Cellular biology occurs through myriad interactions between diverse molecular components, many of which assemble in to specific complexes. Various techniques can provide a qualitative survey of which components are found in a given complex. However, quantitative analysis of the absolute number of molecules within a complex (known as stoichiometry) remains challenging. Here we provide a novel method that combines fluorescence microscopy and statistical modelling to derive accurate molecular counts. We have devised a system in which batches of a given biomolecule are differentially labelled with spectrally distinct fluorescent dyes (label A or B), and mixed such that B-labelled molecules are vastly outnumbered by those with label A. Complexes, containing this component, are then simply scored as either being positive or negative for label B. The frequency of positive complexes is directly related to the stoichiometry of interaction and molecular counts can be inferred by statistical modelling. We demonstrate this method using complexes of Adenovirus particles and monoclonal antibodies, achieving counts that are in excellent agreement with previous estimates. Beyond virology, this approach is readily transferable to other experimental systems and, therefore, provides a powerful tool for quantitative molecular biology. To successfully function, these components typically need to be assembled into specific complexes or clusters. For example, receptor signalling generally requires the co-location of various sensory, regulatory and stimulatory partners; the precise make-up of these assemblies can tune the nature of the signal and resultant physiological output. Molecular cell biology research has, thus far, largely focused on determining the identity of the components found in a given complex. However, it is becoming clear that the quantity of any given component is also vitally important. Quantifying the number of molecules, or stoichiometry, within an assembly can be used to understand its ultrastructure and, ultimately, to create complete models of entire macromolecular assemblies, as has been demonstrated for HIV capsids and the neurological synapse8. Nonetheless, these approaches typically require detailed a priori knowledge of the experimental system  and/or a well understood reference sample with which to calibrate the measurement10. These steps need to be performed independently for each different experimental model and microscope set up; this creates a high barrier to implementation and can make these methods vulnerable to experimental variation and artefacts.There are various approaches to investigate the number of molecules within a given complex; for example calibrated biochemical analysis or cryo-electron microscopy (cryo-EM). However, such methods pose practical and/or technological barriers and, by their very nature, obscure heterogeneity within the sample. Single molecule localisation microscopy (SMLM) modalities, such as STORM and PALM, are potentially powerful techniques for countinga priori understanding of the experimental system.Here we outline an alternative, and potentially complementary, approach that combines (non-SMLM) fluorescent microscopy and statistical modelling to extract estimates of molecular numbers within a complex. The method requires differential binary labelling of a constituent (i.e. separate batches of a protein of interest are labelled with fluorescent dye A or B); by appropriate mixing of the differentially labelled batches, assembled molecular complexes can be simply scored as being positive or negative for a given label. The frequency of positive complexes is then analysed by statistical modelling to extract estimates of stoichiometry. This approach is simple and requires minimal calibration or 11. The major AdV capsid protein is hexon; this assembles into trimeric subunits, that are hexagonal in shape, which in turn arrange to form an icosahedron with 20 triangular faces  is a non-enveloped DNA virus; its genome is enclosed within a proteinous shell, called a capsid13. Nonetheless, anti-hexon antibodies can prevent virus infection by recruiting the intracellular antibody-sensor TRIM21, which targets the virus for degradation and activates cell-intrinsic immune responses15. Anti-hexon monoclonal antibody 9C12 inhibits AdV infection via this mechanism and is used as a prototypical system to investigate TRIM21. The stoichiometries of antibody and TRIM21 recruitment to incoming virus particles remain unclear and are likely to be a determinant of the resulting cellular response.Antibodies (Ab) that bind sites such as the spike can directly neutralise AdV by blocking receptor interactions, therefore preventing the virus particle from entering the cell. However, antibodies targeting the hexon protein (which makes up the majority of the capsid) do not necessarily interfere with the mechanics of virus entry17; this maximum is likely determined by the limits to antibody binding and packing enforced by the geometry of the particle. We have applied our counting method to the AdV-9C12 complex and generated estimates that are in good agreement with these previous studies, therefore validating our approach.Previous studies, using alternative techniques, have provided estimates of the stoichiometry of AdV-9C12 complexes. Each AdV particle possesses 720 identical hexon proteins, each of these represents a potential binding site for 9C12. However, the hexon subunits are assembled as trimers, and are arranged in a specific geometry (as described above). Moreover, antibodies are bivalent, therefore each 9C12 molecule has two hexon binding pockets. Consequently, it is highly unlikely that each hexon molecule will be occupied by a single 9C12 molecule (i.e. 720 antibodies per virus particle). Analysis by cryo-EM, immuno-gold EM staining and calibrated fluorescence measurements suggest a true maximum stoichiometry of 100-200 antibodies per particleWe used differential binary labelling and statistical modelling to extract estimates of stoichiometry, our strategy is outlined in Fig. A or AbB). Mixing of the differentially labelled antibody batches at appropriate proportions results in only a minority of virus particles receiving a particular fluorescent dye (B in the example cartoon). Therefore, when imaged, we detect three distinct fluorescent signals: each virus particle can be identified by its reference dye (green in the cartoon example), every virus particle has also received antibodies with dye A (magenta), however, very few particles are positive for dye B (blue) and can be scored as positive or negative in a binary fashion. The frequency of virus particles that are positive for AbB is a function of the A:B mixing proportion and the stoichiometry of Ab:virus interaction; this relationship between the data and the hidden truth can be modelled.In our method Fig. B, both cK, the total number of (AbA and AbB) antibodies bound to a virus, can be modelled as a binomial random variablep is the probability of an antibody binding to a particular binding site of the virus. If p are known, then the expected number of antibodies bound to a single virus is simply p cannot be expressed easily since it depends not only on the antibody concentration used but also the composition of the virus particle and the geometry of interaction, which can be difficult to obtain. To extrapolate an antibody count it is, therefore, necessary to estimate both, p.Consider a single virus to be capable of binding B molecule  to describe mentclass2pt{minimm experiments to be conducted at varying antibody concentrations m sets of virus state observations m independent models, each estimating j. While estimating concentration-specific antibody binding probabilities is desired, inferring multiple In most applications, more than one experiment is performed; consider 18. No prior knowledge is incorporated by imposing a beta distribution Beta on all https://github.com/sophiamersmann/molecular-counting, the raw data used for molecular counting can be found here: 10.5281/zenodo.3955142.Such a general model contains a single likelihood entclass1pt{minimaB molecules (V). Formally, these are not required to comply with specific bounds. However, certain configurations of an experimental setup are not expected to yield data that lead to a sensible model. Using only ’B’ labelled antibodies (AbB) in an experiment  and the proportion of AbB molecules , then the proposed model failed to produce a reasonable estimate of p for most underlying true values; higher number of viruses seemed to compensate this effect to some extent ; for each spot we resolved a single maxima of fluorescence that was Successful implementation of our strategy requires sensitive and unambiguous measurements of individual virus-antibody complexes. We achieved this by immobilising AdV particles onto coverslips for analysis by total internal reflection fluorescence microscopy . Prior to immobilisation, purified AdV particles were directly labelled with Alexa Fluor 488, this provided a reference label by which AdV particles could be unambiguously identified. When observed by TIRF-M Fig. Bi AdV488ter Fig. A.647), and imaged by TIRF-M. Each AdV particle was positive for antibody, indicating the assembly of virus-antibody complexes  or 9C12Biotin (AbB) . We then monitored the 9C12647 (AbA) fluorescence signal under each condition. As the proportion of 9C12647 (AbA) dropped we measured a stepwise reduction in fluorescence signal ; indicating a fair competition in binding between AbA and AbB.To achieve differential labelling a second batch of 9C12 was directly conjugated with biotin; this served as the AbB within individual virus-antibody complexes. To explore this we incubated immobilised AdV particles with 5647 (AbA) spiked with 1% 9C12Biotin (AbB) (i.e. fl = 0.01). Molecules of 9C12Biotin were detected using streptavidin (an ultra-high affinity biotin binding protein) conjugated to a quantum dot (QDot655). The photostability of quantum dots permits signal accumulation over prolonged exposure times22, therefore increasing the sensitivity of detection. Analysis by TIRF-M revealed that whilst every particle was positive for 9C12647 (AbA) only a subset possessed 9C12Biotin-QDot655 (AbB) signal  . These data are consistent with the assembly of virus-antibody complexes in which the vast majority of antibody molecules are from batch A (9C12647), but a subset of complexes contain Biotin); the proportion of AbB positive particles will serve as the output data for statistical modelling.As depicted in Fig. mentclass2pt{minimA/AbB mixture. Typically, these mixtures were prepared using a 10Notably, our method is dependent on a precisely known value for mentclass2pt{minim16. Guided by the simulations in Fig. B proportions, from 0.007 to 0.07  and AbB (9C12Biotin) intensities for control samples (treated with unmixed AbB or AbA) and four representative test samples incubated with a titration of 9C12, containing 0.7% AbB  estimate; credible interval ; Fig. sat  intensity values ; extrapolating from this we then converted the AbA fluorescence values to inferred antibody counts for individual virus particles. Figure The stoichiometric estimates generated by our method are derived from an ensemble measurement and, therefore, represent the antibody interactions of the average virus particle; this obscures heterogeneity within the population. However, given the excellent agreement between the estimated antibody counts and AbA 9C1247 intensA 9C1247 intensA 9C1247 intens17.In summary, we have used statistical modelling to derive stoichiometric estimates of AdV-9C12 complexes. This suggests that the most probable antibody binding maximum is, on average, 133 molecules (95% CI 119-162). However, using stoichiometric estimates to calibrate fluorescent data revealed population heterogeneity with a small proportion of virus particles binding AdV + 9C12 is a well-understood model system and, therefore, is ideal to develop and validate our molecular counting method. However, the technical and analytical framework, outlined here, will be generally applicable to other molecular complexes. Achieving reliable estimates requires the appropriate choice of Various methods permit the investigation of molecular stoichiometries within biological assemblies but technical limitations often make it difficult to obtain reliable estimates. For example SMLM, by its very nature, identifies single molecules and, if properly calibrated, can deliver accurate stoichiometries; however, successful counting by SMLM requires a very detailed understanding of the photochemical behaviour of the chosen fluorescent dyes. Here we outline a robust, and relatively easy, experimental framework for extracting accurate molecular counts using (non-SMLM) fluorescent microscopy and statistical modelling.a priori understanding of the system. The only requirement is that the chosen label is clearly discerned from background; this is easily achievable with bright/stable fluorescent dyes and relatively inexpensive cameras; in this case we used quantum dots for sensitive detection, but many standard fluorescent dyes should also suffice.By creating a scheme in which complexes need only be qualitatively scored for a particular label, our method negates the necessity for carefully calibrated measurements and an An obvious limitation is that our method relies on an ensemble measurement and obscures heterogeneity within the population of complexes. However, this information remains accessible via the A-label fluorescent signals measured from each complex. Consequently, the ensemble-based stoichiometric estimates of the average complex can be used to calibrate these fluorescent signals and infer approximate molecular counts for individual complexes, therefore, restoring heterogeneity.We were able to make robust measurements of AdV-9C12 interactions by fluorescence microscopy and successfully implemented the differential labelling strategy. We performed multiple independent measurements at various antibody concentrations to derive molecular counts for AdV-9C12 complexes. Our analysis estimated that the average AdV particle interacts with a maximum of 133 9C12 antibody molecules. Moreover, through examination of population heterogeneity we revealed that a small proportion of AdV particles may bind up to 230 antibody molecules.17. Whilst there are consistently five 9C12 molecules at each of the twelve vertices of the AdV particle, additional antibody interactions occur through heterogeneous packing across the surface; the pattern of which is likely dictated by the random order in which binding sites become occupied on any given virus particle. Consequently, with optimal antibody packing there is likely to be an absolute maximum binding occupancy of These data can be reconciled with a molecular model of AdV-9C12 complexes. AdV particles possess 720 identical hexon subunits, each providing a potential binding site for 9C12, however, previous estimates suggest an absolute maximum of 240 antibody molecules per virion. This would suggest that particle geometry places packing constraints on the arrangement of antibody molecules. Cryo-EM analyses indicates a complex and heterogeneous interaction network in which particle geometry creates potential antibody clashes and, therefore, prevents binding to every site simultaneouslyThese interpretations expose a potential flaw in our approach. Our modelling strategy assumes that components bind independently, but in this test case the geometry of AdV particles create clashes between adjacent 9C12 molecules such that complete saturation is not possible. Consequently, antibody binding events can be influenced by prior antibody interactions and, therefore, are not independent. Although this may have introduced inaccuracies in our estimates, the molecular counts derived from our approach are in good agreement with previous values. Moreover, we maintain that the assumption of independent binding is appropriate for a generalisable method that can be applied to other biological assemblies.a priori knowledge on maximum stoichiometries we recommend using low Calculating the Fisher information of our method demonstrates that it is capable of reliable quantification over a broad range of In conclusion, we have developed a novel and robust method for counting components within biomolecular complexes. We demonstrate that this approach can provide accurate counts and could be applied in a wide range of other biological systems.Supplementary Information 1.Supplementary Information 2.


The acquisition of new hosts is a fundamental mechanism by which parasitic organisms expand their host range and perpetuate themselves on an evolutionary scale. Among pathogens, viruses, due to their speed of evolution, are particularly efficient in producing new emergence events. However, even though these phenomena are particularly important to the human species and therefore specifically studied, the processes of virus emergence in a new host species are very complex and difficult to comprehend in their entirety. In order to provide a structured framework for understanding emergence in a species (including humans), a comprehensive qualitative model is an indispensable cornerstone. This model explicitly describes all the stages necessary for a virus circulating in the wild to come to the crossing of the epidemic threshold. We have therefore developed a complete descriptive model explaining all the steps necessary for a virus circulating in host populations to emerge in a new species. This description of the parameters presiding over the emergence of a new virus allows us to understand their nature and importance in the emergence process. Significance StatementThe emergence of a new virus in a host population is a complex process. The characteristics of emerging epidemics are well described after the epidemic threshold is crossed, as their dynamics become deterministic and are similar to those of classical epidemics. However, the steps and parameters that influence them before this threshold are stochastic in nature. This work therefore proposes a complete descriptive modeling of the different stages leading to a new emergence. This step is an important milestone toward a better understanding of these processes.The emergence of a transmissible disease is, by definition, the establishment of an epidemic dynamic within a host species by a pathogen that has not previously infected it. By nature, such events are rare and result from complex processes whose explanatory parameters are mostly unknown. One of the main problems we face with emerging communicable diseases is that we only perceive these diseases when they have already emerged and have caused many visible and quantifiable cases. Indeed, from a medical standpoint (human or veterinary), a disease emergence is only formalized when a clinical picture, thus a disease, is associated with a novel pathogen. However, this clinical phase and an ongoing epidemic represent only the last part of the long and complex process of disease emergence. The dynamic of declared epidemics is now well known and the mathematical modeling is precise and well mastered . HoweverAmong the diversity of microorganisms with a potential as emerging disease causative agents, viruses, and more specifically RNA viruses, are the most problematic candidates. Most emerging or re-emerging human viral diseases are caused by RNA viruses. The WHO in its “Prioritizing diseases for research and development in emergency contexts list”, lists no less than 10 diseases, 9 of whthemeing caused by RNA viruses, and the remaining one being the theoretical disease “X” whose etiological agent is not known yet . The perIt is necessary to decipher the process of virus emergence and describe in detail the various steps. We describe in this article an in-depth and detailed analysis of each step of the process and provide a model describing all these steps.The model presented in this article builds on the “parasitic filters” developed in the 1980s by Louis Euzet and Claude Combes to describe the sorting processes restricting the host range of parasite, but was updated since then . These fThe emergence of a virus in a new host species can be divided into three obligatory successive phases: (i) an initial environmental phase  Fig. , which iDuring the environmental phase, a virus metapopulation circulates between different hosts and adapt differentially by intra-host selection to the different species. Each host species has the potential to harbor a genetically differentiated population of the virus metapopulation depending on the ecological contact between the host species and their respective host genetic differences. This host range is largely defined by the target receptor recognized by the virus to enter and infect a target cell. However, viruses from any host species remain capable of triggering an infection in another species within its host range. From a “pathogen point of view,” the concept of species barrier does not cover a reality as only the presence of a receptor recognizable by the virus proteins determines the possibility of infection . The vircircE. A high circulation increases the probability of encounter and transmission. A high number of host species in the host range induces a high network of circulating viruses. This parameter is very difficult to estimate due to the very limited knowledge on the dispersion of viruses in the environment when it is not simply absent. Such viruses circulating among various host species were already identified. For example, Rodrigues et al., in 2017  (The probability of encounter can be directly and deeply modified in some cases if the virus is able to manipulate and modify the behavior of its host—s virus) .AImp-E will alter the way in which the different species in the ecosystem can encounter, either directly  or indirectly   . One of viduals) .PInfC-0E. This capacity is the result of the mode of transmission, thus the location of the viral replication sites in the initial host, the density of viable viral particles produced, and the survival competence of the virus in the environment at the time of the transmission  threshold and trigger an emerging disease. Below this threshold, the pathogen may disappear (and probably disappears most of the time) due to stochastic events.A discrete intranovel host species transmission allows the virus to maintain the infection. This also allows time for adaptive selection mechanisms to optimize the virus infection capacities to its new host species. The genome has been selected until then in the previously infected species and will now evolve to adapt more specifically to this novel host species. This low-key diffusion is conditioned by a new encounter filter defined by different factors:V-0D—and its evolution will largely affect its transmission for two reasons: (a) too low a replication capacity will not allow the production of sufficient viral particles for an efficient transmission and survival  and (b) too high a replication capacity will decrease the mobility of the infected host, increase its probability of dying or decrease its social interactions , and will finally result in a decrease of the virus transmission —smission .MCD—(and damage caused to the host) as well as the immune response of the host—ImmD—, which will modulate the virulence of the virus (possibly to its advantage within the limits of what was explained for V-0D), increasing or decreasing the achieved virulence according to various mechanisms: (a) neutralization of infectious viruses and infected cells decreases virulence, (b) immune tolerance to limit the inflammatory response decreases virulence, and (c) a poorly controlled immune response will increase tissue damage and thus final virulence  threshold  and thisPCIS—, depends essentially on the level of virus circulation in the host population, but also on the probability of successful infection in case of contact—SPInfC. The virus can also modify this last parameter if it is able to manipulate its host—Emanip-D—, which can be modulated over time by the evolution of the virus.Specific elements of virus and host interactions, namely the probability of an infecting contact between two individuals—HDS—during the event, (b) the duration of the event—TBS, and (c) the frequency of the event—fBS. The amplification loops are fractal by nature. Each event will impact the following ones, leading to an increase in the prevalence of the infection in the populations concerned. The superspreading events, often referred to as clusters, detectable in the deterministic phases of different epidemics are the epidemiologic counterpart of these amplification loops, they respond to the same constraints  the host population density—straints .AModS—(e.g. reducing the habitat surface area will increase the probability of encounters) but also by climate change—ClimChS—, which will disturb the distribution of species but also their behavior, e.g. their circadian movements or migrations.The different parameters of these loops can also be modified (increased or decreased) by various anthropogenic disturbances—Once a virus over runs the outbreak threshold owing to the occurrence of amplification loops , the epidemic is declared, the disease emergence is achieved, and a cluster of clinical cases will be generated. The dynamics of the disease now follow classical epidemiological deterministic models.The emergence of new pathogens, i.e. still unknown pathogens at the time of its emergence such as SARS-CoV-2, whether they are viruses as in this model or any other pathogen, is a process that is particularly difficult to apprehend and understand for two main reasons:The dynamic of pre-epidemic emerging pathogenesis is, by definition, extremely complex to assess. Indeed, at any given moment, there are countless primary cases of a variety of pathogens in all possible species. A recent survey on games and wild animals in China showed the presence of 102 viruses, out of which 21 were considered as posing a potential risk to humans . HoweverThe dual chaotic/deterministic nature of the disease emergence phenomenon makes it difficult to understand and to develop tools and models. If the deterministic phase is now well determined and considerable scientific progress has been made, the chaotic phase remains completely unexplored and largely misunderstood.The difference in nature, stochastic/chaotic vs. deterministic, of the mechanisms involved in the emergence processes of viral diseases implies a mathematical modeling approach beyond the qualitative model described in this work. The deterministic postoutbreak threshold phase has been well studied, described, and modeled for several decades and the success of predictions based on classical epidemiological models demonstrates its relevance. This is not the case for the stages preceding the crossing of the outbreak threshold and the detection of an epidemic in a population. This black box clearly cannot be modeled in a classical way for two main reasons.EcolH-nE parameters, but it covers many aspects of the biology and ecology of each species, including ecological niche , behavior , etc.First, the complexity of the parameters involved would need to be broken down and each subparameter evaluated and modeled. The ecology of each species in the host range is summarized by Second, while some parameters follow deterministic laws, such as the match between the virus binding proteins and the cell receptor present in the new host species, chance plays a central role in the achievement of many events. For example, the actual encounter of an individual of a host species, effectively infected by the virus, with an individual of the new host species is of course influenced by many parameters , but the realization of the event is fundamentally random.The chaotic nature of disease emergence does not allow the application of classical deterministic models. This fact is perfectly illustrated by the very existence of an epidemic threshold, described by Hartfield and Alizon . The behIn order to model and therefore study disease emergence processes, it will be necessary to develop a new approach including methods to model these stochastic dynamics that resemble the deterministic chaos known in physics. Part of the answer will undoubtedly be to adapt concepts and tools developed for physical phenomena that have similarities with the mechanisms involved in pathogen emergence.The future of emergence risk studies will rely in particular on spatial approaches and on the elaboration of increasingly complex risk maps integrating numerous parameters and generated by state-of-the-art computer tools such as machine learning techniques . The devL.G. and R.F. designed research, performed research, and wrote the paper.


Monitoring the performanceof polymer-functionalized surfaces thataim at removing and inactivating viruses is typically labor-intensiveand time-consuming. This hampers the development and optimizationof such surfaces. Here we present experiments of low complexity thatcan be used to characterize and quantify the antiviral propertiesof polymer-functionalized surfaces. We showcase our approach on polyethylenimine(PEI)-coated poly(ether sulfone) (PES) microfiltration membranes.We use a fluorescently labeled model virus to quantify both virusremoval and inactivation. We directly quantify the log removal ofintact viruses by this membrane using single particle counting. Additionally,we exploit the change in photophysical properties upon disassemblyof the virus to show that viruses are inactivated by the PEI coating.Although only a small fraction of intact viruses can pass the membrane,a considerable fraction of inactivated, disassembled viruses are foundin the filtrate. Fluorescence microscopy experiments show that mostof the viruses left behind on the microfiltration membrane are inthe inactivated, disassembled state. Combined, our fluorescence microscopyand spectroscopy experiments show that not only does the model virusadsorb to the PEI coating on the membrane but also the interactionwith PEI results in the disassembly of the virus capsid. One example of functionalizedsurfaces for virus removal and inactivation is the polymer-functionalizedmicrofiltration membrane for gravity or low pressure driven waterfiltration. Nonfunctionalized microfiltration membranes poorly retainviruses as their large pore size allows for the relatively unhinderedpassage of viruses. To make microfiltration membranes suitable forvirus removal, functionalization of the membrane is required. Membranefunctionalizations that have been realized, on a lab scale, to decreasethe virus load in water include coating with the cationic polymerpolyethylenimine (PEI) and grafting with zwitterionic polymer hydrogels.4 These functionalized membranes have been shown to effectively removeinfective virus particles. However, the mechanism behind the reductionof infectious particles is largely elusive.A large field in virusresearch addresses the development of methodsfor the inactivation and removal of viruses in, for example, waterand biological fluids. The most straightforward way to remove virusesis based on their size, for example, by ultrafiltration membranesthat are used for water filtration.5 Theoutcome of these assays gives the number of infectious particles inthe sample of interest. Easier quantification methods, which do howevernot asses infectivity, include counting intact viruses in flow virometryor scanning electron microscopy.7 These methods give thetotal number of virus particles per volume. With qPCR the copy numberof genetic material of the virus of interest is determined.8 This copy number does not necessarily reflectthe number of infectious virus particles present as virus inactivationmay result in a release of genetic material. Both released geneticmaterial and virus proteins do not contribute to infectivity; virusdisassembly correlates with loss of infectivity. Current methods tomonitor the breakdown of self-assembled complexes of bio(macro)moleculeslike the virus capsid include fluorescence correlation spectroscopy,fluorescence resonance energy transfer based methods, dynamic lightscattering, nuclear magnetic resonance, and the monitoring of thepresence of binding epitopes for antibodies only present in assembledviruses.12 The methods that are currently used to study virus inactivationand removal are experimentally complex and/or time-consuming and poseoften a bottleneck in the development and optimization of antiviralsurfaces.In the developmentand optimization of surfaces for virus removal,quantifying the reduction and understanding the mechanisms behindthe reduction of infectious particles are crucial. Obtaining thisinformation is often complex and time-consuming. Moreover, many ofthe used assays require expert knowledge outside the field of surfacefunctionalization, for example, in microbiology. To quantify the infectivityof a sample that contains viruses, typically a combination of an end-pointdilution and plaque assays is used.Here we use single particle counting (SPC) in combinationwitheasily accessible fluorescence microscopy and spectroscopy methodsto investigate virus removal and inactivation. To showcase our approach,we functionalized a commercial PES microfiltration membrane with PEIas described in ref . Such meFor the simple, nonoptimized,membranes we used to showcase ourapproach, we determine a 2 log removal of intact viruses. The spectroscopyexperiments, however, show that not only intact but also disassembledviruses are present in the filtrate. The intact and disassembled viruscapsids found in the filtrate add up to ∼13% of the appliedvirus load. This implies that the majority of the viruses were capturedby the membrane. We use fluorescence lifetime microscopy to imagethe virus particles adsorbed to the membrane. The fluorescence lifetimedata show that most of the viruses adsorbed to the PEI-coated PESmembrane are no longer intact but disassembled. Combined, the datashow that the CCMV model virus not only adsorbs to the PEI coatingon the membrane, the interaction with PEI results in the disassemblyof the virus capsid.All chemicals were purchased from Sigma-Aldrich unless stated otherwise.Mw  ∼  25 kDa,Sigma-Aldrich), a cationic polymer, was adsorbed onto negatively chargedcommercial flat sheet EXPRESS Plus poly(ether sulfone) (PES) microfiltrationmembranes with a pore size of 0.45 μm . The PES membranes were first cut into smallerpieces (diameter 20 mm) by using a punch and die set from PrecisionBrand. Before use, the stock PEI solution was diluted in demineralizedwater to 0.52 mM for coating of the PES membrane. Coating was achievedby overnight immersion of the membranes in a solution of 0.52 mM PEIunder mild agitation. Afterward, the coated membranes were washedthoroughly with demineralized water, dried under ambient conditions,and stored until further use.For the membrane modificationwe followed the coating procedure reported in ref . In shor15 The solution exposed primaryamines of the virus capsid proteins were targeted in a fluorescencelabeling step. The formation of stable amide bonds between the aminegroups on the capsid proteins and fluorophores was achieved by followingthe procedure reported in the literature.16 In short, the amine groups on the capsid proteins of CCMV were allowedto react with the N-hydroxysuccinimidyl (NHS)ester of Atto647N (ATTO-TEC GmbH). The labeling was performed by mixinga molar excess of the fluorophore into a CCMV solution . This solution was incubated for 1 h at room temperature.Subsequently, the labeled viruses were separated from unreacted fluorophoresby using a Zeba-spin desalting column (30 kDa molecular weight cutoff)and stored at 4 °C. Nonspecific binding of Atto647N to the virusparticles was negligible.17Cowpea chloroticmottle virus (CCMV) was obtained following the protocol reported inthe literature.7 M–1 cm–1 (5.87 cm2 mg–1).19 The molar extinctioncoefficient of Atto647N at 646 nm is 150000 M–1 cm–1; the absorbance of Atto647N at 260 nm is low withan extinction coefficient of 6000 M–1 cm–1. The fluorophore absorbance at 260 nm was taken into considerationin calculating the DOL. The labeling procedure resulted in a DOL of61 fluorophores/virus.Theaverage number of attached fluorophore molecules per virus (degreeof labeling or DOL) was derived from the absorbance at 260 and 646nm. CCMV does not absorb at 646 nm; the molar extinction coefficientof the virus at 260 nm was reported to be 2.7 × 10For the virusfiltration experimentsan Avanti mini extruder was used to support the (modified) membrane.The extruder was connected to 1 mL Hamiltonian syringes on both theinlet and outlet. With the help of a syringe pump , the flow of the virussolution through the membrane was set to a rate of 100 μL/min.All the filtration experiments were performed at room temperature.20 To exclude false positives, for example, from noise or (far) outof focus signal, an intensity threshold was used.Virus particle counting experiments were performedas reported in ref . The virFor single particletracking to obtain particle sizes, we usedthe same setup to recorded videos of the freely diffusing labeledvirus particles in the solution. Excitation was synchronized to a5 ms exposure time at a frame rate of 75 frames/s. To obtain particletrajectories, we used the same script as in SPC to identify particlesin each frame. To avoid false positives, identified particles wererequired to be present for a least three consecutive frames. Fromthe single particle trajectories mean-square displacements were obtained.The mean particle size was determined via the diffusion coefficientderived from the mean-square displacement data by using the Stokes–Einsteinrelation.12/mL CCMV in an Eppendorf tube under agitation usingan orbital shaker at 160 rpm for 30 min at room temperature.We incubated 200μL of 0.52 mM PEI solution with 10 μL of a 1.6 ×10excitation = 630 nm by using a FluoroMax-4 (Horiba Jobin Yvon) spectrophotometer.Measurements of the fluorescence lifetime, fluorescence correlationspectroscopy (FCS), and 3D fluorescence lifetime imaging (FLIM) weredone by using a PicoQuant MT200 confocal microscope equipped witha FlimBee laser scanner and a 60× NA1.2 objective . Atto647N was excited by a 640 nm pulsed laser; the emissionwas filtered with a 690/70 nm bandpass filter  and detected on a single photon avalanche diode . The obtained data were analyzed by using the SymphoTime64software .For the spectroscopiccharacterization of the labeled CCMV particles, we made use of severalinstruments. Emission spectra were recorded at λTo mimic the presence of (enteric) viruses in the feed in a microfiltrationexperiment, a model nonenveloped virus, CCMV, was used. To enablequantification and to discriminate intact from disassembled virusesin fluorescence microscopy and spectroscopy experiments, the viruscapsids were fluorescently labeled. We compare a PES and a PEI-coatedPES microfiltration membrane to investigate the removal of infectiousparticles.21 The good agreement between the expected values and themeasured concentration and size confirms that the solution mainlycontains intact labeled viruses. This solution is used as feed inthe filtration experiments.The concentration of a stock solution of fluorescentlylabeledviruses was determined spectroscopically. This solution was diluted,and the concentration of the diluted sample was determined by usingsingle particle counting (SPC). Fluorescence microscopy videos ofthe individual, freely diffusing labeled CCMVs were recorded. SPCconfirms the CCMV concentration to be 27 pM, as expected from dilution.Size determination by single particle tracking (SPT) of the labeledCCMV particles results in a mean diameter of 28 nm, which is in goodagreement with the size expected for intact CCMV.13 Increasing the CCMV load by 10 and 100 timesgave the same 2 log removal; no sign of saturation of the membranewith CCMV was observed  number of virusparticles that was applied to the membrane and the total (cumulative)number that passed the membrane and is found in the filtrate. Thecumulative number of applied and detected particles is presented in observed 1, inset.17 This differencein fluorescence can be used to study virus disassembly. In the bulkspectroscopy experiments on labeled viruses the presence of PEI resultedin dequenching of fluorescence and a blue-shift of the emission spectrum measurements were performed. We previouslyreported that for labeled CCMV at the DOL used the fluorescence fromintact virus capsids is quenched and red-shifted compared to the fluorescencefrom disassembled capsids.spectrum2a. The pspectrum2a. In thspectrum2b. This spectrum2c. The m2/s. All these parameters confirm thepresence of disassembled capsids in the filtrate. Concluding, bothintact and disassembled virus capsids are present in the filtrateas evidenced by the single particle tracking and bulk spectroscopyexperiments, respectively. A rough estimate of the ratio between assembledand disassembled capsids can be obtained from the spectra shown in 13 Because typically only a small fraction of viruses are infectious,this difference does not reflect the number of disassembled, inactivatedviruses.Considering that incubation of CCMV with PEI results in virus disassembly,it is expected that filtration over the PEI-coated PES membrane notonly results in virus retention but also affects virus integrity.To allow for the detection of disassembled virus capsids in the filtrateby using spectroscopic methods, an increased CCMV feed concentrationof 270 pM was used. In 12 particles.In the image, the large pore size of the membrane results in regionsin which no fluorescence is observed. For lower loads qualitativelycomparable images were obtained, but the total intensity per pixeldecreased, reflecting the lower amount of virus on the membrane. Plottingthe average intensity per pixel, considering the differences in excitationpower used, shows an almost linear relation between the intensityand the applied virus load (The capsids found in the filtrate only account for ∼13.5%(12.5% disassembled + 1% intact virus) of the total amount of virusapplied to the filter. A large fraction of the viruses thus remainedbehind on the membrane filter. To confirm that viruses indeed remainedbehind on the membrane and to investigate whether these viruses areintact or disassembled, the membrane was inspected in confocal microscopyexperiments. The fluorescently labeled viruses on PEI-coated PES membraneswere imaged after exposure to different virus loads. The membranewas raster scanned, and time-correlated single photon counting (TCSPC)was used to record fluorescence decays and to obtain fluorescenceintensity and FLIM images. rus load 4d. The i12 and 7.7 × 1011 particles thefluorescence lifetime images are shown in To establish if the viruses on the membrane are disassembled, afluorescence lifetime image was obtained by fitting a single exponentialto the fluorescence decay at each pixel 4b. Consi1 = 1.1 ns and τ2 = 3.4 ns are found. However, thefractional amplitudes of the decay components shift from A1 = 0.7 and A2 = 0.3 in solutionto A1 ∼ 0.4 and A2 ∼ 0.6 on the membrane. The increase in the contributionof the longer fluorescence lifetime on the membrane evidences thatviruses disassemble on the PEI-coated PES membranes. However, thefluorescence decay does not converge to the single-exponential decayobserved for fully disassembled viruses (To gain more quantitative insights, the fluorescence decays, obtainedfrom all pixels in the images for each virus load, are summed. Theresulting total decays are plotted together with the fluorescencedecay observed for the intact viruses in the feed 4e. The f viruses 2b. The f22 Upon decreasingthe pH, we thus expect the PEI to remain adsorbed to the PES membranewhile the interaction strength between the PEI and the virus particlesdecreases. Indeed, we find that rinsing the virus containing membraneat pH 3.8 results in virus detachment as evidenced by the absenceof fluorescent signal from the membrane (The adsorption and disassembly of theviruses on the membrane likelyresult from interactions between the positively charged PEI and thenet negatively charged CMMV surface. To verify that adsorption isindeed dominated by charge–charge interaction, we changed thepH. A decrease in the pH should result in protonation of the CCMVsurface while PEI remains protonated and the surface potential ofthe PES remains negative.membrane 5a,b. ExpSummarizing, we directlyquantified the number of assembled virusparticles in the filtrate and thus the log removal of the membrane.Additionally, our method allowed for the semiquantification of thefraction of disassembled, inactivated viruses in the filtrate, andthe visualization of the inactivated viruses on the functionalizedmicrofiltration membrane. Our data show that the interactions betweenPEI and the virus capsids is not only strong enough to hold back viruseson functionalized microfiltration membranes but that the interactionwith PEI also results in the disassembly of the capsids and thus inactivationof the viruses.


Cucumber mosaic virus (CMV), which has great impact on agronomic production worldwide, is both aphid and seed transmitted. Although the mechanisms of aphid transmission have been widely studied, those underlying the ability of CMV to survive and remain infectious during the passage from one generation to the next through the seeds are still to be clarified. Moreover, the viral determinants of seed transmission rate are poorly understood. Three viral genotypes produced from same RNA 1 and 2 components of CMV-Fny but differing in RNA 3  were propagated in Nicotiana tabacum cv Xanthi plants in order to assess differences in tobacco seed transmission rate and persistence through plant generations in the absence of aphid transmission. Seed-growth tests revealed CMV infection in the embryos, but not in the integuments. Seedlings from seed-growth tests showed the presence of all considered viruses but at different rates: from 4%  to 16% (CS). Electron microscopy revealed absence (CS) of viral particles or virions without the typical central hole (F and FS). In agreement, structural characteristics of purified CMV particles, assessed by circular dichroism spectroscopy, showed anomalous spectra of nucleic acids rather than the expected nucleoproteins. These alterations resulted in no seed transmission beyond the first plant generation. Altogether, the results show for the first time that correct virion assembly is needed for seed infection from the mother plant but not to seedling invasion from the seed. We propose that incorrect virion formation, self-assembly and architecture stability might be explained if during the first stages of germination and seedling development some tobacco seed factors target viral regions responsible for protein-RNA interactions. Cucumber mosaic virus  is a plant virus with great impact on agronomic production worldwide due to its extremely wide host range and geographical distribution M in deg cm2 dmol−1 [Circular dichroism (CD) spectra of purified virion (0.2 mg/mL) samples in aqueous solution were recorded on a Jasco J600 CD spectropolarimeter at 24 °C using a cell with a 1 mm optical path length. A HAAKE water bath was used to control the temperature. Data are expressed as molar ellipticity [2 dmol−1 .131→Gly131 (nt 391–393), located in the βE-αEF region of the CP.For the first time, this study demonstrated the ability of three different genotypes of CMV to be seed-borne in tobacco plants, and the inability to proceed beyond the first generation of plants. The three different genotypes varied in seed transmission rate and in the genomic sequence at RNA 3. Thus, our data allows a speculation on this genomic segment as a possible viral genetic determinant of seed transmission, and on the amino acids potentially implicated in this process and their position: codon for SerIn addition, we show that in tobacco plants CMV is unable to persist for more than one generation of strict vertical transmission. An explanation of mechanisms determining the lack of second-generation seedlings infection is that defective or few virions passing to the first generation are unable to recover the virus population after severe population bottlenecks associated with seed transmission, so that the virus does not invade the seeds again. We hypothesize that during the first stages of germination and seedling development some tobacco seed compounds  may target, for example, the viral CP N-terminal region, rich in basic amino acids and responsible for protein-RNA interactions. In this way, the correct virion formation, self-assembling and architecture stability are interfered with and cannot occur. As a consequence, the vertical transmission is restricted to the first generation of plants, without the ability to achieve a second round of progeny infection, regardless of the transmission rate.


Magnetic beads improve biosensing performance by means of their small volume and controllability by magnetic force. In this study, a new technique composed of optically induced dielectrodphoresis (ODEP) manipulation and image processing was used to enhance the signal-to-noise ratio of the fluorescence for stained magnetic beads. According to natural advantages of size-dependent particle isolation by ODEP manipulation, biomarkers in clinical samples can be easily separated by different sizes of magnetic beads with corresponding captured antibodies, and rapidly distinguished by separated location of immunofluorescence. To verify the feasibility of the concept, magnetic beads with three different diameters, including 21.8, 8.7, and 4.2 μm, were easily separated and collected into specific patterns in the defined target zone treated as three dynamic transducer elements to evaluate fluorescence results. In magnetic beads with diameter of 4.2 μm, the lowest signal-to-noise ratio between stained and nonstained magnetic beads was 3.5. With the help of ODEP accumulation and detection threshold setting of 32, the signal-to-noise ratio was increased to 77.4, which makes this method more reliable. With the further optimization of specific antibodies immobilized on different-size magnetic beads in the future, this platform can be a potential candidate for a high-efficiency sensor array in clinical applications. Proteins are important factors in many biological processes, including reproduction of genomic information, gene expression regulation, mRNA transcription, metabolic catalytic reactions, and molecule transportation. In the past few decades , measureBefore the simultaneous detection of multiple proteins in biological samples, high-throughput, low-cost, and low-volume sensing platforms with a sensing performance of high sensitivity and a low limit of detection (LOD) are desired ,11. HoweAmong these results, the limitation of simultaneous multiple sensing by means of magnetic beads still remains an issue. To keep the advantages of magnetic separation and explore further possibilities with affordable price and easy operation, we would like to explore the behavior of antibody-functionalized magnetic beads manipulated in a microfluidic channel by the optically induced electrokinetic (OEK), such as light-actuated AC electroosmosis (LACE) and optically induced dielectrodphoresis (ODEP) under certain operation conditions in the previous literature . With thr, E2 represent radius of the microparticle, permittivity of the medium, and square of the electrical field gradient, respectively [Re[cmf], which is determined by the angular frequency of the electric field , permittivity and conductivity of the medium, and internal permittivity and conductivity of microparticle [ODEP has been proposed from the derivation of DEP by the replacement of physical metal electrodes with tunable and virtual optical-induced electrodes . For ODEectively . Re[fcm]particle ,41, is tparticle .In this study, commercial streptavidin-coated magnetic microbeads commonly had different diameters (D)  being used to investigate the manipulation of tunable transducer elements and corresponding fluorescence study. The structure of these magnetic microbeads has multiple layers from the polystyrene core to several outer layers, such as iron oxide, a protective polymer layer, and astreptavidin coating layer. In this study, these streptavidin-coated magnetic microbeads were prepared in diluted bovine serum albumin (BSA) buffer solutions  with a volume ratio of 0.05%. The electrical conductivity was measured to be 6.5 μS/cm by a conductivity meter .+-doped hydrogenated amorphous silicon (n+ a-Si:H) layer with a thickness of 20 nm deposited by plasma-enhanced chemical vapor deposition (PECVD)  on an ITO/glass. The two through-holes on the top ITO/glass were fabricated by a driller machine to connect the microchannel layer as the inlet and outlet of the solution with magnetic beads in the following experiments and then fixed with a PDMS cubic connector by O2 plasma surface treatment for subsequent connection to the syringe pump. A designed structure of the microchannel and whole ODEP chip is schematically shown in ODEP chips were mainly constructed of a top conductive electrode of ITO/glass, a microchannel, and a bottom photoconductive semiconductor layer of a-Si:H/ITO/glass. The detailed process of the whole system is shown in our previous publication . By follBefore operation, the fabricated ODEP chip was fixed to a self-designed chuck to have horizontal status and stable connections with the bias voltage supplement. The prepared magnetic bead suspension solution was loaded into the microchannel by using a syringe pump . To achieve the OEK-based manipulation of magnetic microbeads, a function generator  was used to apply an AC bias voltage between the top and bottom ITO conductive layer. A commercial digital projector  controlled by a laptop was used to provide programmable light patterns to the backside of the ODEP chip for the manipulation of magnetic microbeads. A microscope, integrated with a charge-coupled device (CCD)  and controlled by a personal computer, was set up to monitor the manipulation of magnetic microbeads from the top of the ODEP chips. For the fluorescence check, this microscope equipped with an excitation lamp  was fixed from the top side of the ODEP chip and filter lens. The exposure time and gain were set as 1000 ms and 4, respectively. During the manipulation and fluorescence monitoring, a light-shielding curtain was used to avoid interference ambient light. The whole ODEP system setup is shown in dF) acting on a spherical particle in a continuous flow condition can be well explained by Stokes’ law, as listed in Equation (2)  factor described in Equation (1) [r) described in Equation (1) [First, the basic manipulation behavior of three different magnetic beads must be verified in advanced investigations. As mentioned in tion (1) . In the tion (1) . Differetion (1) . For exaBased on the maximum manipulation speed of 1 MHz, a low speed of 15 μm/s of light pattern movement can be used to collect all magnetic beads, as shown in Before the accumulation procedure was undertaken, the maximum number of magnetic beads collected in the ODEP manipulation was checked by using different numbers of magnetic beads of 25, 37, 52, and 74 with three different diameters. The procedure, demonstrated in Before manipulating immunostained magnetic beads, different staining ratios between the primary and secondary antibodies were used to verify the fluorescence response of magnetic beads with different diameters. Images for different magnetic beads with different stained ratios captured by optical microscope (OM), fluorescence microscopy (FM), and ImageJ-processed from FM were collected, as shown in To evaluate the possibility of fluorescence images for multiple sensing targets binding on magnetic beads, ODEP manipulation followed with the procedure described in In the meantime, the spatial resolution in the photodetector of FM could also be an important factor impacting the sensing results, especially in small magnetic beads. As shown in To enhance the low SNR  in the group of small stained magnetic beads with a diameter of 4.2 μm, a new skill using a further manipulation step, called accumulation, was used to enhance the signal by collecting more magnetic beads in a wider area and then concentrating them 3-fold in a certain target zone. The detailed ODEP manipulation procedure of this step is shown in As shown in We successfully demonstrated a new technique composed of ODEP manipulation and image processing to enhance the signal-to-noise ratio of the fluorescence for stained magnetic beads. Moreover, under ODEP manipulation, three dynamic transducer elements constructed by magnetic beads with different diameters can be easily obtained to increase the efficiency of biomarker collection and reduce the volume requirement of clinical samples, and which can be used as a tunable and efficient sensor array. Magnetic beads with three different diameters, including 21.8, 8.7, and 4.2 μm, are easily separated and collected into specific patterns in the defined area, which can be easily used to investigate the fluorescence of the stained results. The SNR between the stained and nonstained magnetic beads with a diameter of 4.2 μm is 0.79 and then increases to 77.4 by means of accumulation by ODEP and setting detection thresholds which range from 2 to 32. With the completion of this study, the confidence level of real application can be significantly improved. With the careful design and optimization of specific antibodies immobilized on different-size magnetic beads in the future, this developed platform can be further applied in sensor arrays in clinical applications with high efficiency.


Tomato-infecting viruses have been considered as a serious threat to tomato crops in Poland. Therefore, during 2014–2021, 234 tomato samples delivered directly by greenhouse tomato growers to Plant Disease Clinic of IPP-NRI were tested. Eight virus species: pepino mosaic virus (PepMV), tomato yellow ring orthotospovirus (TYRV), tomato spotted wilt orthotospovirus (TSWV), potato virus Y (PVY), cucumber mosaic virus (CMV), tomato black ring virus (TBRV) and tomato mosaic virus (ToMV) were detected in single or mixed infection in 89 samples. The presence of TYRV was established for the first time in Poland in 2014. Since then, its presence has been observed in single and mixed infection with TSWV and CMV. Here, we analysed the genetic variability of TYRV population based on complete nucleocapsid (N) protein gene sequence of 55 TYRV isolates. Maximum-likelihood reconstruction revealed the presence of three distinct, well-supported phylogroups. Moreover, the effect of host species on virus diversity was confirmed. Therefore, RT-LAMP assay was developed for the rapid and efficient detection of TYRV isolates that can be implemented in field and greenhouse conditions. Cucumovirus), pepino mosaic virus , potato virus M , potato virus Y , tobacco mosaic virus , tomato black ring virus , tomato mosaic virus , tomato torrado virus  and tomato spotted wilt orthotospovirus  was confirmed [Tomatoes are one of the world’s most consumed vegetable crop. On a global scale, the annual production of tomatoes is estimated to be over 180 million tons and their harvesting area is still increasing ,3. The tonfirmed ,10,11,12onfirmed ,14. The onfirmed ,18,19,20onfirmed ,22,23.In 2014, new orthotospovirus species named tomato yellow ring orthotospovirus (TYRV), was found in greenhouse tomatoes for the first time  and sincBacillus stearothermophilus that has polymerase and reverse transcriptase activity [It is very likely that, due to the similarity of symptoms induced by TYRV with those induced by TSWV, its presence in Poland remained unnoticed for some time. Therefore, disease management strongly relies on a fast and accurate identification of the causal agent . In receactivity . Due to activity . The useactivity . LAMP amactivity ,40,41,42The aim of this study was the analysis of the incidence of viral diseases in commercial greenhouses in Poland with particular emphasis on orthotospoviruses. Moreover, we analysed the genetic variability and evolutionary processes involved in TYRV diversification. Analyses were performed on 55 TYRV sequences, representing the largest data set that has been analysed for this virus to date. The contribution of the host plant in TYRV population structure was investigated using Bayesian approaches. Finally, we developed an RT-LAMP assay for the rapid and efficient detection of TYRV isolates.Solanum lycopersicum) samples, delivered directly by greenhouse tomato growers to Plant Disease Clinic of IPP-NRI, were tested. Collected tomatoes  originated from twelve different Polish voivodeships. The majority of them came from Greater Poland, Kuyavian-Pomeranian and Masovian. The tested tomato plants showed variable symptoms: chlorotic or necrotic mosaic on leaves and/or fruits, necrotic plots on fruits, bright yellow ring patterns on fruits, chlorotic rings on leaves and/or fruits, leaf malformation and plant stunting suggesting virus infection. From each sample, 100 mg of apical tomato leaves were used for total RNA isolation using the RNeasy Plant Mini Kit  in accordance with the manufacturer’s instructions.During 2014–2021, 234 tomato (−1 min (depending on the primers used) and a final elongation at 72 °C for 5 min.In order to identify the virus infection, the wide range of diagnostic primers detecting CMV, PepMV, PVY, TBRV, tomato brown rugose fruit virus (ToBRFV), tomato chlorosis virus (ToCV), ToMV, ToTV, TMV, TSWV and TYRV were used . The selhttp://blast.ncbi.nlm.nih.gov/Blast.cgi, accessed on 30 September 2021), assembled, edited and aligned using BioEdit [® software .In a negative control reaction, total RNA isolated from healthy tomatoes was used as a template. RT-PCR products were verified by electrophoresis in 1.5% agarose gel, purified from agarose gels  and sequenced by an outsourced company . Obtained sequences were analysed using Standard Nucleotide BLAST online tool  protein gene sequences of 15 TYRV Polish isolates (previously reported and three described in this study) were compared with the other 40 complete nucleocapsid (N) protein gene sequences of TYRV isolates retrieved from the GenBank database . The seq7 generations with first 104 samples discarded as a burn-in. Convergence of the particular parameters and their effective sample size (ESS > 200) was checked with Tracer v1.7.2 [http://tree.bio.ed.ac.uk/software/figtree/, accessed on 25 November 2018). Subsequently, phylogeny-trait association was evaluated with BaTS 2.0 [p-value < 0.05.The posterior distribution of TYRV phylogenies was obtained using the Bayesian Markov chain Monte Carlo (MCMC) approach as available in the BEAST version 2.6.6 package . Analyser v1.7.2 . FinallyBaTS 2.0 . As a tr®Dye . In addition, to establish primer specificity, the RT-LAMP was performed using LightCycler ®96 Instrument . The reaction consisted of 7.5 μL of Isothermal Mastermix Fluorescent Dye (ISO-001) , 1 μM of FIP and BIP, 0.25 μM of F3 and B3 primers, 0.25 μL reverse transcriptase  and 0.5 μL of target RNA in a final volume of 12.5 μL. The fluorescence signals were recorded in FAM channel  for 30 min. The sensitivity of RT-LAMP assay and conventional RT-PCR were estimated and compared. For this purpose, tenfold dilutions of TYRV-H total RNA were used. The RNA concentration was measured using a NanoDrop 2000 spectrophotometer , adjusted to 100 ng/μL, and serially diluted to serve as a template for both RT-LAMP and conventional RT-PCR methods. The RT-PCR was performed using 2 μL of TY2-F/TY2-R primers  protein gene sequences retrieved from the GenBank database . The set primers , 1 μL ofOut of 234 collected tomato samples, 89 were infected by viruses in single or mixed infection . The resS. lycopersicum grouped in POL and IRN-1 clusters, whereas isolates from S. tuberculosum and Glycine max were located in both Iranian clusters. Nevertheless, isolates from Arachis hypogaea, Capsicum annum, Alstroemeria and Chrysanthemum isolates grouped together within appropriative Iranian clusters. All isolates from ornamental plants were found in IRN-1 cluster. Selective pressure analysis indicated that TYRV population is driven by purifying selection. The evidence of potential negative selection was obtained for 87 codons, from which 52 were detected by three of the used algorithms  (The nucleocapsid (N) protein gene sequences of three new Polish TYRV isolates  of 825 nucleotides in length were deposited in GenBank under accession numbers: OM654405-OM654407, respectively. The nucleotide and amino acid sequence identity of the 15 Polish TYRV nucleocapsid (N) protein gene sequences were relatively high and ranged from 99.2% to 99.8% and from 99.2% to 100%, respectively . A compa, FUBAR) . Only thS. lycopersicum (22 isolates), Alstroemeria sp. (2 isolates), Chrysanthemum sp. (2 isolates), G. max (2 isolates), S. tuberosum (14 isolates), A. hypoagea (6 isolates) and C. annuum (2 isolates) (Suplementary Tropaeolum majus (1 sample), N. tabacum (1 sample), Gazania sp. (1 sample), Anemone (1 sample) and Cineraria cruenta (1 sample) were excluded due to an insufficient sample size. Despite the reduced number of isolates used in analyses, the topology of obtained MCC tree was consistent with this presented by a maximum likelihood tree . Nonetheless, only two subpopulations of TYRV isolates retrieved from S. lycopersicum and S. tuberosum showed differentiation, whereas no statistically significant results were obtained for Alstroemeria sp., Chrysanthemum sp., G. max, A. hypoagea, and C. annuum  protein gene sequences was inferred . Secondlood tree . A phylo. annuum .RT-LAMP primers designed in this study efficiently amplified all the tested TYRV isolates A. The amPlant viral diseases cause epidemics in crops that are often too complex to control and threaten food security. This difficulty is mainly due to the lack of early detection and ineffective countermeasures, especially for emerging viruses. Furthermore, mixed infection affecting a single plant or crop are recognised to be common in plant disease epidemics. Mixed infection can generate a range of ecological interactions that have an impact on viral fitness, and consequently have far-reaching epidemiological implications. From over 130 viruses knowing to infect tomatoes, about 50 species are considered as serious threat causing several problems in field-grown and greenhouse crops ,64. Duri®-01 of Belgian DCM company and V10 of Dutch Valto company were registered in Poland, respectively. The vaccination strategy is based on the principle of cross-protection, where a mild isolate of the virus is used to protect plants against more severe ones. Since then, the number of PepMV-infected samples has been decreasing in comparison to previous years. Nevertheless, PepMV still remains one of the most important threats to tomato cultivation due to its high genetic variability, quasispecies nature and creation of new variants by mutations and recombinations [Cucumovirus) has one of the broadest host range among plant viruses and is responsible for important agronomic losses in many crops worldwide [Crinivirus, Potexvirus, Potyvirus, Tobamovirus) led to synergists interactions affecting the symptoms development and increasing the CMV accumulation [NWi-P strain was observed [NTN, PVY0, PVYNWi-P, PVYNN242 and new recombinant variant between PVYNTN and PVYNWi-P. The predominant strain in greenhouse population was PVYNWi-P and this strain was also identified in 2020 suggesting its prevalence in Poland. The remaining viruses: TBRV and ToMV were detected only once, and it seems that they are not a threat to tomato production. Tobamoviruses on tomato have been rarely detected but lately they were identified in irrigation ditches and drainage canals surrounding fields [Among infected samples, PepMV was the most frequently detected. It is a rapidly emerging virus, which has been established as one of the most important viral diseases in tomato production worldwide . In Polainations ,68. TYRVinations . Orthotoinations . In 2021orldwide . During mulation . In Polamulation ,72. Whatmulation ,74,75,76mulation . Therefoobserved . The surg fields  which caRecently, new emerging virus species have been identified in the EU. One of them was ToBRV, firstly reported in a greenhouse tomato crop in 2014 in Jordan . To datePathogen diagnostics plays an important role in crop protection and disease management. The detailed analysis of genetic structure of virus population is essential to develop effective, sensitive, low-time and cost detection method to identify viruses especially when new pathogen species emerged. Therefore, in this work we decided to analyse the evolutionary dynamics of TYRV which presence has been observed in Poland since 2014. The phylogenetic analyses divided TYRV populations into three clusters corresponding to geographical regions of their origin. The phylogenetic division into two Iranian clusters was reported previously ,82. BaseThe genetic structure and diversity of viral populations can be affected by several factors, such as recombination and selective pressure. Recombination clearly plays a significant role in the evolution of RNA viruses by generating genetic variation, and is beneficial in the case of genes that are under diversifying selection . The recDisease management strongly relies on a fast and accurate identification of the causal agent . Several


RNA viruses have been the most destructive due to their transmissibility and lack of control measures. Developments of vaccines for RNA viruses are very tough or almost impossible as viruses are highly mutable. For the last few decades, most of the epidemic and pandemic viral diseases have wreaked huge devastation with innumerable fatalities. To combat this threat to mankind, plant-derived novel antiviral products may contribute as reliable alternatives. They are assumed to be nontoxic, less hazardous, and safe compounds that have been in uses in the beginning of human civilization. In this growing COVID-19 pandemic, the present review amalgamates and depicts the role of various plant products in curing viral diseases in humans. The continuous increase in the human population has made globalization and contact between people, domestic animals, and wildlife inevitable. This increased connectivity between man and the wild has led to some devastating diseases from wildlife reservoirs with a heavy mortality toll. Some of them like the human immunodeficiency virus (HIV), H1N1 influenza, the highly pathogenic H5N1 avian influenza, Nipah virus, Hendra virus, severe acute respiratory syndrome coronavirus (SARS-CoV), Ebola virus (EBOV), and more recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have created havoc in the world , 4. Meanpro) and papain-like protease (PLpro) cleaved the translated polypeptides to release nonstructural proteins (nsps), whereas RNA-dependent-RNA polymerase (RdRp) facilitates RNA transcription and replication. On the other hand, its mRNA is translated to produce structural and accessory proteins in endoplasmic reticulum (ER). Then, structural proteins are assembled with nucleocapsid into the secretory vesicles (lumen). Finally, the assembled SARS-CoV-2 particles were released by following the exocytosis method [RNA viruses contain RNA molecule to carry their genetic information. However, it also contains the information required for the synthesis of its own protein. These proteins may help in replication and spread to other susceptible host. Due to their reduced coding capacity, they are dependent on host cell to complete multiplication cycle . This ges method .Till now, 13 families of single-stranded RNA (ssRNA) and 1 family of double-stranded RNA (dsRNA) virus have been included in virus classification . Those vMedicinal plant (MP) contains a substantial amount of pharmacologically important secondary metabolites that can be used for therapeutic purposes. Since the very past, different plant parts or extracts had been utilized by local people to prevent many diseases up till now . InteresOn the other hand, commonly used natural plant products in Ayurveda are clearly mentioned in Susruta Samhita and Charaka Samhita or it can be obtained through traditional knowledges . ConventZingiber officinale (ginger), Adhatoda vasica , Piper longum (long pepper), Andrographis paniculata (bitterweed), Tragia involucrata (Indian stinging nettle), Syzygium aromaticum (clove), Terminalia chebula , Hygrophila auriculata (kokilaksha), Cyperus rotundus (java grass), Plectranthus amboinicus (Indian borage), Clerodendrum serratum (bharangi), Tinospora cordifolia (guduchi), Saussurea costus (costus), Sida acuta (teaweed), and Anacyclus pyrethrum (akarkara), has been recommended by the Ministry of AYUSH , Government of India [Cassine xylocarpa stem (Celastraceae), Maytenus cuzcoina root & bark (Celastraceae) [Thymus carmanicus (Thyme), Thymus vulgaris, Thymus kotschyanus, and Thymus daenensis [Nerium oleander  is used against Poliovirus type 1 [Bryophyllum pinnatum , Mondiawhitei , Terminalia ivorensis , Ageratum conyzoides  are used to cure echovirus [Andrographis paniculata (Acanthaceae) and Gynostemma pentaphyllum  are used to prevent avian influenza virus (H5N1) [Traditionally, medicinal plants are being used to cure various human diseases. Most of the Asian countries like China, Japan, and India have a great past history of usage of medicinal plant and mushroom extracts . Amalgamof India . The anttraceae) , and cruaenensis , 29, whis type 1 ; methanochovirus ; aqueouss (H5N1)  etc.  TaCarica papaya leaf extract that is used by the local people of North Eastern plain zone of India, Madhya Pradesh [Andrographis paniculata (bitterweed), Alternanthera sessilis (sessile joyweed), Achyranthus aspera (prickly chaff flower), and Solanum xanthocarpum (yellow-fruit nightshade), and leaf and bark of Calotropis procera  used in Bihar by traditional healers [Carica papaya (papaya) on patients with dengue fever increases their platelet count [pro)  [There is not a single medicine, which is globally accepted for the treatment of dengue fever. However, extracts obtained from different plants are expected to lower the severity of dengue viruses by increasing the platelet count, which includes  Pradesh , 56, who healers , 33. In et count . More spet count .  Table gallate) .Ampelocissus tomentosa (root), Clerodendrum serratum (whole plant), and Terminalia chebula (leaves) are effective against chikungunya virus, yellow fever virus, and entero virus, respectively [Litchi chinensis inhibits 3CLpro [Juniperus oxycedrus (cade juniper), Laurus nobilis (bay tree), Thuja orientalis (thuja) act as viral growth inhibitor [Broussnetia papyrifera (paper mulberry) containing Kazinol F and Broussochalcone A, and 3′-(3-methylbut-2-enyl)-3′,4,7-trihydroxyflavane showed noncompetitive inhibition on papain like protease (PLpro) of MERS-CoV and SARS-CoV, respectively [pro protease, which cleaved translated polypeptides to liberate nonstructural proteins.Ethanolic and methanolic extracts of ectively . Flavonos 3CLpro , 68, andnhibitor  against ectively , 70. Theectively , 62; tinectively  inhibit Moringa oleifera helps the patient of COVID-19 to decrease the rate of infection caused by the SARS-CoV-2 virus. Different plants induce the production of numerous secondary metabolites such as phenolics, essential oils, glycosides, coumarins, alkaloids, terpenoids, and peptides mainly in response to microbial infections or to avoid herbivores and other organisms  and 2 (HIV-2) , hepatitCamellia sinensis (tea) shows biological action by binding on RNA-dependent RNA polymerase against SARS-CoV-2 [Allium sativum (garlic) act as ACE2 receptor inhibitors [Linum usitatissimum (flax) [Chamaecyparis obtusa var. formosana (Taiwan yellow cypress) act as 3CLpro inhibitor against SARS-CoV; Scutellaria lateriflora (blue skullcap) helps to prevent SARS-CoV by scutellarein as helicase inhibitor [Nigella sativa (fennel flower) show the blocking of virus entry into pneumocyes and increasing the Zn2+ uptake to boost host immune response against SARS-CoV-2 [″-O-p-hydroxybenzoagte obtained from Ocimum sanctum L. inhibit Mpro protease activity during SARS-CoV-2 viral infection [Few preidentified compounds from different traditional medicinal plants of China showed protective actions against SARS-CoV-2 like betulinic acid, lignin, and sugiol on replication and chymotrypsin-like protease (3CLpro); coumaroyltyramine, cryptotanshinone, kaempferol, N-cis-feruloyltyramine, quercetin, and tanshinone IIa on papain like protease (PLpro) and 3CLpro; desmethoxyreserpine on replication, 3CLpro, and entry; dihydrotanshinone on entry and spike protein; and dihomo-c-linolenic and moupinamide on 3CLpro and PLpro, respectively, to prevent COVID-19 , 105. FuRS-CoV-2 . SeveralRS-CoV-2 , 107. Alhibitors , 98; herm (flax) , 68, betnhibitor . FurtherRS-CoV-2 . The recnfection .Atropa belladonna that gives a positive result and cure of Ebola haemorrhagic fever (Ebola HF) [Cladosiphon okamuranus, and sulphated polysaccharide (named kappa carrageenan) from whole plants of Gymnogongrus griffithsiae [In case of the treatment of Ebola virus, many alkaloids are isolated from bola HF) , 101, whfithsiae  worked afithsiae .Tephrosia , which can able to produce huge number of flavonoids and show antiviral activity against dengue virus. Among them, glabranine and 7-O-methyl-glabranine isolated from T. madrensis showed strong inhibitory effects on dengue virus replication in LLC-MK2 cells. Interestingly, moderate to low inhibitory effect was observed by methyl-hildgardtol A isolated from T. crassifolia. However, hildgardtol A of T. crassifolia and elongatine of T. viridiflora do not show any inhibitory effect on viral growth [Magnolia tree has antiviral activity against serotype 2 dengue virus (DENV-2). This novel molecule can be able to interfere on the endocytosis of virus to reduce its double-strand RNA, by abrogating the colocalization of DENV envelope proteins. Inhibitory activity of honokiol was proved by suppressing the replication of DENV-2 in baby hamster kidney (BHK) and human hepatocarcinoma Huh7 cells [There are three species of l growth . Honokioh7 cells , 47.Lonicerae japonicae (Japanese honeysuckle), Flos (ragged-robin), and Fructus forsythia (Lianqiao) are used together as an antimicrobial and anti-inflammatory agent. Interestingly, chito-oligosaccharide in combination with herbal mixture can also act as an anti-influenza agent [In the Chinese herbal medicine, extracts of za agent .in vitro and ex vitro conditions. This is also very challenging but can be resolved by using sophisticated techniques of recombinant DNA technology, elicitation, etc. [Nowadays, the acceptance of herbal medicines is increasing for many reasons as it is less expensive, with less or null side effects and better patient tolerance. From the past to recent studies, it can be speculated that quality and safety study of plant-derived compounds with medicinal importance is required. Therefore, scientific, accurate, and informative studies are obligatory for any potent compound, which have isolated from plants . About hon, etc. . Along won, etc.  that witon, etc. . It is aon, etc. . The CRIon, etc. .Standing in the current circumstance of global pandemic of COVID-19, that causes huge damage of human health and also destroys economic backbone of a country, researchers are constantly trying to find out the way by which mankind will be safe from the fourth or fifth wave of virus onslaught. At this time of high crisis period, we all want something to eradicate or bypass the disease. We reviewed the plant extracts and/or extracted and identified active compounds from the medicinal plants that are useful for prevention of many RNA viral diseases, focusing on plant extracts and phytochemicals that have already reached in clinical trials and having highlighting properties to prevent the viruses. Along with disruption of global health, RNA viruses have immense potential to stop the economic growth of a country. However, for prevention of those diseases and to secure human populations, antiviral drug discovery is needed. Till date, many traditional medicinal plants were reported to have strong antiviral activities. Medicinal plants contain active compounds like alkaloids, saponins, flavonoids, tannins, polysaccharides, proteins, and peptides. These compounds can help in the prevention of viral diseases by blocking the virus entry and/or via the inhibition of viral replication at the different stages by regulating the enzyme actions as well and specially without having any known side effects. Finally, the improvement of newly discovered medicinal plant products is vital and required for controlling the constant threats of deadly contagious RNA viruses. This review enlightens some way with lesser hazard to combat in this epidemic era of RNA virus like COVID-19. It is necessary to further examine by highlighting drug delivery system of antiviral phytochemical to reach successfully in their intended site of action.


This study examines changes in utilization and costs trends associated with migraine medications.Migraine attacks are a burden to many patients. There are many pharmacotherapy options available with newer migraine drug classes entering the market in the past decade. Little is known about the use, associated costs, and the impact of the newer agents.This retrospective, cross-sectional study examined 2017–2020 administrative claims from a large national pharmacy benefits manager. Patients aged ≥ 18 years enrolled in commercial, Medicare, Medicaid, or health insurance exchange insurance plans who filled ≥ 2 prescription claims for triptans, ergotamines, isometheptenes, gepants, ditans, and CGRP mABs were included. A two-sample t-test was conducted to estimate whether differences in mean utilization and costs between 2017 and 2020 were statistically significant for migraine drug classes, except for CGRP mABs, which were estimated between 2018 and 2020.n = 203,110; 2020) of patients were women. The number of 30-day adjusted prescription fills for prophylaxis remained stable over the four-year period, except for CGRP mABs, which increased from 0.5%  to 5.3% . Antiepileptics, antidepressants and beta blockers were the most common prophylaxes, while triptans, non-steroidal anti-inflammatory drugs/non-narcotic analgesics and opioids were the most common treatments utilized. CGRP mABs were the most expensive, while utilization of triptans were the highest. CGRP mABs had the largest increase in utilization (177.5%) and costs (166.3%) PPPM in 2020 ($291.17) compared to 2018 ($109.35), the year they were first available (p < 0.001). Between 2018 and 2020, costs increased overall and for commercial and Medicare enrollees, but remained unchanged for Medicaid and HIX members.The sample ranged from 161,369 (2017) to 240,330 (2020) patients. 84.5% (Our study demonstrates a shift in migraine medication utilization from 2017–2020, where increased use of CGRP mABs had a significant contribution to increased costs. These increased pharmacy costs must be weighed against the improved tolerability of these agents likely resulting in other healthcare and indirect cost savings.The online version contains supplementary material available at 10.1186/s10194-022-01476-y. Migraine is one of the most common neurological diseases, affecting at least one in six Americans  and 14% Patients with migraine attacks report worse disability or quality-of-life and those with higher headache frequency reported worse health status than those who do not report headaches , 8, 9. F1Freceptor) [Multiple pharmacotherapy options exist to prevent and treat migraine attacks. Pharmacotherapy of migraine focuses on acute treatment  and prophylactic treatments . Acute treatment of migraine attacks are either non-specific pain pharmacotherapies, such as non-steroidal anti-inflammatory drugs (NSAIDs) and opioids, or migraine specific, such as triptans and ergot derivatives, and more recently, the gepants  , and diteceptor) –24. Propeceptor) .Costs related to migraine can be both direct  and indirect . In 2016, it was estimated that the total direct and indirect economic burden of migraine in the United States (US) was 36 billion dollars. Patients with migraine attacks reported, on average, $6575 higher healthcare costs than patients without migraine attacks . PatientThis was a retrospective, cross-sectional study using deidentified member-level enrollment and administrative claims from a large national pharmacy benefits manager (PBM) from January 1, 2017-December 31, 2020. Inclusion was limited to adults aged ≥ 18 years enrolled in commercial, Medicare, Medicaid, or health insurance exchange (HIX) insurance plans whose pharmacy benefits were managed by the PBM. Prescription drugs used specifically for the treatment of migraine were used as a proxy for selecting patients with migraine. Patients who filled two or more 30-day adjusted prescription claims for either triptan, ergotamine, isometheptene, CGRPmABs, gepant or ditan drug classes at any time during this four-year period were included. Members who switched insurance types  within the year were excluded.The prescription drug classes examined in this study were broadly divided into two categories: migraine prophylaxis (or preventive) drug classes and migraine treatment drug classes. Specific drugs within all medication classes examined in this study were identified using the proprietary generic product identifier associated with prescription drugs and are listed in Appendix Table The number and percentage of patients per medication was calculated. Utilization was defined as the total number of 30-day adjusted prescription fills PPPM and calculated by dividing the days’ supply by 30 to standardize as 30-days’ supply; summing up all prescription fills and dividing by the number of months of eligibility for all patients for each of the four years. Annual costs for all migraine acute and prophylactic classes were defined as gross costs net of  rebates PPPM, in 2020 US dollars, by adjusting for inflation using the Consumer Price Index (13). Gross costs comprised of ingredient costs, taxes, dispensing fees, administrative fees, and member out-of-pocket costs for each year, and represent costs after all manufacturer concessions are accounted for (including rebates and discounts) for each of the four years. Gross costs were summed up for all patients, for each medication class and total overall, and divided by the number of months of eligibility for all patients in each year. Independent variables included age, gender, and insurance type .p < 0.05 for the overall sample and among insurance types. A separate two-sample t-test was conducted to determine whether differences between 2018 and 2020 were statistically significant at p < 0.05 for CGRP mABs since they were approved and marketed in 2018. All analyses were conducted using SAS statistical software v9.4 .Differences in mean utilization and costs PPPM for each medication class were examined from 2017–2020. A two-sample t-test was used to determine whether differences between 2017 and 2020 were statistically significant at n = 135,869, 84%) in the study were women across all years. A higher proportion of migraine patients belonged to the 45–64 age group. The study population reflected a mostly commercially insured population . Over the course of the four-year period, the relative percentage of younger patients (aged 18–64) increased each year while the relative percentage of older patients (aged 65 and older) decreased each year in the overall sample population and in the commercial and Medicaid subgroups; however, in the Medicare subgroup, the relative breakdown by age remained consistent  of all migraine utilization, which increased to 5.3% (n = 0.075) in 2020. The percentage was highest for commercial enrollees  and lowest for Medicaid enrollees . The most common migraine acute class overall was triptans ranging from 35.4% of all utilization in 2017 (n = 0.516) to 34.5% in 2020 (n = 0.486), followed by NSAIDs and non-narcotic analgesics  and non-acute opioids use . When examining the percentage contribution to gross cost net of rebates PPPM by all drug classes, CGRP mABs had the largest increase over the study period. In 2017, CGRP mABs comprised 3.0% of all migraine drug costs ($3.12), which increased to 30.0% in 2020 ($33.55), the highest across all migraine drug classes examined in this study  compared to 2017 . This was due to a 4.2% decline in utilization of acute migraine medication classes that offset a 3.8% increase in utilization of migraine prophylactic medication classes over the same period (p < 0.001). While antidepressants (3.5%), beta blockers (3.4%) and ACEI/ARB (4.8%) all had positive four-year trends, the uptick in utilization for CGRP inhibitors also had a significant contribution to the overall utilization increase for migraine prophylactic medication classes. CGRP inhibitor PPPM utilization relatively increased by 177.5% in 2020 (0.652) compared to 2018 (0.235), the year in which they were first available (p < 0.001), while utilization of triptans , NSAIDs and non-narcotic analgesics  and barbiturates  declined, chronic opioid  and ergotamine use  remained relatively unchanged. In the commercially insured sample, non-acute opioid use increased by 4.6% (p < 0.001), while utilization for these drugs declined among Medicare  and Medicaid enrollees , and remained unchanged from HIX enrollees . Notably, there were declines in utilization across all migraine acute and prophylactic medication classes among Medicaid enrollees, many of which were statistically significant at p < 0.001. Among those aged 65 or older, overall utilization remained unchanged (p = 0.997), while use of opioids  and ergotamine  increased, although overall use of these agents was low in all time periods.Overall, there was a 3.0% decline in the number of 30-day adjusted migraine medication prescription fills PPPM on average in 2020 (p < 0.001), from $128.41 in 2017 to $112.01 in 2020 (Table p < 0.001) in average costs. When examining the change from 2018 to 2020, there was an increase of 7.3% (p < 0.001) in average costs, primarily driven by a 166.3% increase in PPM costs for CGRP mABs (p < 0.001) In addition, gepants and ditans were first marketed in 2020, which also contributed to an increase in average cost for migraine therapies for that year.Examining the differences in migraine medication costs net of rebates between 2017 and 2020, we found that average costs PPPM declined by 12.8% (p < 0.001) and were not significantly different for HIX enrollees (p = 0.398). For patients aged 18–64 years, overall costs declined by 13.1% between 2017 and 2020, but increased by 7.3% between 2018 and 2020 (p < 0.001). Triptan costs declined by 53.5% from 2017 to 2018, while CGRP costs increased by 167.8% between 2018 and 2020 (p < 0.001). For patients 65 or older, despite not having statistically significant overall migraine cost changes between 2017 to 2020, had a 34.4% decrease trend in triptan costs from 2017 to 2020 and a 148.4% increase in CGRP costs between 2018 and 2020 (p < 0.001).Regarding costs differences amongst insurance types, the trends were similar for commercial and Medicare enrollees, while they declined for Medicaid enrollees  increased during the study period, they still represented only 17.8% of migraine prescriptions in 2020. However, because of their significantly greater cost, they accounted for 39.7% of overall costs in 2020. Due to their recent entry into the market, data are limited on comparative effectiveness of the CGRP mABs and older preventative therapies, but some conclude that CGRP mABs have similar effectiveness for migraine prophylaxis . The PCOEven with a slight decline in utilization over time, triptans were the most popular migraine treatment, reflecting their wide availability of products and formulations and proven track record for effectiveness. This likely reflects favorable insurance formulary practices, as most oral triptans have a generic equivalent with average wholesale prices from $9-$600 for a 30-day supply, and an average cost of $31.92 for our population in 2020 . In addiOther trends merit some discussion. Opioids are not recommended for treatment of migraine, although they are commonly used for this indication . BecauseOur analysis expands upon previous research that has been conducted on migraine related costs in US based health systems, which have found the newer pharmacotherapy options are more cost-effective for a subset of patients , especially when adding in indirect costs . Prior tThe study has caveats and limitations inherent with analyzing claims data. The study population mainly included commercially insured patients versus those with Medicaid and Medicare, which limits generalizability as it does not reflect national breakdowns of health insurance coverage in the US . BecauseOur study adds to the current literature as it captures the shift of utilization and cost of when CGRP mABs entered the market. These changes in utilization and cost trends allow payers and patients to have a better understanding of treatment costs, especially as clinical guidelines and practices are updated to address this expensive burden and public health problem. Future studies are needed to evaluate the impact of newer migraine medications relative to older medications on healthcare utilization, improved quality-of-life, and work outcomes for patients with migraine.Additional file 1: Appendix Table 1. Migraine Preventive and Acute Rescue Prescription Medication Classes.