for various classes of guides. This analysis revealed that the majority of the guides were predicted to be inefficient, either categorized as Highly Inefficient or Inefficient (90.7%)  among the computational predictions  to map protein-RNA interactions on a transcriptome wide scale . ProteinThe reads from the POP-seq experiment for HeLa cells, corresponding to transcriptomic regions interacting with proteins, were run through the computational pipeline as described in methods .CASowary is written in Python, requiring 3.6.8 or above, with some dependencies on Python 2.7.16. Source code for CASowary is available for free for academic use under GitHub  used in this study. This forms the basic input for the tool.Additional file 4. List of Ensembl gene IDs, Ensembl transcript IDs, common gene name (symbol), chromosome number, gene start position, gene end position, strand, length of the transcript, and the transcript sequence used in this study.Additional file 5 Tab delimited file containing the k-mer, the position of the k-mer in the guide, and the associated p-value for that k-mer.Additional file 6. Tab delimited file containing the training data for the model. The header contains the names for each of the features used.Additional file 7. A peak file generated using macs2 software on the aligned POP-seq data for HeLa cell line using hg38_transcriptome.fasta (Additional File Additional file 8.