Obtaining valuable clues for noncoding RNA (ribonucleic acid) subsequences remains a significant challenge, acknowledging that most of the human genome transcribes into noncoding RNA parts related to unknown biological operations. Capturing these clues relies on accurate “base pairing” prediction, also known as “RNA secondary structure prediction”. As COVID-19 is considered a severe global threat, the single-stranded SARS-CoV-2 virus reveals the importance of establishing an efficient RNA analysis toolkit. This work aimed to contribute to that by introducing a novel system committed to predicting RNA secondary structure patterns  that leverage syntactic pattern-recognition strategies. Having focused on the pseudoknot predictions, we formalized the secondary structure prediction of the RNA to be primarily a parsing and, secondly, an optimization problem. The proposed methodology addresses the problem of predicting pseudoknots of the first order (H-type). We introduce a context-free grammar (CFG) that affords enough expression power to recognize potential pseudoknot pattern. In addition, an alternative methodology of detecting possible pseudoknots is also implemented as well, using a brute-force algorithm. Any input sequence may highlight multiple potential folding patterns requiring a strict methodology to determine the single biologically realistic one. We conscripted a novel heuristic over the widely accepted notion of free-energy minimization to tackle such ambiguity in a performant way by utilizing each pattern’s context to unveil the most prominent pseudoknot pattern. The overall process features polynomial-time complexity, while its parallel implementation enhances the end performance, as proportional to the deployed hardware. The proposed methodology does succeed in predicting the core stems of any RNA pseudoknot of the test dataset by performing a 76.4% recall ratio. The methodology achieved a F1-score equal to 0.774 and MCC equal 0.543 in discovering all the stems of an RNA sequence, outperforming the particular task. Measurements were taken using a dataset of 262 RNA sequences establishing a performance speed of 1.31, 3.45, and 7.76 compared to three well-known platforms. The implementation source code is publicly available under knotify github repo. The RNA molecule, being the intermediate representation of the information flowing from DNA to proteins, holds a crucial role in many biological processes. Recent studies reveal that its detailed structural analysis is of utmost importance. The RNA structure is often depicted by a 2-D representation of the base-pairing nucleotide  known as the “secondary structure”, which conduces to the more-complex construction 3-D representation, termed the tertiary structure. The substantial role of RNA in the expression of proteins, along with its contribution to the gene expression regulation, catalysis, and site recognition, requires the enlightenment of its territorial structure, which is associated with considerable biological functionalities.More specifically, non-coding RNAs (ncRNAs) are functional RNA molecules transcripted from DNA but not translated into proteins. The latter must not be misinterpreted as not enclosing important information or contributing to any biological operation. Current evidence implies that ncRNAs transcribe most of the genomes of mammals and other complex bions, to contradict the widespread assumption that proteins transcribe most genetic information. Their purpose is to fulfill diverse catalytic and structural functions, along with regulating gene expressions at the transcriptional and post-transcriptional level.The literature contains a considerable number of publications discussing the prediction of RNA secondary structure. The employed methodologies are mainly based on dynamic programming algorithms, thermodynamic models, stochastic methods, and syntactic pattern-recognition techniques. A thorough analysis of the related work is presented in The article is organized at the following sections. In Non-coding RNAs (ncRNAs) are functional RNA molecules that are transcripted from DNA but not translated into proteins. This is not to say that ncRNAs do not provide knowledge or serve a purpose. Although it has been generally assumed that proteins transcribe most genetic information, recent evidence suggests that ncRNAs transcribe most of the genomes of mammals and other complex bions. Their purpose is to fulfill diverse catalytic and structural functions and regulate gene expressions at the transcriptional and post-transcriptional level.RNA is the cornerstone of various biological processes; it carries genetic information that is encoded into four distinct nitrogenous bases, i.e., adenine (A), cytosine (C), guanine (G), and uracil (U). As a messenger , it actsContrary to DNA, RNA features a single-stranded molecule resulting in a solid inclination of its bases to interact in two principal ways, either perpendicular to their planes (stacking) or hydrogen-bonded within the base planes (pairing). Those interactions form base pairs via hydrogen bonds between the corresponding nucleotide, i.e., the standard set of RNA base-pairs  known as Watson–Crick base-pairs  and the According to the literature, there is a strong correlation between the structure of a RNA molecule and its function ,11,12 toTurnip Yellow Mosaic virus  ← EMPTY_SET  endforfunction EARLEY_PARSER  INITIALIZE(input_string)  n ← LENGTH(input_string)Start → •S, 0), Sets[0])  ADD_TO_SET((  for i ← from 0 to n    for each state in Sets[i]      if (state is not completed)        if (RIGHT_TO_DOT(state) is a nonterminal)          PREDICTOR        else          SCANNER        endif      else        COMPLETER      endif    endfor  endfor  return Setsα• Cβ, j), i, grammar)function PREDICTOR((B → δ) in GRAMMAR_RULES  for each , Sets[i])    ADD_STATE_TO_SET, i, input_string)function SCANNER((B →   if (a is input_string[i])γ a •δ, j), Sets[i+1])    ADD_STATE_TO_SET, i)function COMPLETER((A → γ• A β), j) in Sets[x]  for each , Sets[i])    ADD_STATE_TO_SET RNA sequence is parsed using a CFG parser in order all trees that include a pseudoknot to be produced; (ii) all derived trees are then traversed to identify additional base pairs around the pseudoknot; and (iii) the optimal tree is selected via the criteria of minimum energy and the maximum number of base pairs of the pseudoknot. These three main tasks of the proposed methodology see  are thorAs exhibited in The proposed methodology of detecting pseudoknots in sequences of nitrogenous bases representing RNA rests on syntactic-pattern-recognition techniques and specifically on an efficient CFG parser. Consequently, it is vital to select the right primitive patterns. In the case of RNA recognition, the most-typical option is to represent the nitrogenous bases adenine, cytosine, guanine, and uracil as single characters “A”, “C”, “G”, and “U”, respectively. These characters in sequence constitute an RNA representation. Hence, in our case, where a grammar parser is proposed to recognize pseudoknots in RNA, the proposed grammar vocabulary contains only the four terminal symbols T = {“A”, “C”, “G”, “U”}, with each one representing a distinct base: adenine, cytosine, guanine, and uracil, respectively. Therefore, every RNA sequence may linguistically be represented as a string containing the terminal symbols, e.g., UAGGC or AUGGCCGUACG.The task to syntactically recognize a given pattern may actually be converted into using an appropriate pattern grammar, in order to parse the linguistic representation of the original patterns. The design of the pattern grammar may have a significant impact on the recognition’s result. Therefore, the formation of the CFG to be used is an important subtask in implementation having as the underlying model syntactic-pattern-recognition techniques. Hence, the design of an efficient grammar is indispensable in order to describe the syntax of the pseudoknot within any arbitrary RNA sequence. It is well known that CFGs are adequate to represent structural features. The core stems. The second column of ∅ is the empty set. Hence, L may produce strings of length greater than zero as A, UA, CCGGAU, etc.L is the non-terminal symbol that will produce sequences of bases forming the two interior loops of the pseudoknot, i.e., sequences of bases between C and U as well as between G and A. Non-terminal L may produce strings belonging to set D is the non-terminal symbol that will produce sequences of bases between the two crossing base pairs, i.e., between bases U and G in this example. Using non-terminal symbols K and N, L may recognize substrings of terminal symbols of length zero to two, i.e., hub repo .C …U G ……A. Then, rules 19, 18, and 22 were used to recognize the bases between C and U, i.e., C G C C U G ……A. After that, rules 24, 29, and 34 were used to recognize the empty string between the U G bases of the core stems. Finally, rules 16, 17, 17, 17, and 23 were used to recognize the bases between C and U, i.e., C G C C U G A U U U G A. The integration of this substring in the initial RNA sequence and the process of decorating the pseudoknot with additional base pairs is explained in The parse tree produced by the parsing of substring “C G C C U G A U U U G A” is shown in The proposed methodology parses all substrings, beginning with the one that starts with the first sequence symbol and features the minimum potential length. Iteratively, the length is extended by one symbol to include the entire initial RNA sequence finally. In the same iterative fashion, string starting points are augmented to exclude the previous set starting symbol. The parsing is over when the substring’s length to be parsed deteriorates further than a predefined threshold . This methodology, considering that Context-free grammar was selected with the view of augmenting it with attributes (forming an attribute grammar) in order to store probabilities and to manage to prune parse trees during the parse-tree construction process, in future work. In order to enhance the performance of the proposed system, an alternative implementation of the first task was proposed using a brute-force algorithm. This approach traverses the input string in order to spot all possible base pairs and then traverses all base pairs so as to identify couples of base pairs, which potentially form the core stems of a pseudoknot, i.e., consisting of two helical segments that are bound by two single-stranded sections or loops. The brute-force approach achieved a performance speed of 2.55 compared to the implementation that makes use of the context-free grammar at the first task. The speedup, though, comes at the cost of the overall extensibility that the grammar approach provides. In any case, both proposed implementations are faster than two well-known platforms . Performdecoration. Having detected the core stems U–A and C–G at positions 9 and 11 and 5 and 10, respectively, all bases in both pseudoknot loops,  and 11 to 15 (right loop)) were examined to identify against forming base pairs with bases outside the pseudoknot loops. Hence, base pairs belonging in the left loop were checked out if they may form base pairs with bases at positions 17 to 19, while bases belonging in the right loop were examined to match the ones at positions 1 to 4. In both the left and the right loops of the pseudoknot, the base pairs at positions 8–17, 7–18 and 4–11, and 3–12 were sequentially detected, respectively. Once the parse trees are generated following the methodology described in the previous subsection, all trees are traversed to decorate the pseudoknot with additional base pairs. The proposed system permits the user to optionally select the existence of base pairs U–G in the pseudoknot’s loops. At the same time, the existence of bulges or interior loops in the loops of the pseudoknot is part of our future work.According to the literature, multiple methodologies have been presented that tackle the problem of RNA base-pair prediction, with the prevalent ones being the (i) method of minimum free energy , which dThe proposed system employs a hybrid model of optimal tree selection, combining principles originating from the two most-prevalent techniques, i.e., the method of maximum pairing and that of MFE, to predict the pseudoknot pattern of any RNA secondary structure accurately yet in an efficient way. MFE is cost-effective in terms of performance; initially, all trees are sorted by the number of base pairs around the detected pseudoknot, and MFE applies only to the ones ranking the top score of the base-pairs count. This is a heuristic that outperforms the MFE original approach.H-In order to select the best candidate from the set of secondary structures, our method chooses the one with the minimum free energy. To carry out this important task, a module from HotKnots  was incotally in , and refAccording to the literature, the prediction of pseudoknots of any arbitrary RNA sequence is a NP-complete problem. On the one hand, free-energy-minimization algorithms proposed to provide pseudoknot predictions invoke dynamic programming to rank high regarding their computational cost, while their precision decreases proportionally to the length of the input sequence. On the other hand, existing heuristic approaches lack generalization capabilities when being tested under different datasets. In this setting, we introduced a novel hybrid strategy to pick the RNA sub-sequence that is the most-probable pseudoknot expression. According to The proposed implementation is hybrid itself as well. By invoking Python and C code routines, a performant, scalable yet easy-to-use, and extended software package was implemented. Python was used to provide high-level flexibility and out-of-the box features such as flexible parallelization capabilities, sub-process supervision, and file management, while C nailed the parsing task by minimizing the memory footprint and maximizing CPU utilization.The input sequence was sliced into multiple sub-sequences  the accuracy of the pseudoknot’s core stems prediction, (ii) the capability to predict the base pairs existing in the ground truth dot-bracket (confusion matrix), and (iii) the execution time.i, j) is equivalent to , , , and , as proposed in [posed in .The measurements divided per RNA sequences’ length are presented in The percentage of pseudoknot’s core stems exact prediction per platform is also shown in The percentage of pseudoknot’s core stems exact prediction per platform for all groups of length of RNA sequences is also shown in We benchmarked our framework on the sequences of To evaluate the overall performance, we focused on the precision, the MCC, and the F1-score. The latter is the harmonic mean of the PPV and the recall. Our methodology outperformed on average all methods in regards to precision metric having 0.784, while Knotty was 0.729, IPknot 0.718, Hotknots 0.706, and IHFold 0.608. Regardingthe F1-score and the MCC metrics, Knotty outperformed on average all methods with a F1-score equal to 0.807 and a MCC equal to 0.569. The proposed methodology had an accuracy very close to Knotty . In addition, HotKnots scored F1-score = 0.738 and MCC = 0.452, while IPknot  and IHFold  had lower accuracy on both the F1-score and the MCC.The above-mentioned results are also shown in In The last metric that was used in order to compare the proposed methodology with other platforms is that of execution time. In The execution time required per platform is also shown in In Total execution time required per platform for the four groups of different RNA sequences’ length is also shown in Recently, COVID-19 evolved into a severe global threat. This virus’ connection to RNA is one of the most-prominent artifacts justifying the requirement of concrete and accurate RNA-analysis toolkits. This study introduced an innovative methodology to detect H-type pseudoknots in RNA secondary structures accurately and performantly. The method is based on Early’s parser, which, given an RNA sequence in the form of a string, produces a space of all possible parse-trees, each one expressing a potential pseudoknot structure. The optimal tree is picked through a hybrid model combining pairing maximization and free-energy minimization for each context–tree pair. The evaluation of the proposed algorithm demonstrated its outperformance to the task of pseudoknot prediction, paving the way for our future work endeavours: (i) discovering even more complex patterns such as pseudoknots enclosing bulges or hairpins, (ii) building advanced searching algorithms leveraging common patterns of the secondary structure of RNA, and (iii) creating an open web platform to make our work accessible to all researchers. The work in ,91 may b


Galeocerdo cuvier, Carcharhinus plumbeus) and reef  sharks using > 1200 deployments of baited remote underwater stereo-video systems (stereo-BRUVs) across > 500 km of coastline. We found evidence for species-specific influences of habitat and fishing activities on the occurrence (probability of observation), abundance (MaxN) and behaviour of sharks . Although the presence of management zoning (No-take areas) made little difference to most species, C. amblyrhynchos were more common further from boat ramps . Time of arrival for all species was also influenced by distance to boat ramp, although patterns varied among species. Our results demonstrate the capacity for behavioural metrics to complement existing measures of occurrence and abundance in assessing the potential impact of human activities on shark populations.Quantifying the drivers of population size in reef sharks is critical for the development of appropriate conservation strategies. In north-west Australia, shark populations inhabit coral reefs that border growing centres of human population, industry, and tourism. However, we lack baseline data on reef sharks at large spatial scales (hundreds of km) that might enable managers to assess the status of shark populations in the face of future development in this region. Here, we examined the occurrence, abundance and behaviour of apex ( The coasts bordering these shallow habitats are often centres of human population and activities, notably tourism, recreational and commercial fishing, and industrial development . These anthropogenic pressures imperil the long-term persistence of elasmobranch populations, a problem compounded by the slow life histories of many species, increasing their vulnerability and hindering population recovery7.Sharks are top-order predators that play important roles in the shallow water ecosystems of reefs, embayments and estuaries throughout tropical and temperate oceans by transferring energy and predation risk across seascapes8. To accommodate the needs of various stakeholders, management planning typically includes areas where fishing is excluded (No-Take Areas) and other areas where some types of extractive activities are restricted. Several studies have used BRUVs as a tool to evaluate the efficacy of marine reserves on shark abundance in both tropical and temperate reefs10. The extent to which such strategies effectively protect highly mobile species such as sharks is a subject of debate given the size of their ranges relative to the area of protection . There is, however, evidence that the abundance and biomass of predatory fishes is higher inside marine reserves and negatively correlated with human activities, such as coastal development, human population size, and cultivated land12. For sharks, recent modelling studies combining data from acoustic telemetry and baited remote underwater video systems (BRUVs) across 36 countries suggest that the median width of No-Take Areas in coral reef systems (9.4 km) would need to be increased by five times and be accompanied by strict enforcement in order to sufficiently protect populations of common reef-associated shark species, such as whitetip (Triaenodon obesus), blacktip (Carcharhinus melanopterus), and grey (C. amblyrhynchos) reef sharks13. Such models imply that in many situations, current systems of spatial management are unlikely to offer adequate protection to larger, more mobile components of the predatory community of reef sharks 20. Although abundance is a widely used and standardized metric to assess the status of fish populations, behaviour is potentially a more sensitive measure of anthropogenic disturbance21. There is contrasting evidence surrounding the direction and magnitude of changes in behaviours of sharks driven by anthropogenic factors. For example, higher depredation rates by sharks on fishes caught by recreational anglers have been recorded in areas that are fished more regularly in Western Australia22. This suggests that recreational fishing may select for boldness or alter shark behaviour due to the availability of hooked fish as prey23. Conversely, evidence from New Caledonia suggested that grey reef sharks (C. amblyrhynchos) had increased wariness and were less likely to attempt to feed on bait in areas that were close to human population centres20. Determining the drivers of such differences in behaviour over reef-wide scales could enable the use of standardized behavioural metrics that might provide more comprehensive insights into the impacts of human activities on the shark assemblages of coral reefs.Besides management, a suite of other factors can drive the occurrence and abundance of sharks on coral reefs. These include the structural complexity of habitat24. This method can also provide an opportunity to examine the influence of human activities (or isolation from humans) on the behaviour of sharks recorded in the field of view of the cameras20. Recently, behavioural metrics such as time to arrival  and number of interactions with a bait bag have been used to examine interactions between predatory species and their prey29. These studies hypothesized that prey would take longer to arrive in the field of view of stereo-BRUVs in less structurally complex habitats that offer little refuge from predators27 or are in areas with exposure to sharks28. Additionally, rays are less likely to forage from the bait bag in areas with higher predator exposure29. This framework can be expanded to investigate the effect of proximity to human activities on the behaviour of sharks on coral reefs. For example, if human activities are perceived as threatening or disturbing, time to arrival by sharks at a BRUVs would increase and likelihood to feed from a bait bag would decrease. Conversely, if human activities provided a benefit (i.e. feeding opportunities) time to arrival would decrease and likelihood to feed would increase.Baited Remote Underwater Stereo-Video Systems (stereo-BRUVs) are commonly used to assess the abundance of sharks in coral reefshttps://www.abs.gov.au/census). Additionally, other parts of this north-west coast have become hubs for tourism and recreational fishing30. In 2017/2018, the boat-based recreational fishing catch across Western Australia included over 1.32 million individual finfish (49% released)30. Most of this fishing effort occurred in the West Coast bioregion surrounding Perth , but the Gascoyne Coast  had the second-highest level of recreational fishing effort (12%), followed by the North Coast (8%)30. Given the potential for these anthropogenic activities to adversely impact shark populations, it is important to develop regional benchmarks of the status of shark populations to ensure appropriate conservation and management strategies. This is given added impetus due to north-west Australia providing a refuge for species extirpated from parts of their former range, such as the Coral Triangle7.In the north-west of Western Australia, relatively intact populations of sharks inhabit coral reefs adjacent to infrastructure  that support mineral extraction  industries. The development of these facilities has been accompanied by growth in coastal centres of human populations and associated activities (32), as it facilitates the examination of patterns that may be driven by multiple correlated variables. We hypothesised that the occurrence and abundance of reef sharks would be higher further from anthropogenic activities and in areas of greater habitat complexity. Additionally, we hypothesized that sharks would arrive in the field of view of the stereo-BRUVs faster and be more likely to feed at increasing distances from human activities.Here, we use > 1200 deployments of stereo-BRUVs to investigate the occurrence, abundance, and behaviour  of sharks across more than 500 km of the north-west coast of Western Australia Fig. C. amblyrhynchos, T. obesus, C. melanopterus, G. cuvier, and C. plumbeus) per deployment ranged from 0 to 6 with a mean of 0.7 (SE 0.34) reef sharks  and 0.04 (SD 0.17) apex sharks (G. cuvier and C. plumbeus) recorded per 60 min deployment. In all deployments, the most abundant apex shark was G. cuvier (sum MaxN = 60) followed by C. plumbeus (sum MaxN = 44). In deployments in depths of < 25 m (n = 897), the most abundant reef shark species were C. amblyrhynchos (sum MaxN = 199), C. melanopterus (sum MaxN = 84), and T. obesus (sum MaxN = 62).A total of 889 (sum MaxN) sharks comprising 19 different species were observed across the 1273 stereo-BRUV deployments. The MaxN of the five most abundant sharks  for C. melanopterus, and 20 min 26 s (SD = 13 min 17 s) for T. obesus.For the five most abundant sharks across all 1273 BRUV deployments, the time of arrival per deployment ranged from 3 to 59 min (mean = 28 min 30 s SD = 4 min 42 s). For apex sharks, the mean time of arrival was 26 min 40 s (SD = 16 min 32 s). For reef sharks on deployments < 25 m depth, the mean time of arrival was 23 min 14 s (SD = 14 min 27 s) for The most parsimonious model for the occurrence of an apex shark included standard deviation of relief and depth Table , Fig. 2aC. amblyrhynchos, the most parsimonious model for occurrence included depth, reef cover, and status  resulted in shorter arrival times and higher likelihood of feeding for the most common species, C. amblyrhynchos. Although shorter distances to the nearest boat ramp resulted in shorter arrival times of C. melanopterus and T. obesus, these species did not feed frequently enough from the bait bag to model likelihood of feeding. Despite sampling over an extensive spatial range and recording a high number of sharks, our models explained a very small amount of variation , abundance (MaxN), and behaviour , the zoning status of the reef made little difference to apex sharks and 33), and the Rowley Shoals (0.65 reef sharks per hour24) and northern Great Barrier Reef (0.05 G. cuvier per hour7). However, our estimate of shark abundance was lower than remote reefs in New Caledonia (> 2.5 reef sharks per hour34), Cocos Keeling Islands (~ 2 C. amblyrhynchos per hour35), and Minerva Reef in Tonga (0.2 G. cuvier per hour7). Such differences in average numbers of sharks recorded by BRUVs might be due to a number of potential sources, such as variation in reef productivity among locations35, or events that attract and aggregate these predators in reef waters, such as turtle nesting36 in the case of apex predators, or spawning schools of fishes for reef sharks37. Repeated series of BRUVs sampling will be required to determine if these differences are fixed in nature or due to ephemeral events.In a global context, our observation of 0.7 reef sharks per hour and 0.04 apex sharks per hour was similar to other comparable protected reef systems, such as Fiji , with individuals sometimes travelling to Indonesia and the temperate waters in south-west AustraliaC. amblyrhynchos arrived faster to stereo-BRUVs and were more likely to feed on the bait bag at increasing distances from human activities. There are two potential (and non-exclusive) explanations for these relationships. Firstly, time to arrival at a BRUVs is highly correlated with abundance in both sharks and other predatory reef fishes43. Thus, higher abundances of C. amblyrhynchos at increasing distances from boat ramps might result in the observed decline in arrival times. Alternatively, human activities could be increasing the wariness, and therefore arrival times, of this species close to boat ramps, as was the case in New Caledonia20.Distance to a boat ramp influenced the occurrence, abundance, and behaviour of reef sharks. We found that C. amblrhynchos, C. melanopterus and T. obesus arrived sooner to the stereo-BRUVs closer to boat ramps. This result was not correlated with the abundance of these species. Although distance from human activities (e.g. human population density) or distance to boat ramp have been used in studies investigating patterns of shark abundance and behaviour (e.g.20), it is possible that these metrics are a coarse measure of human activity in north-west Australia. For example, distance to boat ramp may be correlated with another, unmeasured variable that is driving these patterns. This may be the case in our study, as C. melanopterus and T. obesus are more likely to inhabit reef lagoons and crests, which generally occur closer to boat ramps. For this reason, a more direct measure of human activities could provide an insight into the potential drivers of these patterns. For example, at Ningaloo there is evidence of behavioural links between reef sharks and the presence of recreational and charter fishers. From July 2015 to May 201622, surveyed 248 fishing boats at boat ramps on the Ningaloo Reef coast and 155 boats at ramps on Exmouth Gulf. They found that fishers reported sharks removing fish from lines on almost 40% of trips in both locations. Importantly, there was marked spatial variation in depredation, with higher rates occurring in areas where there was greater fishing pressure. This suggests that sharks may display learned behaviour in response to the opportunity to scavenge a relatively easy meal, but this behaviour may be restricted to locations where fishing was more common. An experimental approach would be required to investigate any associations between fishing and the behaviour of reef sharks (see23).In contrast to C. melanopterus were most likely to be observed in the shallowest deployments (0–4 m), and this species is known to inhabit complex habitats on reef flats within shallow lagoons46. C. amblyrhynchos were found at intermediate depths (4–9 m), whereas T. obesus were most likely to be observed in deeper deployments (16–25 m). This result for the latter species is unsurprising, given that it favours structurally complex reef edge and back reef habitats as they often consume prey that shelter in crevices and holes45. In addition to depth, reef cover was an important driver of occurrence of T. obesus and C. amblyrhynchos. Our finding that C. melanopterus was most abundant at intermediate levels of relief may be confounded by the shallow water depths in which it occurred, with the species more difficult to observe in complex reefs that could obscure parts of the field of view of the cameras. Time of arrival for all three species was quickest in areas of high structural complexity, which adds further support for suggestions that reef sharks prefer structurally complex habitat47. Such habitats may host a greater number and diversity of potential prey items as well as providing more refuge from the larger apex sharks that might prey on reef species49. If this is the case, environmental degradation and disturbance events that reduce the structural complexity of reef habitats may adversely affect reef sharks.Depth and habitat complexity (reef cover or standard deviation of relief) were important predictors of occurrence of all species of reef shark. These sharks were more likely to be observed in shallow depths (< 25 m), but within this range we found evidence of species-specific depth preferences. C. plumbeus and G. cuvier, the two most abundant species, we found a trend of higher probability of occurrence in deeper (> 25 m) waters, and in areas of less structurally complex habitat. This is expected given that G. cuvier often inhabit open ocean waters41 and, these apex sharks have little need for shelter from other predators (at least at adult sizes). Tagging studies have also demonstrated that tiger sharks frequently visit shallow sandflat environments, which are likely to be important foraging areas for these predators51. By not incorporating this key habitat into our sampling, we may have underestimated the abundance of these apex predators in north-west Australia. Furthermore, stereo-BRUVS are biased towards sampling smaller species of shark, compared to other methods, such as longline surveys, which select larger species due to catchability and size selectivity biases53. This may also contribute to the low number of larger sharks recorded in our study. Although the low number of these species recorded on stereo-BRUVs may trigger concerns regarding the impact of historical commercial fishing activities in this region, (shark fisheries in the north-west closed in 2009) recent evidence from > 25 years of scientific longline and dropline surveys found fluctuating but stable patterns in catch rates and body size of these species38. This similarity in catch and size patterns before and after the closure of commercial fishing activities suggests that these large-bodied, apex sharks have always been a rare part of the assemblage in the region.We recorded few apex sharks despite an intense sampling effort across a large spatial scale that included a broad variety of reef habitats. For 54, activity levels55, and depth distributions56 of sharks can alter at night. Despite this sampling bias, our study provided a comprehensive survey of patterns in the distribution and abundance of sharks across hundreds of kilometres of tropical and sub-tropical reef. Sampling at night using stereo-BRUVs is a challenge for any study as it generally necessitates the use of lights that might alter the behaviour of both prey and predator species in the vicinity of the stereo-BRUVs. One solution to this problem might be to use biologging to examine temporal variation in shark behaviour and fine-scale movement patterns. This approach has demonstrated distinct diel patterns of activity for six co-occurring species of sharks in the Gulf of Mexico and provided evidence of strong temporal partitioning of foraging times57. Such data could aid the interpretation of stereo-BRUVs data sets.Our study examined patterns in the abundance and behaviour of sharks during the day, but it is important to note that habitat use58. Alternatively, the current size of No-Take Areas may be inadequate to protect wider ranging sharks due to the large home ranges these species tend to occupy. Distinguishing among these alternatives will require detailed studies of the behaviour of both fishers and sharks in relation to spatial management strategies. We found species-specific drivers of reef shark occurrence, abundance and behaviour, which illustrates the value of pooling large data sets collected by multiple institutions for analysis. Our results also demonstrate the capacity for behavioural metrics to complement existing measures of abundance and occurrence in assessing habitat preferences and the potential impact of human activities on reef shark populations.Our results provide evidence that reef sharks have a strong affinity with structurally complex habitat with high levels of coral cover. We also found a small effect of distance from boat ramps and spatial patterns of management on the abundance and behaviour of reef sharks. Both results are difficult to interpret as distance from boat ramps is likely a very coarse measure of human disturbance in this region, whereas in terms of the impact of spatial management, our outcomes could be explained by a variety of equally plausible hypotheses. It might be that fishing pressure on sharks is too limited at this location to create distinct spatial patterns in shark abundance with No-Take Areas. Indeed, levels of commercial shark fishing in this region are lowSampling occurred on shallow reefs on the continental shelf of north-west Australia from the southern point of the Ningaloo Reef to the Dampier Archipelago, where hard reef is considered a major component of the benthic community Fig. . This arSurveys were completed between April 2014 and September 2015 using stereo-BRUVs deployed over 11 separate studies Table . A total70.Stereo-BRUVs consisted of two high-definition video cameras (either Canon Legria HFG25 or GoPro Hero 3+) attached to a galvanised steel bar framed in a trapezium prism. Cameras are inwardly converged at 7 degrees, which provided an overlapping field of view. This configuration allowed for accurate measures of size and distance. Further information on configuration and calibration is available inSardinops spp.), which were contained within a plastic-coated wire mesh basket, attached to a conduit rod and positioned 1.2 m in front of the cameras. Each system was deployed by boat and left to film remotely for at least 60 min on the seafloor before being retrieved and re-deployed elsewhere. Neighbouring deployments were separated by at least 400 m to reduce the likelihood of fish swimming between stereo-BRUVs59.Each stereo-BRUV was baited with approximately 1 kg of commercially purchased frozen crushed pilchards (http://www.seagis.com.au). In each video, any shark present in the field of view was identified to species level. The time (minutes) difference between the BRUV landing on the seafloor and the first individual of each species of shark entering into the field of view was also recorded and hereinafter referred to as “time of arrival”. Additionally, we recorded if each species fed from the bait bag , and was used to calculate likelihood fed. Relative abundance counts were obtained as the maximum number of individuals of a single shark species present in the field of view of each stereo-BRUV at one time (MaxN42). The stereo-configuration of the video systems allowed us to obtain accurate and precise measurements of shark length using EventMeasure. This stereo-video configuration also allowed for measures of distance, which was used to finalise measures of relative abundance by confirming whether individuals were within a sample boundary of 10 m from the cameras. Data checking and formatting of EventMeasure MaxN outputs used R language for statistical computing (R Core Team 2020) and R scripts provided in Langlois et al.59.Stereo-BRUVs were analysed using the program EventMeasure  hard corals, (2) macroalgae, (3) reef , (4) sand/rubble, (5) seagrass, (6) soft corals, (7) sponges, and (8) ascidians73. For every deployment the number of cells within each image containing the same habitat type were summed and divided by the total number of cells containing habitat. For simplicity we refer to these data as ‘percent cover’. When grid rectangles were positioned over open water they were classed as ‘no habitat’ and excluded from the overall percent cover and final statistical analyses. If grid rectangles contained habitat, an estimate of relief was also made and categorised from 0 to 5 based on the scheme in Wilson et al. (2007), providing the mean relief for each deployment.Measures of habitat and relief were obtained following protocols outlined inWater depth (m), GPS coordinate and management status (i.e. whether the stereo-BRUV was deployed in an area open to fishing or a No-Take Area) were recorded for each deployment. The latitude and longitude were also used to calculate the minimum Euclidean distance (m) to the nearest boat ramp which was used as a proxy of relative fishing effort.60) to explore the relative importance of habitat, management, and environmental variables in determining the abundance and time of arrival of sharks on stereo-BRUVs deployments. We considered five variables in these models: reef cover (continuous), depth , distance to closest boat ramp (continuous), standard deviation of relief (continuous), and status   and apex sharks  based on Roff et al. (2016).We used a generalised additive mixed modelling approach (GAMMsd) Table . Data exG. cuvier and C. plumbeus were later summed into an ‘apex shark’ category due to low numbers of sightings. Since the three species of reef sharks  were predominantly recorded at depths < 30 m, we subsetted our data to only include deployments at < 25 m depth (n = 897), to allow for the inclusion of depth as a continuous variable in these models.Models were initially run separately for each species, but FSSgam61) to investigate the relative importance of each variable in driving the abundance of sharks on stereo-BRUV deployments. Given that the occurrence of sharks on stereo-BRUV deployments was highly zero-inflated (~ 90% zeros), a hurdle model approach was used to model shark abundance. This class of model accounts for an excess of zeros through a two-step model structure62. The first step fits a binomial probability model to determine whether a zero or non-zero outcome occurs and the second step fits a separate model for positive outcomes. In this analysis, the occurrence of a shark (presence/absence) was modelled across all deployments using a binomial distribution. The next step only included deployments where sharks were present to model the abundance (MaxN > 0) of sharks using a Gamma distribution with a log link. The time of first arrival of each species of shark in the video from each stereo-BRUV deployment was modelled using a Tweedie distribution63 and the likelihood of feeding for each species was modelled using a binomial distribution . For each model, the mean latitude and the year of each stereo-BRUV campaign were included as random effects.We employed a full-subsets generalised additive mixed modelling approach  and AICc weight values (ω)65. To avoid issues with collinearity, only predictors with absolute Pearson correlations coefficient < 0.28 were included in a single candidate model. To ensure models remained ecologically interpretable, only models with up to three predictors were included in any one candidate model. To reduce overfitting and to further ensure that models remained ecologically interpretable, smoothing terms were fit using a cubic regression spline, with the ‘k’ argument limited to 3. The summed AICc weights were used to derive measures of variable importance of each predictor across all candidate models66, where higher summed values represent increased importance of that predictor to the response variable. Since models within two AICc units show weak support for one over the other, the most parsimonious model was the model that included the fewest variables and lowest estimated degrees of freedom within two units of the AICc65. The variables that were included in the most parsimonious models were plotted to visualise the shape and direction of the predictor variables and the response variables.Models were fitted using the gam function in the R package mgcvThe research was approved by the University of Western Australia ethics committee (RA/3/100/1317).Supplementary Information.


In recent years, vaccine development using ribonucleic acid (RNA) has become the most promising and studied approach to produce safe and effective new vaccines, not only for prophylaxis but also as a treatment. The use of messenger RNA (mRNA) as an immunogenic has several advantages to vaccine development compared to other platforms, such as lower coast, the absence of cell cultures, and the possibility to combine different targets. During the COVID-19 pandemic, the use of mRNA as a vaccine became more relevant; two out of the four most widely applied vaccines against COVID-19 in the world are based on this platform. However, even though it presents advantages for vaccine application, mRNA technology faces several pivotal challenges to improve mRNA stability, delivery, and the potential to generate the related protein needed to induce a humoral- and T-cell-mediated immune response. The application of mRNA to vaccine development emerged as a powerful tool to fight against cancer and non-infectious and infectious diseases, for example, and represents a relevant research field for future decades. Based on these advantages, this review emphasizes mRNA and self-amplifying RNA (saRNA) for vaccine development, mainly to fight against COVID-19, together with the challenges related to this approach. Vaccines are considered one of the most effective strategies to prevent, control, and eliminate infectious diseases ,2. The eBetacoronavirus genera. The SARS-CoV-2 viral genome has 29.8 kilobases, with a G+C content of less than 40%, and is composed of six large open reading frames (ORFs) common to coronaviruses and two untranslated regions (UTRs) at the 5′ and 3′ ends [SARS-CoV-2 is a single-chain positive-sense RNA virus of the  3′ ends . Four st 3′ ends . Among t 3′ ends ,18.Early sequencing of the SARS-CoV-2 genome allowed for the prompt determination of its sequence identity/similarity with the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and SARS-CoV (both previously responsible for concerning outbreaks), and routine sequencing has facilitated the identification of new mutated SARS-CoV-2 variants-of-concern . NumerouInternational efforts to end the current pandemic have been unprecedented in terms of resource allocation, scientific focus, and the pace of innovation . Given tRNA-based vaccines were among the first to emerge and have become prominent in national immunization programs. RNA vaccine technology builds on the central dogma of molecular biology, in which messenger RNA (mRNA) is the intermediate step between the translation of the encoding DNA and the production of its respective protein. It is a technology that enables the carriage of genetic information directly into the cell, allowing endogenous protein expression instead of administering protein (antigen) as an exogenous entity such as killed or defined subunit platforms . MoreoveAs with other platforms, the development of RNA-based vaccines involves antigen discovery and analysis of the nucleotide sequence that will be translated into the protein of interest. For RNA-based vaccines, screening of modified nucleotides can optimize expression, as can the selection of an appropriate method . VariousStudies that served as a basis for the development of synthetic RNA vaccines were reported from the end of the twentieth century and were motivated by the 1961 discovery of mRNA . An impoThe amount of protein (antigen) expressed is directly related to the content of mRNA that can enter the intracellular environment. The presence of well-defined mRNA in the cytosol allows the presentation of exogenous and endogenous antigens to occur and can provide activation of the immune system via different pathways ,52. HoweThese studies were of great importance in establishing benchmarks for further evaluation and, consequently, assisting in the process of optimizing these vaccines, providing essential safety and immunogenicity, and providing a basis for the production of RNA vaccines in accordance with good manufacturing practices ,64. In tRNA-based cancer vaccines have been designed to express tumor-associated antigens, resulting in the stimulation of T-cell-mediated immune responses . Acute mBefore studies in humans, in vitro and in vivo studies using DCs electroporated with mRNA assessed their ability to trigger potent immune responses against tumor antigens . Boczkow® vaccine platform , designed by CureVac, uses an mRNA complex with protamine and naked mRNA, where protamine assists in the process of inducing cellular immunity [The RNActiveimmunity . The plaimmunity  and CV-9immunity . Table 1In addition to the applications in cancer and non-infection diseases, it is important to mention that RNA-based vaccines also have a great potential to be applied to the treatment and prophylaxis of non-infectious diseases, such as autoimmune and allergic diseases ,92. ThesCompanies specializing in therapeutics with mRNA have sought solutions to a wide range of health conditions. When it comes to autoimmune disorders, previous studies have shown that mRNA therapy has a high potential application in the treatment of these diseases ,94,95. IWhen it comes to RNA-based vaccine applications for allergic diseases therapy, in contrast to cancer or autoimmune diseases applications, vaccination against allergy does not involve the administration of self-antigens . It is gAlthough mRNA vaccines were in the spotlight during the COVID-19 pandemic, it is important to note that much work has already been completed by using this technology platform in the treatment and prophylaxis of non-infectious diseases. Such studies demonstrate the high potential of RNA vaccine application.Zaire Ebolavirus, and coronavirus [In addition to the push for RNA-based vaccines to fight cancer, in recent years, the use of these platforms has gained prominence against infectious agents, especially against emerging infectious diseases such as those caused by the Zika virus, onavirus . In geneonavirus ,104. Unlonavirus .saRNA replicons are created by replacing the structural genes of, typically, an alphavirus (such as Semliki Forest virus (SFV), Sindbis virus (SINV), or Venezuelan equine encephalitis virus (VEEV) with the gene for the antigen of interest. It is important to note that the absence of endogenous viral structural genes in the replicons means that the production of infectious virions or virus-like vesicles in individuals after vaccination is negated, increasing the safety profile when compared to vaccine technologies such as attenuated virus . When deChlamydia trachomatis [Toxoplasma gondii [Plasmodium [Leishmania donovani [Plasmodium falciparum and showed that it induced antibody formation in in vitro assays and in a non-human primate challenge model. Maruggi et al. [Streptococci induced protective efficacy in mice through the induction of functional antibodies.RNA-based vaccines have been used to deliver bacterial and parasite genes but, except for vaccine candidates for chomatis , most ofa gondii , Plasmodasmodium , and Leidonovani ). Recentdonovani  developei et al.  reported® platform-based influenza A virus infection vaccines, demonstrating that the vaccines promoted balanced, long-lived, and protective immunity against infection with influenza A virus in both small animals (mice and ferrets) and large animals (pigs) [RNA-based vaccines have advanced further in the context of viral infections, most notably for SARS-CoV-2 but also including other respiratory viruses (SARS-CoV-1) , insect-s (pigs) . RNA vacs (pigs) ,127, andThe response to the COVID-19 pandemic has delivered many important milestones in vaccine development, especially for RNA-based platforms. Numerous vaccine candidates were proposed in record time, with the rapid-development process guided by the knowledge acquired from coronavirus targets that had already been used in successful vaccines for humans . Almost RNA-based vaccines were among the first candidates to enter preclinical and clinical development against COVID-19. According to the WHO, as of October 1, there were at least 194 preclinical studies of COVID-19 vaccine candidates, of which 24 included RNA-based vaccines . These sIn general, preclinical studies involving RNA-based vaccines have demonstrated that this technology can induce both humoral and cellular immune responses, with sufficient data to support advancement to clinical development phases ,146,147.Moderna’s mRNA-1273 was the first COVID-19 vaccine candidate to enter the clinical phase in the Western hemisphere. Its rapid development was made possible by the technological advances achieved through the earlier use of the company’s platform for vaccines against other viruses , as wellmRNA-1273 contains a nucleoside-modified mRNA that encodes the stabilized prefusion SARS-CoV-2 spike protein (S-2P) based on the originally identified Wuhan lineage virus (GenBank accession number MN908947.3) that is encapsulated in lipid nanoparticles. mRNA-1273 is administered intramuscularly in two doses scheduled 28 days apart . The phaGiven the rapid progression, the long-term safety and durability of the humoral immune response elicited by mRNA-1273 are only now becoming clear. Available data demonstrate that circulating neutralizing and binding antibody titers at day 119 after the first vaccination (90 days after the second vaccination) are still at concentrations capable of providing protection in participants of different ages . In the Although the phase 3 trial of mRNA-1273 included patients from several risk groups for developing severe COVID-19, such as diabetics, hypertensive individuals, individuals with chronic lung disease, liver disease, significant heart disease, people with HIV, and people with severe obesity, other conditions, such as patients with chronic kidney disease, were not evaluated . Thus, BWith an immediate USD 400 million awarded in grants , Pfizer Data from Sahin et al.  suggest The high efficacy demonstrated in the phase 3 trial of BNT162b2 supported its eagerly awaited application for emergency use authorization (EUA). On 2 December 2020, UK regulators granted EUA to BNT162b2, making it the world’s first approved COVID-19 vaccine . Nine daIn addition to being the first vaccine approved within the context of the pandemic of COVID-19, BNT162b2 was the first vaccine to be licensed for use in adolescents between the ages of 12 and 15 in countries such as the United States , Canada ® [CVnCoV, the COVID-19 vaccine candidate developed by the German company CureVac, is based on mRNA technology capable of encoding the prefusion-stabilized form of the full-length S protein of the Wuhan lineage virus (GenBank accession number YP_009724390.1) and formulated on the LNP-formulated RNActive® . It is i® ,199. The® . The pha® ,148. The® . Prelimi® , almost The lower performance of CVnCoV relative to mRNA-1273 and BNT162b2, which use the same technological development platform, was speculatively attributed to variants-of-concern found in the countries where the study was conducted  ,202. HowThe first RNA vaccine approved for clinical trials in China was ARCoV (CN111333704), a vaccine developed by the People’s Liberation Army (PLA) Academy of Military Sciences in collaboration with Suzhou Abogen Biosciences and Walvax Biotechnology Co. ARCoV is a lipid-nanoparticle-encapsulated mRNA vaccine encoding the RBD domain of SARS-CoV-2 (Wuhan) S protein . Phase 1® (Lipid-Enabled and Unlocked Nucleomonomer-Agent-Modified RNA) delivery system. ARCT-021 carries a sequence that encodes alphavirus replicase and the full-length, unmodified S protein (Wuhan sequence) [Vaccines based on saRNA technology also rapidly emerged. Among them, ARCT-021 (LUNAR-COV19), developed by Arcturus Therapeutics  and Duke–NUS Medical School in Singapore, uses the STARR™ (Self-Transcribing and Replicating RNA) system in combination with the LUNARequence) . This syequence) . A diffeequence) . Phase 1equence) . These rWith funding support from the British Government, Imperial College London also used saRNA technology to encode the prefusion-stabilized SARS-CoV-2 S-glycoprotein (Wuhan sequence) along with RNA replicase from an alphavirus, encapsulated in a lipid nanoparticle . After preclinical results demonstrated that two doses of COVAC1 induced cellular and humoral responses , a phaseHDT Bio’s COVID vaccine program, HDT-301, pairs a saRNA with a lipid inorganic nanoparticle (LION) formulation. Preclinical studies have demonstrated that HDT-301 induces neutralizing antibodies as well as a Th1-mediated immune response in both mice  and non-human primates. The generated neutralizing antibodies persisted for at least 70 days post-vaccination at titers compared to convalescent human serum . FollowiSeveral analyses of both clinical trial data and samples have assessed the ability of various COVID-19 vaccines to protect or generate neutralizing antibodies against different variants-of-concern of SARS-CoV-2 ,217,218.The B.1.1.7 variant was demonstrated to be more infectious than the Wuhan strain, around 60%, and also more resistant to monoclonal antibodies targeting the N-terminal domain . HoweverIt is important to highlight that researchers believe the antibodies produced still might be sufficient to protect against SARS-CoV-2 infection, or at least against severe cases of COVID-19, since they can still neutralize the virus overall . Since RWithin a brief period between the disclosure of the genetic code of SARS-CoV-2 and the authorization for use by different regulatory agencies, a large amount of information on RNA-based vaccines has been made available, which allows for a better investigation of the characteristics and composition of each developed vaccine, as well as enabling one to assess how these factors may influence immunogenicity and, consequently, the resulting protection. Naked RNA cannot pass through the cell membrane and efficiently leak into the cytoplasm due to its intrinsic properties such as size, charge, and degradability ,232. TheThe development of an effective LNP platform for mRNA or saRNA delivery involves a crucial step, which is the choice of cationic or ionizable lipid. Considering the RNA vaccines developed against COVID-19, ionizable lipids were used by the vast majority of developers . This ch® platform is also biodegradable and has optimized efficiency for mRNA delivery [3O4) nanoparticles (SPIO), which can act as the stability intensifier. Preclinical trials have shown good efficacy of CNEs in delivering antigens against HIV, RSV, and cytomegalovirus and in inducing immune responses [The vaccines mRNA-1273 (Spikevax) and BNT162b2 have the molecules SM-102 and ALC-0315 as ionizable lipids, respectively, in their formulations . These ldelivery  due to tdelivery . The saRdelivery , developdelivery . In addidelivery . The HDTdelivery . Like LPdelivery . It is iesponses . A featuesponses .In addition to the delivery system, the engineering involved in the mRNA construction process is one of the critical points for an RNA vaccine to achieve an acceptable safety and efficacy profile. Optimization of the mRNA sequence to improve the immunogenic and safety profile has been one of the main challenges in developing new vaccines. This optimization has focused on the following approaches: increasing mRNA half-life to increase the duration of protein expression and protein levels, the optimization of poly-(A)-tail length, the modification of the 5′ and 3′ untranslated regions (UTRs) to adjust immunogenicity, capping strategies to prevent rapid mRNA degradation, and the incorporation of modified nucleotides within the coding sequence ,243,244.The combination of the delivery system with improved properties and the optimized mRNA should promote the initiation of the translation process of the target antigen in vivo. During previous outbreaks caused by other coronaviruses, the S protein has been considered as the main antigen for the development of vaccine candidates and, similarly, all mRNA vaccines against SARS-CoV-2 were developed to induce immune responses against the S protein or the receptor-binding domain . PreclinFurthermore, it is important to note that the definition of the components of a vaccine has a direct bearing on the possible costs of manufacturing and making the vaccine available. One of the most important advantages of the RNA platform over conventional vaccine technologies is that its manufacture is simpler, since it does not contain steps such as cell culture, which require more time and investment . MoreoveThe COVID-19 pandemic has quickly transitioned RNA vaccines from a promising platform to becoming a major tool for COVID-19 prevention and a return to normal daily routines. Following their FDA emergency use authorization (EUA), by March 2021, more than 170 million doses of RNA-based vaccines had been made available worldwide, representing 43% of the total vaccines produced . Within One of the main challenges associated with RNA vaccines is related to the maintenance of the immune response over time against SARS-CoV-2 through neutralizing antibody titers. In a study conducted in Israel with 4868 participants, it was observed that in the third month after administration of the second dose of the Comirnaty vaccine, IgG antibody levels decreased at a consistent rate; in the same period, the level of neutralizing antibodies decreased rapidly, with an average reduction of more than 70% from initial values . AnotherHowever, because new variants-of-concern usually present with mutations in the S protein gene that can reduce the affinity of neutralizing antibodies, another strategy under consideration is the use of variant-specific and/or multivalent vaccines. In this context, as discussed earlier, the manufacturing flexibility of RNA-based vaccines affords an advantage over other vaccine platforms. Moderna has adjusted its mRNA vaccine to match the Spike gene sequence of variant 501Y.V2 , and cli2 and consume more electricity compared to vaccines developed from other technologies, such as CoronaVac and Sputnik V. Thus, the development of thermostable RNA-based vaccines that do not require expensive equipment and special storage conditions and distribution chain is of importance. The use of thermostable lipid nanoparticles in the RNA system and freeze-dried techniques are considered the technological advancements that could achieve this goal [The countries where COVID-19 vaccines have been incorporated into the routine of the health system have had to prepare strategic planning related to their storage, transport, manipulation, stock control, and distribution, mainly because approved mRNA vaccines currently require special storage conditions ,273. Thehis goal ,278.Another important challenge is associated with the production of RNA vaccines. Biopharmaceutical companies are estimated to be able to produce up to 12 billion doses by 2021; however, to have an equitable distribution of doses among countries, especially considering the need for booster doses, this amount is not believed to be sufficient . HoweverAlthough the approval of the first RNA vaccine during the COVID-19 pandemic was a milestone, its uniqueness and rapid development led to public concerns about the safety of RNA-based vaccines . This skDespite being studied over the past few years and having initial studies conducted in the context of cancer vaccines ,241,287,In the context of COVID-19, it is important to highlight not only the rapid development and availability of mRNA vaccines but also their high efficacy. Thus far, clinical trials and the subsequent expansive use of COVID-19 vaccines demonstrate not only the safety but also the efficacy of the RNA vaccine platforms. As demonstrated in clinical studies, mRNA vaccines, particularly Pfizer’s and Moderna’s mRNA vaccines, have been shown to be highly safe and effective. However, it is important to mention that, even with high efficacy, such vaccines need to be applied in two doses, and the application of a booster dose (third dose) is already being considered for risk groups (the elderly and people with immunodeficiencies). A promising alternative to resolve this issue is the application of saRNA vaccines, which, thanks to their self-replicative capacity, have the potential to confer an immune and long-lasting response with just a single dose. However, clinical immunogenicity data for these vaccines are not yet available.It is important to highlight that many strategies need to be to evaluated when developing RNA-based vaccines. Among them are the delivery technologies applied to it since naked RNA cannot enter cells due to its intrinsic properties. Knowledge of the delivery platform composition is especially important since it impacts the formulation stability, the ability to induce an immune response, decreased reactogenicity, and the efficacy of RNA delivery. LNPs are the most used platform, and their composition provides a solid structure that protects RNA from degradation. It is also important to note that the components of a vaccine directly influence the planning and costs of manufacturing, key factors for making the immunizer available.Despite the rapid response capability and flexibility of RNA vaccine technology demonstrated as these vaccines have become central to efforts to contain SARS-CoV-2, tied to their high safety and efficacy, RNA-based vaccines face significant challenges, mostly related to the scale of production, supply chains, and long-term efficacy, the latter of which is accentuated with the emergence of new variants. Moreover, RNA-based vaccines still face skepticism and strengthening anti-vaccine movements. However, thanks to its versatility, RNA technology is changing the vaccine industry and providing hope that it may be used to generate candidates with the potential to protect against a wide variety of cancers and infectious diseases .


Non-invasive tumor diagnosis includes liquid biopsy withdrawn from extracellular and extratissue samples including human urine in which RNA-based markers can be measured by various means. RNA markers include short-chain RNA such as microRNA and long-chain linear and circular RNA. This study describes all steps between sample acquisition, sample stabilization, shipping, and the quantitative determination of RNA-based biomarkers by RT-qPCR that are related to non-coding and coding polymerase II transcripts including mRNA. We aim to provide a novel and thorough easy-to-perform description of all technical and logistics steps of urine RNA-based diagnostics.Body fluids in the context of cancer diagnosis are the primary source of liquid biopsy, i.e., biomarker detection that includes blood and serum, urine, and saliva. RNA represents a particular class of biomarkers because it is thought to monitor the current status of gene expression in humans, in organs, and if present, also in tumors. In case of bladder cancer, we developed a scheme that describes, in detail, all steps from the collection of urine samples from patients, stabilization of samples, their transportation, storage, and marker analysis by qPCR-based technology. We find that urine samples prepared according to this protocol show stability of RNA over more than 10 days at unchilled temperatures during shipping. A specific procedure of primer design and amplicon evaluation allows a specific assignment of PCR products to human genomics and transcriptomics data collections. In summary, we describe a technical option for the robust acquisition of urine samples and the quantitative detection of RNA-based tumor markers in case of bladder cancer patients. This protocol is for general use, and we describe that it works for any RNA-based tumor marker in urine of cancer patients. In the field of cancer diagnostics, non-invasive technologies are increasingly attractive for initial diagnosis of tumors and for therapy monitoring ,2,3. BodCell-free nucleic acids including cell-free RNA in urine may originate from cell necrosis, cell apoptosis, active secretion by healthy and by tumor cells of the urinary tract, and transport of circulating RNA from blood into urine . Even thOn the diagnostic clinical level, however, these issues are not dominant, whereas technical parameters directly influence the feasibility of using the composition of urine RNA as a source of strong diagnostic markers. In this article, we describe a series of relevant parameters for the diagnostic chain from sample acquisition to laboratory determination of tumor markers.In the following, we describe all steps from clinical sampling of urine, sample delivery, sample treatment, isolation of total RNA, synthesis of cDNA, primer design for qPCR, and qPCR . All tecIt is noteworthy that we aim to isolate total RNA, regardless of the sub-fraction in which it is contained. Initial studies on the distribution of RNA in sub-fractions of urine samples indicate that RNA can be found in cell pellets, sediments produced by various g-values, or in solution/supernatant. The amounts of RNA, however, varied substantially within different samples. Thus, in order to exclude influences by cell fractions, we used total urine without further steps, e.g., centrifugation. This is thought to give rise to the analysis of the complete set of urine RNAs.Urine samples were acquired from patients at hospitals or doctor’s offices where donors had been informed about the background and the diagnostic steps, and where they signed a written consent. Approximately 7 mL of urine were drawn up into a monovette, pre-filled with 3.54 g of guanidinium thiocyanate (GTC) . The guaOnce urine samples had been soaked into monovettes containing GTC, the RNA in solution seems to be relatively stable. However, to gain additional insight into the major parameters of RNA stability, we first measured the temperature dependency on the detectability of 18S rRNA for two individual donors. We chose 18S rRNA because this is the most abundant RNA species in urine samples and, thus, it allows a large dynamic range of amounts of RNA to be quantified. Fresh urine samples were dissolved in GTC in monovettes and kept at constant temperatures varying between 4 °C and 60 °C, which we feel, covers a temperature range that is realistic for shipping and storing samples . This teHowever, we wish to stress that this methodology has not been tested for shipping temperatures above 37 °C. Thus, for very warm countries or summer seasons we recommend to carefully consider or control shipping temperatures.The second most critical parameter related to RNA stability in urine samples seems to be related to the time period of shipment or storage at room temperature. In order to shed light on this factor, we shipped monovettes containing urine samples as a regular postal parcel, which took 4 days until arrival. In addition, we kept monovettes containing urine samples for a 19-days period at room temperature before the stabilization step . The conIn summary, the time period between sample acquisition and storage of samples at −80 °C does not seem to be related to a major loss of detectable amounts of RNA. A stability study was performed with 18S rRNA . In thisThe temperature during shipment seems to have a minor influence on RNA stability below 37 °C while the 60 °C values indicate degradation at higher temperatures . Under rAfter arrival of samples and before freezing them, the pH value was adjusted to 7.0 by addition of 500 μL of 1 M sodium acetate buffer pH 7.0 , and the addition of 167 μL of 3% N-lauroylsarcosine. This resulted in a total volume of 9 mL. After gentle mixing, samples were shock-frozen in liquid nitrogen and stored at −80 °C. For taking aliquots, e.g., 2.25 mL, samples were thawed at room temperature under mild shaking and 250 µL of 1 M HEPES buffer pH 7.0 was added. The final concentrations in the urine sample were 3 M GTC, 50 mM sodium acetate, 0.5% N-lauroylsarcosine, and 100 mM HEPES, pH 7.0.Regarding the storage temperature of −80 °C, it should be noted that samples were stored for many years. It turned out that the highest signal stability, i.e., RNA stability was achieved by storing at this temperature. We would like to emphasize that we mean ‘functional stability’ rather than ‘physical stability’, i.e., the read-out is signal strength in RT-qPCR tests. However, we are not aware of data describing physical RNA stability in fractions of urine including different extracellular vesicles and, in particular, not in the presence of GTC. More specific information on the storage temperature cannot be provided but we feel that the storage temperature gives rise to robust and reproducible marker data.Further, we usually froze urine samples at −80 °C after sub-division into aliquots such that aliquots were thawed only once for preparation of total RNA and freeze-and-thaw cycles were avoided.The origin of RNA in urine samples is thought to contain a number of sources including living or non-viable cells, cell surface-bound RNA ,19, nake7 copies) to urine samples after buffering with HEPES pH 7.0 and before the RNA isolation is started in the use of a commercial RNeasy Midi Kit.Spiking of urine samples with in vitro transcribed RNAs is a part of quality assurance. Here, we used a standard luciferase-derived in vitro transcript, which is added at defined amounts  Database. Here, we searched for annotated, non-redundant sequences for DNA, RNA, and proteins including a platform for sequence data with genetic and functional information.Subsequently, we used the RefSeq data to define a set of target RNA sequences and considered all known transcript variants (‘NM_XXXXX’). Further, we considered non-translated sense transcripts, antisense transcripts, and pseudogene-derived sequences (‘NR_XXXXX’) whereas we did not consider SNPs.m, length, GC content, potential of primer dimers, total length of amplicons, and specificity. The use of TaqMan probes and their design were included only in case of failure of Primer-Blast. This can be supported by tools provided by commercial suppliers of TaqMan probes .A selection of target-specific primers was derived from NCBI Primer-BLAST and Primer3 algorithms. In addition, we used BLAST and global alignment algorithms (‘user selected’). The tool ‘Primer3 version 4.0.0’ was used to consider and to analyze criteria including Tm 57–63 °C . Data bank for Homo sapiens, RefSeq mRNA (“NM”) or RefSeq RNA („NR“). As far as possible, all primer pairs should be specific for all transcript variants of a given locus  we search for a marker that increases during tumor development and a second marker that decreases during tumor development. The ratio of both has at least two conceptional advantages. Firstly, it is independent of the total amount of urine RNA to be analyzed. Thus, standardization is not necessary. Secondly, the ratio between the healthy state and the disease state seems to be able to indicate a larger dynamic range than single individual marker values.7 copies of luciferase RNA transcribed in vitro. RNA isolation was then performed using the Midiprep Kit  according to company instructions. For this, an equivalent volume of 70% ethanol and 25 µL of ß-mercaptoethanol was added to the 2.5 mL sample. 4 mL was added to the column. Subsequent steps were performed following the manufacturer’s instructions, including an on-column hydrolysis of genomic DNA by treatment with DNase I. RNA was eluted twice with 160 μL H2O, lyophilized, and resuspended in 16 µL of RNase-free water. Samples were stored at −80 °C.For isolation of urine RNA, a 2.25 mL aliquot of denatured and stabilized urine was thawed with gentle shaking, mixed with 0.25 mL of 1 M HEPES, pH 7.0, and spiked with 10Reverse transcription was performed using the SuperScript III First-Strand Synthesis Kit  in a total volume of 20 µL containing 7.5 µL RNA extract and 300 ng of random hexamer primer . For Non-RT control reactions, nuclease-free water was added instead of solutions of RNaseOut and reverse transcriptase.® 7900HT Sequence Detection System  with 50 °C for 120 s (UDG activation), 95 °C for 120 s (hot start), followed by 40 cycles consisting of 95 °C for 15 s, and 60 °C for 60 s. Melting curve analysis was performed. For the TaqMan system, TaqMan Universal Master Mix II, with uracil-N-glycosylase (UNG)  was used. The template volume was the same as for the SYBR Green system. The primer pair concentration and TaqMan probe concentration were 200 nM, and 250 nM, respectively. The thermocycler conditions were 50 °C for 120 s, 95 °C for 600 s, and 40 cycles consisting of 95 °C for 15 s and 60 °C for 60 s. Samples were measured in quadruplicates and negative controls without reverse transcriptase and RNaseOut (Non-RT) or without template (NTC) were included. Standard curves were obtained after amplification of 101 to 107 copies of purified standard plasmids. Data analysis was performed via the SDS 2.4.1 software .qPCR was performed using the SYBR Green and TaqMan Systems in a total reaction volume of 10 μL in 384-well plates. SYBR Green reactions were performed with SYBR Select Master Mix, with uracil-DNA glycosylase (UDG) . Template volume was 4 µL of 1:16 diluted cDNA or 4 µL of 1:160 diluted cDNA for detection of 18S rRNA. The concentration for each primer was 200 nM. Quantitative PCR was carried out in an ABI PRISMGene-specific primer sequences, amplicon length, cloned reference sequences, and TaqMan probes are listed in This study focuses on technical aspects of the acquisition, shipping, and analyses of urine and urine RNA, respectively. The data summarized here describe a standardized methodology for the search of non-invasive urine RNA-based tumor markers. Please note that this study does not describe validated RNA markers for BC. It rather describes the feasibility of this approach. This methodology has been applied in many studies describing RNA-based tumor makers, including microRNA and RNA polymerase II transcripts in human cells ,23,24,25In order to illustrate the usefulness of the protocols, we included qPCR-based results in the use of urine RNA samples in The examples of marker detection shown in However, completely different settings without isolating total RNA could be considered for optimization of the power of RNA-based markers. This might include the search for compartments that primarily contain specific RNA markers . For exaAlthough RNA is satisfactorily stabilized by GTC, its protection could conceivably be increased by analyzing the role of detergent and its concentration. Similarly, the influence of temperature peaks on amounts and integrity of RNA could be characterized with more detail in order to identify further improvements.The acquisition and shipping of urine samples from clinics and doctor’s offices can be organized such that monovettes, pre-filled with GTC, can be safely and stably stored at the place of sample collection, instructions for sampling are available and parcels can even be prepared. Since the shipping step seems to be established as well, we describe a robust procedure prior to storage of samples and laboratory analyses, where one is able to detect RNA markers at low copy numbers of equal to or less than 100 copies per qPCR reaction. This is supported by a detailed and defined scheme of primer design for PCR .It is conceivable that many kinds of RNA species and DNA species can be measured in a diagnostic setting by methodology based on this work. This may include long-chain RNA and short RNA strands, e.g., microRNA and circular RNA.


E. coli Rho. We find that different mechanisms previously proposed for each step co-exist, but apparently occur on various timescales and tend to lead to specific outcomes. Our results indicate that three kinetically distinct routes take place: (1) the catch-up mode leads first to RNA shearing for RNAP recycling on DNA, and (2) later to RNAP displacement for decomposition of the transcriptional complex; (3) the last termination usually follows the stand-by mode with displacing for decomposing. This three-route model would help reconcile current controversies on the mechanisms.Rho is a general transcription termination factor in bacteria, but many aspects of its mechanism of action are unclear. Diverse models have been proposed for the initial interaction between the RNA polymerase (RNAP) and Rho ; for the terminational release of the RNA transcript ; and for the post-terminational outcome (whether the RNAP dissociates or remains bound to the DNA). Here, we use single-molecule fluorescence assays to study those three steps in transcription termination mediated by  Rho is a general transcription termination factor in bacteria. Here, Song et al. use single-molecule fluorescence assays to provide evidence that Rho-mediated transcription termination can occur via three kinetically different routes. Bacterial ρ, participating in transcription termination1 and many others3, is an ATP-dependent RNA translocase4. ρ binds nascent RNA at rut (Rho utilization) sites using its primary RNA-binding surface in an open state and wraps the RNA with its secondary RNA-binding surface to transform into the active state4.Transcription termination is essential for precise expression and proper regulation of genes. In bacteria, intrinsic termination requires only rut site and catches up with EC that is pausing at a termination site according to the so-called kinetic-coupling5, RNA-dependent6, RNA-centric7, and tracking8 models.With respect to the pre-terminational modes regarding how ρ encounters RNA polymerase (RNAP) or elongation complex (EC) in order to mediate termination, widely accepted is the catch-up mechanism, in which ρ first binds nascent RNA at a rut site emerging out of RNAP according to the so-called RNAP-dependent6, EC-centric7, and allosteric9 models. This alternative pre-terminational mechanism has been supported by several biochemical11 and structural data12, although questioned by other biochemical data13.This classical mechanism for the pre-terminational step is challenged by the stand-by mechanism, in which ρ first binds RNAP of stable EC and stands by for binding an incipient RNA 14. The stand-by mode, on the other hand, generally assumes that RNA is released or EC is disassembled not by the motor action of ρ but by allosteric changes in EC conformation triggered by ρ12.For the RNA release, which defines termination of transcription, the catch-up mode generally assumes a critical role in ρ′s motor activity. The mechanical force exerted by ρ is expected to shear RNA off from RNA·DNA hybrid in the RNA shearing model or displace RNAP forward out of the ribonucleotide (NTP) incorporation site in the RNAP hyper-translocation model17. After releasing RNA at termination, RNAPs diffuse on DNA in upstream and downstream directions, change the moving direction, and even flip themselves on DNA, until reinitiating transcription on promoters or falling off DNA17. This post-terminational one-dimensional (1D) diffusion of RNA-free RNAP on DNA is named 1D recycling, shortened here as recycling, and the reinitiation by such 1D recycling RNAP is named 1D reinitiation.As to the post-terminational outcomes, recent single-molecule studies revealed that RNAPs mostly remain on DNA after RNA release at ρ-independent, intrinsic termination and are directly reused for reinitiation of transcription on the same DNA molecule17, it is unknown yet whether recycling, decomposing, or both result from ρ-dependent termination.Much less frequently at intrinsic termination, EC decomposes into the three essential components all at once with simultaneous or near-simultaneous dissociations of RNA and RNAP from DNA. This one-step disassembly of EC is called here decomposing for short. While recycling is much more frequent than decomposing from intrinsic terminationIn this study using single-molecule fluorescence measurements, we discover that ρ-dependent termination of a single terminator follows three different routes rather than a single path while characterizing the termination events of individual transcription complexes in three steps; pre-terminational setup, terminational release, and post-terminational outcome. The three routes each lead to a specific destination on a distinct timescale.Salmonella mgtA leader with a ρ-dependent terminator19  due to missing GTP, so active transcription complexes are labeled with two fluorescent dyes, Cy3 on RNA and Cy5 on DNA  are immobilized on polymer-coated quartz slides using biotin–streptavidin conjugation and extensively washed to remove all unimmobilized complexes. In single-molecule termination assays Fig. , the immVanishing of Cy3 spots after NTP + ρ injection indicates release of transcript RNA out of immobilized complexes resulting from transcription termination at the termination-associated pausing site (termination site) or from runoff transcription at the DNA downstream end following transcription readthrough at the termination site . PIFE occurs to cyanine (Cy) dyes when their local environment becomes more viscous by binding proteins to hinder the dye’s photoisomerization from fluorescent In this study, Cy3 PIFE occurs when the Cy3 labeled at the 5′ end of RNA remains proximal to RNAP in ISCs, and the PIFE decreases when the 5′ end moves away from RNAP as the RNA grows in length upon resumption of transcription elongation from ISCs. Individual complexes showing this pattern of Cy3 fluorescence changes have gone through active transcription and therefore are solely included in our data analysis.By contrast, Cy5 PIFE arises when the Cy5 labeled at the downstream end of DNA is approached by RNAP. Either transcribing RNAP with RNA after readthrough at the termination site or recycling RNAP without RNA after termination at the termination site can reach the downstream end to cause the PIFE. On the other hand, once RNAP falls off DNA, it readily diffuses away and seldom rebinds DNA even at the ends in this single-molecule assay.Real-time monitoring of Cy3-RNA and Cy5-DNA signals revealed three distinct patterns of their fluorescence changes Fig. . TranscrThe second pattern represents the termination resulting in RNAP recycling on DNA , as Cy5 PIFE starts as soon as Cy3 signal vanishes Fig. . Only RNThe third pattern reflects the termination resulting in EC decomposing , as Cy3 signal disappears but Cy5 PIFE never arises Fig. . RNAP re17. It can be followed by the second-round transcription for termination or readthrough and subsequent such events, but these cyclic events are not monitored in this assay as the reinitiated transcripts are not labeled with Cy3 after the ISC-washing step.The 1D reinitiation could occur by recycling RNAP after termination and subsequent backward diffusion to the promoter on the same DNA moleculeThis basic setup of single-molecule termination assay is called holistic assay to be distinguished from the two below-described assays that each measure only a certain discrete mode of termination. In a negative control experiment without ρ, termination efficiency (TE) drops to a background level, 6.3 ± 0.7% Fig. . This ρ-2+. Thus, raw TE is 57.4 ± 3.4%  than decomposing termination (199 s) or readthrough (198 s) as shown in Fig. 9.The holistic assay does not differentiate the catch-up and stand-by pre-terminational pathways. In order to solely monitor the termination that is mediated by ρ in the stand-by mode  rather than by ρ in the catch-up mode , we pre-incubated ISCs with ρ and washed away the unbound before resuming transcription with NTPs but without adding ρ Fig. . AlthougInterestingly, almost all stand-by termination events are followed by decomposing outcome  than readthrough (207 s) as shown in Fig. P297S mutant25, washed away the unbound, and resumed transcription by adding NTPs and wild-type ρ  happens much earlier than decomposing termination (189 s) or readthrough (177 s) as shown in Fig. While the catch-up assay’s experimental setup with pre-bound ρsay Fig.  in welcoE. coli ρ-dependent termination observed with mgtA terminator, we examined four additional ρ-dependent terminators, rho, ribB, trp t’, and λ tR1  are known to participate in stable EC along with ρ12. In order to examine how they influence the termination routes, we added them to ISCs in all three assays with mgtA terminator. Expectedly, the activity lifetime of stand-by ρ is longer with NusA/G than without them  catch-up → readthrough → runoff, (2) catch-up → termination → decomposing, (3) catch-up → termination → recycling, (4) stand-by → readthrough → runoff, and (5) stand-by → termination → decomposing. While the stand-by → termination → recycling path is not operating in any terminator, the operation of a single ρ-dependent terminator runs via the three routes starting with catch-up or stand-by ρ.When portions of the three termination routes in all termination events from each terminator were separately calculated Fig. , the catmgtA terminator with NusA/G were grouped together in a box plot with median and quartile values  is the earliest and especially earlier than the catch-up readthrough (route 1) (P = 0.001). Decomposing termination is observed later than readthrough by catch-up (P = 0.03) or stand-by ρ (P = 0.01).Next, the measured timings of recycling termination, decomposing termination, and readthrough events were compared among each other, while the five terminators without NusA/G and ues Fig. . AccordiThese chronological orders are in fact more evident when comparisons are made directly between termination and readthrough timings for each individual terminator Fig. . In the Furthermore, decomposing results later with stand-by ρ than catch-up ρ or almost at the same time in all terminators, when the decomposing termination timings by the two ρ modes are directly compared from each other in individual terminators as shown in Fig. 14, ρ pulls RNA to resolve RNA·DNA hybrid for terminational release of RNA and immediate or delayed dissociation of RNAP from DNA. In the RNAP hyper-translocation model14, by contrast, ρ pushes RNAP forward on DNA for the collapse of transcription bubble leading to RNA release with simultaneous or subsequent RNAP dissociation.Finally, we examined whether RNA shearing or RNAP hyper-translocation is utilized in ρ-dependent termination. In the RNA shearing modelmgtA terminator mutant AU100 where AU content of the RNA·DNA hybrid formed at the termination site is increased to 100% from the wild-type 44%  or ρ first binds RNAP and stands by for RNA emergence9 (stand-by mode). Contrary to the previous reports that only one pre-terminational mode is present, we discover that both catch-up and stand-by modes are used by a single terminator. Their proportions, however, vary in different terminators, raising interesting questions of how their proportions are determined and influence gene regulation.Mechanisms of ρ-dependent termination have long been studied but still remain elusive. A prevailing debate has been concerned with whether ρ first binds RNA and catches up with RNAP later17. Frequently with catch-up or stand-by ρ, RNA release and RNAP dissociation from DNA occur together, as RNAP displacing results only in EC decomposing. By contrast, less frequently with catch-up ρ, only RNA is released but RNAP is not concomitantly dissociated from DNA when RNA shearing results only in RNAP recycling on DNA, while this is much more frequent in intrinsic termination without ρ.We additionally discover that decomposing outcome is much more frequent than recycling from each of the five tested ρ-dependent terminators, as opposed to that recycling outcome is much more frequent than decomposing from intrinsic terminatorsOur kinetic analyses additionally reveal how these co-occurring mechanisms are chronologically arranged in the course of ρ-dependent termination Fig. . The choTranscriptional readthrough naturally synchronizes with the later termination, which is decomposing termination much more likely than recycling termination. However, decomposing termination completes even later than readthrough, regardless of whether it is mediated by catch-up or stand-by ρ Fig. . It is pA simple speculative course of ρ-dependent termination Fig.  could stThe catch-up and stand-by pre-terminational modes would follow separate paths on different timescales and could build disparate structures of termination-proficient complex favoring specific outcomes such as RNAP recycling on DNA and EC decomposing at once. We speculate that even for the same decomposing termination, the catch-up and stand-by ρ′s could induce dissimilar changes in a termination complex structure because their termination timings often differ much from each other Fig. .Most, if not all, previous models of ρ-dependent termination simulate with a single ρ molecule. However, it should not be ruled out that two ρ molecules participate side by side in termination and compete or collaborate with each other. Because the sums of stand-by and catch-up TEs are larger or smaller than the holistic assay measurements Fig. , one can17. However, the decomposing outcome is not absent in intrinsic termination requiring RNA hairpin formation, so one can hypothesize that the background termination results from infrequent decomposing of EC unstabilized without ρ or RNA hairpin, and that shearing RNA alone for recycling occurs actively rather than passively in both intrinsic and ρ-dependent terminations. Apparently, ρ plays the same role as the terminator RNA hairpin to mediate recycling termination and a different role to mediate decomposing termination.Incidentally, one can consider it odd that the background termination occurring without ρ results solely in the decomposing outcome, while ρ-independent, intrinsic termination results mostly in recycling3) possible stepwise combinations in the performance of a single terminator. The three routes apparently operate on individual timescales and lead to their specific outcomes. This three-route model  for 5 min. The complexes were then imaged under a homemade wide-field total-internal-reflection fluorescence microscope equipped with 532-nm green (Excelsior-532-50-CDRH) and 640-nm red (Excelsior-640c-35) lasers (Spectra-Physics) using an electron-multiplying charge-coupled camera . All experiments were performed at 37 °C with 1-s exposure time in alternating laser excitation mode40 and time resolution was 2 s. Softwares IDL 7.0 (ITT), MATLAB R2018a (MathWorks), and Origin 8.5 (OriginLab) were used for data analysis.Individual transcription complexes were immobilized to quartz microscope slides via biotin-streptavidin conjugation on the slide surfaces that were coated with polyethylene glycol (PEG) and biotin-PEG5000 (Laysan Bio) in 1:40 ratio2, 20 mM NaCl, and 1 mM dithiothreitol) for 20 min. Transcription was resumed with all four NTPs (200 μM each) and ρ (100 nM or varying) in a transcription resuming buffer . When needed, NusA (500 nM) plus NusG (500 nM) or a ρ mutant (100 nM) was added to the stalling buffer.ISCs were prepared by incubation of DNA, Cy3-labeled ApU , ATP, CTP , and RNAP holoenzyme (340 nM) in a transcription stalling buffer  and purified by using HiTrap IMAC HP affinity and Superdex 200 gel filtration35. NusG was expressed with a C-terminal His6 tag from a cloned plasmid pRM1160 in E. coli BL21(DE3) and purified by using HiTrap IMAC, HiTrap Q, and HiLoad Superdex 75 columns32.RNAP holoenzyme was either purchased from New England Biolab (M0551S) or custom-purified as previously describedE. coli RNAP holoenzyme (30 nM) and a template DNA (15 nM) with one of the five terminators were incubated in a transcription buffer  at 37 °C for 10 min. The incubation was continued with ρ at 0, 15, 30, or 60 nM and NusA/G each at 0 or 50 nM for 10 min, and then with 200 μM ATP, 200 μM GTP, 200 μM UTP, 0.025 μM CTP, and 0.05 μM [ɑ-32P]CTP for another 10 min. The transcription reaction was quenched by the addition of a 2× urea-denaturing gel loading buffer and analyzed on a 6%-polyacrylamide urea gel. While raw TE is the ratio of termination band intensity to the sum of termination and readthrough band intensities, ρ-dependent TEs are estimated by subtraction of the background TE measured without ρ from the raw TEs measured with ρ.2, 10 mM dithiothreitol, and 1 mM ATP, and by ligating them using T4 DNA ligase 2 (New England Biolabs). Homo-duplex DNAs were made by polymerase chain reactions (PCRs) using biotin-labeled forward and Cy5-labeled backward primers. Hetero-duplex DNAs were made by PCRs using biotin-labeled forward and unlabeled backward primers for wild-type DNAs, and using unlabeled forward and Cy5-labeled backward primers for mutant DNAs. Then, PCR products were annealed, and products with both biotin and Cy5 were used in experiments.Using DNA oligomers (Supplementary Table Further information on research design is available in the Supplementary InformationReporting SummaryPeer Review File