Validation of imaging contrast agents, such as fluorescently labeled imaging antibodies, has been recognized as a critical challenge in clinical and preclinical studies. As the number of applications for imaging antibodies grows, these materials are increasingly being subjected to careful scrutiny. Antibody fluorescent brightness is one of the key parameters that is of critical importance. Direct measurements of the brightness with common spectroscopy methods are challenging, because the fluorescent properties of the imaging antibodies are highly sensitive to the methods of conjugation, degree of labeling, and contamination with free dyes. Traditional methods rely on cell-based assays that lack reproducibility and accuracy. In this manuscript, we present a novel and general approach for measuring the brightness using antibody-avid polystyrene beads and flow cytometry. As compared to a cell-based method, the described technique is rapid, quantitative, and highly reproducible. The proposed method requires less than ten microgram of sample and is applicable for optimizing synthetic conjugation procedures, testing commercial imaging antibodies, and performing high-throughput validation of conjugation procedures. Validation of antibodies has been recognized as a critical challenge in clinical and preclinical studies1Quantification of the fluorescence brightness of the labelled antibody is important for the following reasons: i) it enables optimization of the conjugation protocol and selection of the fluorescent label to achieve the highest brightness, ii) provides quality control of the conjugates, leading to the consistency of the imaging results, iii) defines and minimizes the necessary dosage, lowering the toxicity of the imaging procedure while maintaining a sufficient signal-to-noise ratio.in vivo assays of small animalsThe majority of fluorescent antibody applications in biochemical assays are based on a two-component assay, where a secondary antibody is labelled with a fluorescent tag12Although ImAbs have relatively slow pharmacokinetics and low tissue permeability compared to smaller molecules, they have in many cases unmatched specificity. The wide variety of secondary and ImAbs requires their fluorescence measurements to be standardized and reported, but this information is rarely available. Instead it is often assumed that fluorescence brightness of the labelled antibody is equivalent to the brightness of the free dye, which is often incorrectB), which is defined as the product of molar absorptivity of the dye (ε) at the wavelength of excitation (λ), quantum yield (Q) and the number of fluorescent tags (Nf) per antibody, also known as degree of labelling, (DOL) according to The major quantitative parameter describing fluorescence activity of a labelled antibody, and therefore its sensitivity, is the brightness  and uncoated beads that do not bind antibodies (negative beads), but provide a measure of background fluorescence. These beads could be analysed by standard flow cytometry techniques, in which the signal intensity from individual beads is proportional to the fluorescent brightness of the antibody. This method is similar to calculating a Stain Index for assessing the brightness of a fluorophore via the relationship between the positive and the negative (background) signals using cells18Is) can be used as a measurable parameter directly related to fluorescence brightness (B ∝ Is) of the labelled antibody.The fluorescence intensity of the positive beads relative to that of the negative beads provides a quantitative but relative basis for antibody assessment. The separation between the populations at the beads’ saturation (I). Other metrics, such as Stain Index (SI) and Bhattacharyya distance (DB) that takes into account standard deviations were also used. All metrics can be calculated using our developed in-house software, Label-It, based on MATLAB.We envisioned that bimodal distribution of the histogram, in which the pixel intensities clustered around two reasonably separated values, might serve as a benchmark for brightness evaluation and a quantitative approach for antibody validation. Highly overlapped modes  suggest low brightness, while well-separated modes indicate strongly fluorescent probes. Thus, we first fitted a histogram with a two-member Gaussian model to obtain two populations. Identified parameters were then used to calculate the gap between the two peaks to provide what we called Peak Mean Distance  . A hydroFlowJo. Each sample was compared against control not-treated beads. We found the fractions of beads that changed their shape (judged by the changes in front scattering (FSC) and site scattering (SCS) distributions) were consistently less than 6%, with most cases less than 1%. This high similarity between two populations of beads, treated and non-treated, suggests the physical and chemical stability of the beads.The physical stability of the beads upon treatment was confirmed by comparison of their scattering patterns . ScatterIn this work, we postulated that the fluorescence of the bead is proportional to the number of fluorophores, and that the maximum fluorescence comes from the saturation of the beads surface. For that we incubated a standard number of beads with varied quantities of labelled antibodies for each of the studied dyes. To assess the sensitivity of the method and identify the range of concentrations that can be measured, we utilized a blocking method in which the surface of the bead was blocked by a progressively larger concentration of non-labelled antibody, after which it was treated with an excess of a single concentration of fluorescently tagged antibody. The flow cytometry histogram in the corresponding fluorescence channel presents two peaks . The peaThe attempts to reach the full blockade, however, were not successful apparently due to non-covalent attachment of the antibodies to the bead and equilibrium between the competing species (i.e. antibody and dye-antibody conjugate). The shift in the fluorescence negative population observed in this and other experiments is due to some non-specific affinity of the negative beads to antibodies.50) was calculated from the nonlinear regression model of log(inhibitor) vs. response - variable slope, and was found to be 0.18 μM. Given that the range of concentration typically covers two log units (100-fold change in μM concentration) times the IC50, the range of useful concentrations for the given number of beads lies within 0.02–2 μM. It should be noted that the span of concentrations can be different for the beads of different origin, size, or coating.This blocking approach enables us to evaluate the span of concentrations to be used for the measurements of the fluorescent brightness. Analysis of the histograms revealed a typical sigmoid curve of the gap between means vs. concentration of the unlabelled IgG . The 50%The application of our method for fluorescent assessment of IR650-IgG conjugate is illustrated in Is) (The plateau of the fluorescence of beads at higher concentration was due to saturation of the affinity sites on the beads. Fluorescence intensity at the saturation point (Is)  correspoI value (The reliability and consistency of the measurements were first assessed using a single batch of labelled antibody bound to compensation beads at different concentrations of the conjugates and the fixed amount of the beads. High reproducibility of the results (low standard deviation) is demonstrated in I value .π-stacking, leads to efficient energy transfer between the dyes, resulting in severe quenching and lowered brightness of the targeted probeThe presence of multiple fluorophores (DOL > 3) in close proximity can decrease fluorescence brightness of the labelled antibodyπ-stackingMany fluorescent dyes are prone to self-quenching when many of them are attached to a protein, an antibody or a nanoparticle23We used the proposed method to test how the DOL levels affect the brightness. LS822 has an asymmetric charge distribution and is highly hydrophilic. Its hydrophilicity is guaranteed by the three sulfonate groups and ensures the absence of non-specific binding to the beads. The more fluorescently labelled antibody, with a DOL 3.15  vs. 1.81Dye-antibody conjugates are frequently contaminated with free unreacted dye. It is expected that free dyes will have negligible affinity to the beads, and therefore no fluorescence will occur in any of the bead populations when incubated with free dye alone. Indeed, when IR-650 and LS822 were incubated with the beads at two concentrations, the histogram showed only a single peak with near zero fluorescence intensity  because in vivo imaging studies in which low fluorescence demands higher doses of the antibody in order to reach the desired signal-to-noise ratio. We developed a rapid method for measuring the brightness-related parameter of fluorescently-tagged antibodies using a mixture of antibody-capturing positive and negative beads as an internal reference and flow cytometry.Quantitative measurement of the fluorescent properties of labelled antibodies is necessary for reproducibility in a variety of laboratory assays. It is critical for Overall, the procedure requires less than 10 μg of antibody and takes only a few minutes of mixing the fluorescent antibodies with the beads, and then analysing the resulting mixture with a standard flow cytometer. The method is highly reproducible and is applicable for optimizing synthetic conjugation procedures, testing commercial antibodies, and performing high-throughput validation of labelling.in vivo studies are, in general, different from standard flow cytometry configurations . Thus, care has to be taken for direct comparison of conjugates with respect to their performance under imaging conditions. Flow cytometers with dedicated “imaging-like” channels should be preferred for the best translatability between the techniques. Finally, the beads with lower non-specific affinity and beads covered with specific antigen instead of broad-spectrum activity would allow for more universal applicability of the method.Several considerations have to be taken into account. Different clones of monoclonal antibodies (mAbs) may have different affinity for their corresponding native antigen on the cell surface. Therefore, the brightness of different mAb clones captured on the beads may not be the same as the brightness of the cells stained with the same clones. For brightness comparison of commercially available conjugates directed to the same antigen but of a different clone, Stain Index obtained directly from the cell staining is the valid methodology. Special care should be taken interpreting of conjugate brightness based on beads derived data. Selection of conjugates takes place through the interaction of the kappa light chain of the antibody with the anti-kappa antibody on the surface of the bead. The same conjugate, however, interacts with cell antigen through the antigen-binding domain, which is different from a kappa-light chain of an antibody. Given that flow cytometry measurements depend on a number of instrumentation-related parameters, the presented method only provides the relative brightness and cannot determine DOL directly. Absolute values of the brightness will require a set of recognized standards, for example, beads with known fluorescent brightness. The second consideration is that the imaging optics for 2) of the signal from the positive beads. For that, the beads should have relatively low coverage to minimize the averaging. Although we do not present this analysis, the described approach can be used to optimize the conjugation process and establish uniformly labelled conjugates. The method can be also applied to compare alternative labelling techniques, such as utilizing maleimide coupling to sulfhydryls, or through conjugation to the carbohydrate via reductive amination.NHS ester conjugation, so far the most popular method for antibody labelling, leads to variability in the degree of labelling and therefore, to the broad distribution of brightness among fluorescently tagged antibodies. The proposed method can potentially address this question and characterize the variability of labelling by calculating the standard deviation (σ5 per drop (50 μL) in 0.1% BSA/PBS buffer stabilized with 0.09% sodium azide. IRDye 650 NHS Ester was obtained from LI-COR, Cyanine5-NHS ester was purchased from Lumiprobe. Immunoglobulin G (IgG) from rat serum, reagent grade, lyophilized powder, cat. I4131 was purchased from Sigma-Aldrich.Polystyrene beads  were purchased from eBioscience. Each sample of beads contains a positive and negative population. The positive population is coated to have high affinity for kappa chains of antibodies and captures mouse, rat, and hamster antibodies. The negative uncoated population of beads is unreactive, with no sites to capture antibodies. This negative population was expected not to show fluorescence after treatment with the dye-antibody conjugate and hence was used an internal reference. The concentration of beads is 2.5 × 10A dye LS822 and the conjugates of IR650-IgG and LS822-IgG were synthesized, purified, and characterized as specified in the εp,280) was set to 190,000 M−1cm−1 for IgG according to the manufacturer. The molar absorptivities for the dyes in water were determined to be 130,000 M−1cm−1 for LS822 using Beckman Coulter DU-640 UV-vis spectrophotometer, and 230,000 M−1cm−1 for IR650 as reported by the manufacturer. The D/P ratio of the bioconjugates was calculated according to a known eq. 223The molar absorptivity coefficient of the antibodies at 280 nm  were mixed with 25 μL of compensation beads at 4 °C for 30 minutes. Samples were centrifuged at 3,000 rpm for 5 min at 4 °C. Supernatant was removed and the beads were washed once, resuspended in 50 μL PBS, and diluted to 500 μL PBS.50 was calculated from the resulting I values according to the Varying amounts  of unlabelled 20 μM IgG were added to 25 μL compensation beads, and incubated at 4 °C for 30 min. Beads were then isolated by centrifugation, washed once with PBS, and resuspended in an excess (30 μL) of IgG-IR650 conjugate, with the final concentration at 2.5 μM. Beads were further resuspended in 50 μL PBS and diluted to 500 μL PBS prior to analysis by flow cytometry. ICI is the gap between peaks, Top and Bottom are plateaus in arbitrary units, [C] is the concentration of unlabeled IgG in nM, IC50 is the concentration of unlabeled antibody in nM, and HillSlope is the steepness of the curve.Where A solution (3 μL) of either IR650 (0.175 mM) or Cyanine 5 (0.6 mM) in DMF were mixed with 75 μL of PBS buffer. The resulting solutions (0.1 μL and 1.0 μL) were mixed with 25 μL beads each. Final concentrations were 0.026 μM and 0.26 μM for IR650, 0.092 and 0.92 μM for Cyanine 5. The beads were separated from the solution by centrifugation, the supernatant removed and beads further re-suspended in 50 μL PBS diluted to 500 μL PBS prior to the analysis by flow cytometry.For microscopy studies, beads were incubated with a solution of 10 μL of the conjugate in 250 μL of PBS. Before and after the treatment, the beads (1 μL) were placed on a glass slide, covered with a coverslip, and sealed with a nail polisher. Differential image contrast (DIC) and fluorescent images of the beads were recorded with a BX51 Olympus Microscope equipped with Nomarski optics for objective 40X and a Cy5.5 filtercube (Semrok). Images were captured with a Lumenera 3 camera using Infinity Analyze 6.0 software.FlowJo X software package and custom made MATLAB-based software Label_It developed in our lab. The background fluorescence was eliminated by adjusting the gain of the corresponding photomultiplier tubes (PMTs) in the flow cytometer. The scale was set by adjusting the position of the maximum of non-treated beads to zero. Samples of the unconjugated (unlabelled) and saturated beads were run to set the gain of the PMT at the relevant channel. An argon ion laser (637 nm) and a 660/20-nm bandpass filter were used for fluorescence measurements.Flow cytometry experiments were performed using a multichannel flow cytometer (Beckman Coulter). The results were processed with Label_It software by fitting a histogram , and c is the width of the peak. We used established metrics for evaluation of bimodal histograms based on fitting of the histogram distribution. This include Peak Mean Distance (I), defined as a gap between two peaks, Stain Index (SI)Db)The goodness of fit was judged by visual observations, residual plots, R-square value, which typically exceeded 0.96, and RMSE. The output provided the heights, means, and widths for each peak: where the parameter I, SI and DB. We found that for a typical 10,000 events, the value 5 < N < 20 provides the best fit across a variety of dye-conjugates. We also found that I provides a more stable and predictable metric compared to SI or DB and bins width  were set automatically. The two parameters can be also adjusted to obtain the best fit as judged by R-square or RSME values.  SI or DB.BI, SI, D and found I is preferable. The difference between I and other metrics such as SI and BD, is that the latter take into account standard deviations. These standard deviations are calculated from fitting of the flow cytometry histogram with a bimodal Gaussian-type distribution. Although this fitting provides appropriate R-square values (>0.9), it is not very accurate at highly overlapped or well separated peaks. Parameter I is less dependent from standard deviation and appears to be more robust with lower variability .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Antiretroviral therapy has increased longevity for people living with HIV (PLWH). As a result, PLWH increasingly experience the common diseases of aging and the resources needed to manage these comorbidities are increasing. This paper characterizes the number and types of comorbidities diagnosed among PLWH covered by Medicare and examines how non-HIV comorbidities relate to outpatient, inpatient, and pharmaceutical expenditures.The study examined Medicare expenditures for 9767 HIV-positive Californians enrolled in Medicare in 2010 . Costs included both out of pocket costs and those paid by Medicare and Medicaid. Comorbidities were determined by examining diagnosis codes.Medicare expenditures for Californians with HIV averaged $47,036 in 2010, with drugs accounting for about 2/3 of the total and outpatient costs 19% of the total. Inpatient costs accounted for 18% of the total. About 64% of the sample had at least one comorbidity in addition to HIV. Cross-validation showed that adding information on comorbidities to the quantile regression improved the accuracy of predicted individual expenditures. Non-HIV comorbidities relating to health habits—diabetes, hypertension, liver disease (hepatitis C), renal insufficiency—are common among PLWH. Cancer was relatively rare, but added significantly to cost. Comorbidities had little effect on pharmaceutical costs, which were dominated by the cost of antiretroviral therapy, but had a major effect on hospital admission.Comorbidities are prevalent among PLWH and add substantially to treatment costs for PLWH. Many of these comorbidities relate to health habits that could be addressed with additional prevention in ambulatory care, thereby improving health outcomes and ultimately reducing costs. Care for people infected with HIV has traditionally focused on optimal management of HIV infection and ensuring access to providers with specialty knowledge of HIV care. The success in managing HIV infection has led to increased survival for people living with HIV (PLWH), with the result that in 2014 45% of Americans diagnosed with HIV were aged 50 and older.[Non-HIV comorbidities are common among those infected with HIV, particularly among Medicare and Medicaid enrollees. –12 The pMultimorbidity is also common among PLWH. Insurance claims data show that among PLWH aged 50 and older, 22% had one medical condition in addition to HIV, 36% had 2–3 comorbidities, 15% had 4–5, and 10% had >5. There isAs care for HIV infections has matured and PLWH are living longer without AIDS, the resources needed to manage and treat their non-HIV comorbidities have increased in importance. One measure of these resources is the cost of treating these comorbidities, which adds to the substantial costs of HIV/AIDS treatment. Historically, overall costs of HIV treatment have been driven largely by the high costs of antiretrovirals and of hospitalizations.,18 In reThis paper seeks, first, to characterize the number and types of comorbidities diagnosed among publicly-insured PLWH covered by Medicare. Secondly, we examine how comorbidities predict outpatient, inpatient and pharmaceutical expenditure.Insurance claims data for HIV-positive Californians enrolled in Medicare in 2010 were acquired through a confidential data use agreement with the Center for Medicare and Medicaid Services (CMS). The sample includes Medicare beneficiaries enrolled in both Medicare (the primary payer) and Medicaid  as well as those enrolled solely in Medicare (Medicare-only). We applied a case-identification algorithm to create an analysis file of adult beneficiaries with verifiable HIV. [Data acquisition was reviewed and approved by the CMS Privacy Board. The UCLA Institutional Review Board (UCLA IRB #10–000823) reviewed the study and deemed it exempt. Data were obtained in research identifiable files; storage, analysis, and reporting met CMS data security requirements.This analysis separately examines health care expenditures for outpatient services, pharmaceuticals, and inpatient services. Expenditures included all costs reimbursed by Medicare and Medicaid plus costs paid by the patient (e.g. deductible and coinsurance) in each category. Thus pharmaceutical costs include patients’ payments in the “doughnut hole” phase, where Medicare does not reimburse for drug purchases.Diagnoses were grouped using the typology of 26 comorbidities developed by Elixhauser.,22 An inCMS enrollment data provided information on participant age, race, and gender. Reason for Medicare coverage was coded as “disability” or other (e.g. aged). RUCA coding was used to determine urban or rural designation based on participant’s zip code. An individual’s access to an HIV specialist was indicated by whether they had an evaluation and management visit with any provider who treated 50 or more Medicare or Medicaid HIV patients in California in 2010.R in the quantreg package [Mean and median medical costs were calculated by number of comorbidities. Multi-variable methods were used to examine the effect of a given chronic disease on median costs, net of other comorbidities and demographic factors. We use quantile regression to examine median expenditures, where the goal is to minimize the absolute difference between actual and predicted costs. In order to examine the percentage increase in medical costs, we made a logarithmic transformation of each individual’s expenditure. Analyses were carried out using  package More than 99% of the sample used outpatient care and had pharmaceutical claims in 2010. In contrast, only a minority of patients were hospitalized in 2010 . Therefore, we used logistic regression to relate each comorbidity to the probability of hospitalization, holding demographic factors and other comorbidities constant.We fit quantile-regression models to estimate the relationship between the demographic and comorbidity variables and the median logged outpatient and drug spending. InpatienWe estimated a variety of alternative models and used cross-validation to select the model that minimized the mean absolute error (MAE) between the predicted and the observed values for outpatient and drug costs. By assessing the models in terms of MAE, rather than root mean square error (RMSE), we obtain a cost prediction for the typical patient. In contrast, predictions from estimating models that minimize RMSE tend to overestimate costs for the majority of patients in order to reduce prediction errors for the small percent of very high cost patients.We compared observed costs at the individual level to costs predicted by models with no covariates, only demographic variables and with both demographic and comorbidity measures. This provided a test of whether comorbidities have predictive value beyond that of the demographic variables alone. For outpatient and drug costs we examined whether separate models for Medicare-only beneficiaries and dual beneficiaries predicted costs better than a single model that included a dummy variable distinguishing these beneficiary types. Thus, we compared 6 models (3 sets of independent variables for both separate and combined modeling of beneficiary type).Inpatient costs were estimated with a two-step procedure. A logistic-regression predicted the probability of having nonzero inpatient costs and a quantile-regression predicted the median expenditure, conditional on having nonzero inpatient costs. The 9 models we compared crossed 3 different sets of independent variables for the logistic model with the same three sets for the quantile regression model.We assessed each model with tenfold cross-validation by randomly assigning patients to one of ten folds (subsamples), then predicting costs for each patient in each fold. We then calculated the mean absolute error (MAE) between the predicted and observed cost for each patient We assessed prediction accuracy based on the mean of these MAEs.The majority of this sample of PLWH who are enrolled in Medicare are male (90%) and between the ages of 41 and 60 (72%). . Whites The mean Medicare expenditure for California enrollees with HIV was $47,036 in 2010 . Drug coComorbidities were common . About 6Mean and median per capita total expenditures for individuals with each comorbidity group are also shown in An individual can have more than one comorbidity, thus we examine net costs of each comorbidity in a multi-variable framework that controls for the presence of other comorbidities as well as demographic factors.Quantile regression was used to relate logged expenditures for each of the cost components  to demographic factors and presence of comorbidities. . LogistiEach comorbidity coefficient can be interpreted as the percentage increase in median spending associated with this comorbidity compared to a non-disabled, white, urban, male Medicare-only enrollee of mean age with no other chronic conditions, who did not visit a high volume provider (50+ HIV patients).Every comorbidity examined increased the cost of outpatient treatment. While obesity and uncomplicated diabetes had modest effects on outpatient costs, , all three cancers added substantially to outpatient costs. In contrast, pharmaceutical expenses were relatively insensitive to individual conditions, except in the case of hemophilia.The median inpatient cost differential associated with each comorbidity varied over a wide range. Logistic regressions  show thaMedian outpatient costs also varied by patients’ demographic characteristics. Hispanic PLWH incurred lower median cost for outpatient services, while African-Americans had lower costs for both outpatient services and drugs. Female PLWH had about 19% higher outpatient costs, but their medication costs were only 89% of males’. Age did not have a large effect, net of other demographics and comorbidities. Dual enrollees, with both Medicare and Medicaid coverage, had median outpatient costs that were 21% greater than Medicare-Only patients. Patients with high volume providers had slightly higher outpatient and drug costs  than patients with lower volume providers.The findings of this paper describe how medical complexity dramatically increases the already high baseline costs of care for PLWH. In our sample of Medicare enrollees with HIV, nearly 2/3 (64%) had at least one non-HIV related condition, and 39% had two or more. Mean costs of care increased from $30,312 for those without an identified comorbidity to over $46,000 for those with 2 comorbidities, and up to $219,000 for people with 11 or more. Our data confirm that the greater prevalence of comorbidities with increasing age of HIV-infected patients primarily accounts for increased inpatient and outpatient costs with age.The prevalence of comorbidities likely will increase with the aging of the PLWH population. For example, a modeling study in the Netherlands projects that the percentage of HIV-positive Dutch patients who are over 50 will increase from 28% in 2010 to 73% in 2030. The authors predict that 84% of Dutch HIV-infected patients in 2030 will have 3 or more non-communicable diseases—mostly cardiovascular. Thus theIn the current analyses, pharmaceutical costs account for the greatest share of costs for PLWH, but are largely insensitive to comorbidities because the high cost of ART overshadows the cost of drug treatment of other comorbidities. Our data show that drugs account for a 64% of total average costs versus 18% for inpatient costs, continuing the pattern initiated when HAART first came into wide use. HAART imEvidence suggests that patients with HIV have greater numbers of health conditions than age-matched controls. ,13 ConsiIn contrast to their moderate effect on pharmaceutical costs, comorbidities are associated with increases in median hospital and ambulatory care costs in the PLWH population. Historically, the development of ART dramatically lowered inpatient costs by reducing hospitalization rates for PLWH. Hospitalized PLWH are now more likely to die of conditions other than AIDS  than of HIV-related conditions, having increased from 43% of hospital deaths among PLWH in 1995 to 70.5% of such deaths in 2011. Our findThis analysis is unique in looking at a range of non-HIV diagnoses to isolate the effect of each diagnosis on the resources used to treat PLWH. Our analysis examines a broad range of comorbidities, not just one, as in Yanik.  The mostEvidence of the relative contribution of lifestyle factors to morbidity among PLWH is beginning to accumulate. Some havThis paper has a number of limitations. First, the data relate only to California and may not generalize to other states. Secondly, only 20% of all PLWH have Medicare coverage.  Finally,The aging of the population with HIV will increase the widespread prevalence of comorbidities among PLWH, adding to the already high costs of treatment for this population. We have shown that including comorbidity measures in predictions of future medical expenditures for PLWH will improve the accuracy of the spending forecasts. Many of the comorbidities that PLWH live with relate to potentially modifiable health habits. However, it may be difficult for providers to effectively provide interventions to modify negative health behaviors because of the small share of HIV care resources devoted to outpatient services.


Oropouche virus (OROV) is an important cause of arboviral illness in Latin American countries, more specifically in the Amazon region of Brazil, Venezuela and Peru, as well as in other countries such as Panama. In the past decades, the clinical, epidemiological, pathological, and molecular aspects of OROV have been published and provide the basis for a better understanding of this important human pathogen. Here, we describe the milestones in a comprehensive review of OROV epidemiology, pathogenesis, and molecular biology, including a description of the first isolation of the virus, the outbreaks during the past six decades, clinical aspects of OROV infection, diagnostic methods, genome and genetic traits, evolution, and viral dispersal. Oropouche virus (OROV) is one of the most common arboviruses that infect humans in Brazil. It is estimated that since the first isolation of the virus in 1955, it has affected more than half a million people. However, the exact number of cases is difficult to determine, because the infection is underreported due to the similarity of symptoms with other arboviral febrile illnesses, such as Dengue, Zika, Chikungunya, and Mayaro fevers. The lack of an exact diagnosis in hospitals and health-care centers hinders the proper epidemiological notification, which is the principal reason why the estimated number of cases is lower than what is probably occurring in the population, especially in the Amazon-endemic region.Coquillettidia venezuelensis  mosquitoes collected in Bush Bush Forest, Nariva Swamp, Trinidad, on October 18, 1960. This second strain (TRVL 35111) was antigenically closely related to the prototype strain TRVL 9760 by complement fixation (CF) and neutralization (NT) tests.Bradypus trydactilus, captured in a forested area during the construction of the Belém-Brasilia highway and also from a pool of Ochlerotatus serratus mosquitoes caught near the same area.OROV is the causative agent of Oropouche fever, a febrile arboviral illness that is frequently associated with the Brazilian–Amazon region.ain TRVL 5111 was In the following year, the virus was again detected in Belém City, the capital of Pará State, northern Brazil. On that occasion, a large epidemic of Oropouche fever was reported in Belém with an estimated 11,000 people affected.6More recently, OROV was reported in the municipalities of Parauapebas, Porto de Moz, Igarapé Açu, Magalhães Barata, and Maracanã, in Pará State, northern Brazil; the last three were located in the Bragantina area, the region where the virus was first detected in 1970.9In this report, we review the past 60 years of OROV research, providing a brief overview of some of the key milestones that have been achieved since the original isolation of the virus , medium (MRNA), and large (LRNA), according to their respective molecular sizes. The partial viral genome for the Brazilian prototype OROV strain BeAN 19991 was sequenced, and recently the complete genomic sequences for the three segments, including the full noncoding regions (NCRs) was described, showing a SRNA segment of 958 nucleotides, a MRNA with 4,385 nucleotides and a LRNA with 6,852 nucleotides in length (The LRNA contains one open reading frame (ORF) that encodes the L protein, an RNA-dependent RNA polymerase. The L protein has a molecular weight of 261.25 kDa and is associated to the three viral RNA segments.25The details of the OROV replication cycle are still unknown. Progeny production is observed 10 hours postinoculation of the virus in HeLa cells, with a peak after 24 hours.26One important cytopathic effect observed after OROV replication in HeLa cells is the induction of apoptosis, which was detected at 36 hours postinfection.Thus far, the only reported cases of Oropouche (ORO) fever have occurred in Brazil, Panama, Peru, and Trinidad and Tobago. In Brazil, since the first isolation of the virus in 1955 until 1980, OROV caused several epidemics apparently restricted to the State of Pará, northern Brazil, reaching different municipalities of distinct mesoregions: metropolitan area of Belém ; northeast ; southeast (Itupiranga); lower Amazon ; and Marajó Island (Porto de Moz). During this period, only the southwest mesoregion did not report cases or ORO fever.30Callithrix penicillata) on two different occasions in Minas Gerais State, southeast Brazil.31Between 1981 and 1996, outbreaks of ORO fever were registered in the state of Pará ; as well as in other states, such as in the cities of Manaus, Novo Airão, and Barcelos (Amazonas State), Mazagão (Amapá State), Xapuri (Acre State), Ariquemes, Machadinho, and Ouro Preto d'Oeste (Rondônia State), Porto Franco and Estreito (Maranhão State), and Tocantinópolis (Tocantins State).In 2003 and 2004, outbreaks of ORO fever were detected in the municipalities of Parauapebas, Pará State (mesoregion east) and Porto de Moz (middle region of the lower Amazon), respectively.9Outside of Brazil, epidemics have been reported in Panama and Peru. The outbreak in Panama was recorded in 1989 in the Village of Bejuco, located approximately 50 km west of Panama City, capital of the country. In Peru, ORO fever was documented in 1992, when the virus caused an outbreak in Iquitos City.32Culicoides paraensis can be found.3ORO fever cases have been reported in different locations in a large geographical area, including both in South and Central Americas. During outbreaks, a representative epidemic dispersion process is observed, with transmission to several locations situated close to the region where the virus was first detected. This phenomenon was observed in outbreaks that occurred in several municipalities in the states of Pará and Rondônia, Brazil.Culicoides paraensis during previous rainy period. Furthermore, the occurrence of outbreaks is also related to the increase of susceptible human population not previously exposed to the virus. In general, decreasing of outbreaks is associated with the beginning of the dry season and the decreasing of midge density.16ORO fever occurs predominantly in the rainy season, due to the increase in the breeding sites of the vector population. In Brazil, more specifically in the Brazilian Amazon region, the dry season corresponds to the months from July to December, whereas the rainy season occurs between January and June.Bradypus tridactylus), nonhuman primates and some wild birds play a role as vertebrate hosts.31Studies conducted by the Evandro Chagas Institute suggest that OROV is maintained in nature by two distinct cycles: sylvatic and urban , regionally named as “maruim,” and the mosquito Culex p. quinquefasciatus (Culicidae). In laboratory experiments with the Culex p. quinquefasciatus, the insect proved to be an inefficient vector of OROV.Culex quinquefasciatus, reinforcing the probable participation of Culex mosquitoes in the urban cycle of OROV.35In the urban or epidemic cycle, humans apparently are the only vertebrates involved, since studies with domestic animals  excluded the role of these animals in the maintenance of the urban cycle.Culicoides paraensis to transmit the virus to hamsters after five or more days feeding on blood of viremic patients. These midges have diurnal activity, especially during the twilight period, and are aggressive bitters that are attracted by humans. Culicoides paraensis, small insect, is widely distributed in tropical and subtropical areas of the Americas, and is usually found in high density during epidemic periods. The larvae feed on decomposing organic materials, such as trunks of banana trees (genus Musa), fruits husks of coconut (Cocos nucifera), and Cupuaçu (Theobroma grandiflorum) trees, as well as in accumulated debris of trees.36The involvement of the biting midge as a vector of OROV is based on experimental studies carried out by Pinheiro and others.Culicoides paraensis during epidemics is an intriguing problem. Further studies are necessary to determine if this phenomenon is due to the low susceptibility of the insect to OROV, or if only a small fraction of Culicoides paraensis population has the ability to transmit the virus.37However, the low isolation rate of the virus from There is no precise information about the incubation period of ORO fever; however, some observations made during major epidemics suggest that it may vary from 4 to 8 days. In 1981, Pinheiro and others described two laboratory technicians who were accidentally infected with OROV, and showed ORO fever symptoms 3–4 days after infection.16Culicoides paraensis for the first 3–4 days from the onset of symptoms, when viremia is high enough to infect biting midges. Experimental studies in hamsters (Mesocricetus auratus) demonstrated that the extrinsic incubation period is five or more days.33The patient's blood in the acute phase of the illness is infective to the In general, the estimated incidence rates for OROV infection have been determined by seroepidemiological surveys, where groups of families were randomly selected. In this case, a clinical–epidemiological survey was applied to members of each family, and blood samples were collected for virus isolation (acute phase) in newborn mice 2–3 days old) and Vero cells, as well as for the detection of NT, CF, HI, and IgM antibodies . days old30Although the incidence values have not been determined in some outbreaks, a relevant feature of ORO fever is related to a large number of OROV infections reported in all epidemic episodes described so far. Based on official records, the overall cases of ORO fever were estimated at 380,000 cases during the period from 1961 to 2007. It is important to note that in several outbreaks the uniformity in the numerical distribution of cases, as well as in the estimated incidence of cases was not homogeneous. Indeed, the average incidence rate was estimated as 30%. In one of the described epidemics, the proportion of infected individuals showing clinical symptoms of OROV infection reached 63%.28Regarding gender, rates of OROV infections are quite varied. In 1979, during the outbreak in the Bragantina area, northeastern Pará State, females were the most infected group. On the other hand, in the same year, another outbreak occurred in Belém City, where males were the most affected.27N gene of 28 OROV strains isolated from different hosts, geographical locations, and different periods of time, it was reported that genotype I was only detected in Trinidad and Tobago, whereas genotype II was restricted to Peru, and genotype III was found in Panama only. In Brazil, only genotypes I and II were detected: genotype I was more often found in eastern Amazon, whereas genotype II in western Amazon region.40The first genetic study carried out with OROV was described by Saeed and coworkers in 2000 and introduced the basis for understanding the molecular epidemiology of this viral agent. It suggested the existence of at least three distinct circulating genetic lineages in the Americas: genotypes I, II, and III.Callithrix sp.) in the municipality of Arinos, Minas Gerais State, southeastern Brazil, and this isolate was classified as genotype III, previously found only in Panama. This finding reinforced the hypothesis that OROV has encountered favorable ecological conditions to allow its spread to other regions outside the original epidemiological area in the Amazon region. Furthermore, this also opened the possibilities for the virus to spread into highly susceptible populations that were residing in these urban areas, increasing the risk of outbreaks.41In 2000, a strain of OROV was isolated from a new vertebrate host  demonstrated the co-circulation of genotypes I and II and their association with ORO fever cases.In the present study, the appearance of a fourth genotype, based on information obtained from genetic data for the SRNA segment was observed. This new phylogenetic group, isolated from humans during an outbreak in Manaus in the 1980s, was called genotype IV.N gene sequences (3.7 × 10−4 substitutions per site per year), and we used this information to calculate the divergence dates among the strains. The most recent common ancestor for OROV in the Americas was estimated to have emerged around 223 years ago (95% highest probability density [HPD]: 148–342 years) generating the four different genotypes  that are currently described. Detailed analyses suggest that genotype I was the ancient genotype emerging ∼112 years ago (95% HPD: 95–189 years), whereas genotype II subsequently emerged ∼91 years ago (95% HPD: 59–144 years) and was probably originated from strains isolated in the states of Pará and Rondônia, as well as from strains recently isolated in the Amapá State, in 2009. Genotype IV emerged in the Amazonas State ∼43 years ago (95% HPD: 31–56 years) and genotype III was considered the latest lineage to emerge in Brazil, about 37 years ago (95% HPD: 33–70 years) probably in the Rondonia State 33 years ago (95% HPD: 29–58 years), and in other states from Amazon region , and emerging almost simultaneously in Panama about 32 years ago (95% HPD: 22–45 years) and, more recently, in Minas Gerais State, out of the official endemic area of OROV transmission  and epidemiologic data association (date and geographic location of isolation), the possible dispersal event could be predicted for the distinct OROV genotypes in the Americas. Genotype I , possibly spread continuously toward distinct regions: initially to several municipalities in western Pará State, and almost simultaneously in Trinidad and Tobago. Later, genotype I moved toward the states of Amazonas and Acre and finally to the eastern Amazon region including Pará, Maranhão, and Tocantins States. Genotype II apparently emerged simultaneously in the states of Amapá, Pará, and Rondônia, as well as in Peru, and dispersed in these places, emerging in the municipality of Mazagão, Amapá State, in 2009. Genotype III emerged in Rondônia State, moving toward Panama and the states of Acre and Maranhão in Brazil, and lately to Minas Gerais State. Genotype IV, apparently more ancient than genotype III, emerged in the city of Manaus, Amazonas State, and apparently is still restricted to that area.Based on results obtained for the Cebus olivaceus Schomburgk) in a forest near Atapirire, a small rural village located in Anzoategui State, Venezuela.Callithrix sp.) found dead in Minas Gerais State, Brazil.Genomic reassortment is considered to be one of the most important mechanisms for the generation of viral biodiversity in orthobunyaviruses. This phenomenon can occur when two genetically related viruses infect the same susceptible cell at the same time, and the progeny virus can be formed containing a varied mixture of genomic L, M, and S segments from the two parental viruses. This phenomenon, which is also common with segmented viruses from other families, can have significant implications due to the possibility of the emergence of a virus with increased pathogenicity. The exchange of genomic RNA segments involving OROV have been reported in isolates obtained from Peru, Venezuela, and Brazil. The first reassortment event was reported in Peru when the Iquitos virus (IQTV) was isolated in 1999 from a febrile patient.Infections in humans caused by OROV are characterized as an acute febrile illness, usually accompanied by headache, myalgia, arthralgia, anorexia, dizziness, chills, and photophobia . Some pa45Since fatalities have not been recorded, little is known about the pathogenesis of natural OROV infections. Humans present systemic symptoms, with viremia detected in the initial 2–4 days of the onset of the first symptoms. In some patients, the virus has been recovered from the cerebrospinal fluid, but the route of invasion of the CNS is unknown.46Studies using experimental animal models have helped to elucidate some aspects of the pathogenesis of OROV. In 1978, Araujo and others demonstrated that viruses could be detected in liver lesions with significant necrosis of hepatocytes and considerable hypertrophy of Kupffer cells 6 hours after OROV was inoculated intracerebrally into 3-week-old hamsters, suggesting a hematogenous transmission of the virus from the brain to the liver.396.0 TCID50/mL at the 3rd day after infection.48A more detailed infection model in hamsters using viruses inoculated subcutaneously demonstrated the occurrence of systemic infection, with high viral load in the plasma, that can reach a peak of 10The pathogenesis of OROV was also studied in murine models. BALB/c neonate mice inoculated subcutaneously presented clinical signs at the 5th day after inoculation. The animals presented a high concentration of replicating virus in the brain, with inflammation of the meninges and apoptosis of neurons, apparently without encephalitis.47Studies based on subcutaneous inoculations of OROV in wild type and mutated immunocompromised C57BL/6 mice revealed that induction of type I IFN pathway through mitochondrial antiviral-signaling protein, interferon regulatory transcription factor 3 and 7, and interferon-α/β receptor is essential to control OROV infection, and this likely occurs dominantly in nonmyeloid cells.50Diagnosis of OROV infection is basically made using classic and molecular virology techniques: 1) virus isolation attempt in newborn mice and cell culture (Vero cells); 2) serologic assays, such as HI, NT, CF tests, and in-house-enzyme linked immunosorbent assay for total immunoglobulin, IgM and IgG detection, respectively, in convalescent sera; 3) reverse transcription polymerase chain reaction (RT-PCR) and real-time RT-PCR for genome detection in acute samples .Escherichia coli bacterial system. This antigen was tested in IgM enzyme-linked immunosorbent assay (ELISA) assay in clinical samples from patients infected by the OROV in Brazil and Peru.In 2001, Saeed and others engineered the first nucleocapsid recombinant protein antigen using a plasmidial Bunyaviridae and its effects. Since the M segment is the only viral genomic segment that is different between MMDV, IQTV, and PERDV reassortants, the system could be used to generate recombinant viruses and study the differences they present in terms of pathogenesis, virulence outcome, and host range, which could elucidate important implications on the understanding of the evolution of orthobunyaviruses in South America. The virus-like particles assay developed for this virusOROV is one of the most important orthobunyaviruses associated with human diseases in tropical America, with more than 30 major outbreaks and half million reported cases since its first isolation in 1955. In this review, we discussed the major breakthroughs achieved in OROV research. However, there are many more questions that need to be addressed to fully understand the epidemiology and pathogenesis of this virus. The reverse genetics system developed for OROV


Furthermore, tobacco mosaic virus was recently shown to replicate in a filamentous ascomycetous fungus. Thus, at least experimentally, some plant viruses can infect some fungi. Endophytic fungi have been reported from many plants and several of these fungi have been shown to contain viruses. Here we tested if mycoviruses derived from a marine plant endophyte can replicate in plant cells. For this purpose, we used partially purified viral particles from isolate MUT4330 of Penicillium aurantiogriseum var. viridicatum which harbors six virus species, some having dsRNA and some positive-strand ssRNA genomes. These were transfected into three distinct plant protoplast cell systems. Time-course analysis of absolute RNA accumulation provided for the first time evidence that viruses of two species belonging to the Partitiviridae and Totiviridae families, can replicate in plant cells without evidence of host adaptation, i.e, changes in their nucleotide sequence.So far there is no record of a specific virus able to infect both fungal and plant hosts in nature. However, experimental evidence shows that some plant virus RdRPs are able to perform replication  Viruses comprise a heterogeneous group of microorganisms; their diversity suggests multiple origins of viruses and thus they have no conserved sequence that can be used for general detection of undescribed species. Nevertheless, metagenomics approaches and new bioinformatics tools have increased exponentially our ability to detect and describe new viruses4. Thanks to these approaches new viral species from metagenomics samples were described helping to enrich the virus taxonomic framework. An example of how metagenomics is rapidly changing our perception of the viromes associated with higher organisms was recently shown for the invertebrate virosphere4.Interest in viruses is mostly based on their ability to cause disease in plants, animals and humans, but in recent decades their role in mutualistic symbiosis has been shown4. Further interesting data come from metagenomics studies of plant samples in natural environments. The most abundant species identified belong to the families Totiviridae, Partitiviridae, Endornaviridae and Chrysoviridae5. Recently, also a circular single stranded DNA virus in the Genomovirus genus was shown to replicate both in insect and fungal cells6. All the above mentioned families have members which are reported as persistent plant viruses lacking the typical movement protein but able to replicate in meristematic cells leading to their ability to infect all plant tissues; specific members of these taxonomic clades can also infect fungi7 but none of the distinct viral species in these families have been shown to be able to infect both plants and fungi. It is important to note that several of these viruses are from endophytic fungi, thus they reside in fungal hosts which reside in plants. A link between plant viruses and mycoviruses was for the first time shown for viruses of the Hypoviride family: analysis of protein sequences revealed that hypoviruses share a common ancestor with the plant-infecting Potyviruses8. In addition, a still unrecognized group of viruses formed by Ourmia-like fungal viruses9, plant ourmiaviruses10, and a number of new species of still undefined host constitute a well-supported clade in phylogenetic analysis11. Two other families that show a wide mosaic of hosts are Bunyaviridae12 and Reoviridae13. In these two families we can find viruses infecting animals (vertebrate and invertebrate), plants and fungi. This evidence suggests the possibility that common host cellular machinery for virus replication is shared between these different hosts.This enriched taxonomic framework shows a number of clades (often at the family or genus taxonomic level) which have as hosts a mosaic of species belonging to different kingdomsNarnaviridae. This family of mycoviruses is divided into two genera based on subcellular localization: Narnavirus, which has members that are cytosolic viruses infecting yeasts and oomycetes, and Mitovirus which has members which are mitochondria-confined viruses found only in fungi14; however, some mitovirus sequences have been found to be endogenized into plant genomes with almost complete sequences suggesting one or more integration events of fungal mitoviruses into the chromosomal DNA of vascular plants15.Further evidence of relationships between fungal and plant viruses comes from the family Saccharomyces cerevisiae16. Another example comes from work showing the ability of two replicase proteins, p33 and p92, of tomato bushy stunt virus (TBSV) to maintain and replicate virus-associated defective interfering (DI) RNAs17. This evidence has confirmed that at least these plant viral RdRPs can function in yeast cells. Another recent work reports evidence of tobacco mosaic virus (TMV) replication in three species of fungi in the genus Colletotrichum18. Overall, these data seem to confirm that some plant viruses can replicate in cells of different ascomycetous species. These experiments were stimulated by the aim to use a genetically treatable host such as yeast for plant viruses19.Experimental evidence of the ability of viruses to adapt their replication machinery to host cells of species belonging to different kingdoms are already present in literature. The first example was shown by the ability of brome mosaic virus (BMV) to replicate in the yeast, 2 we reported 12 new mycovirus species isolated from a collection of marine fungi associated with the marine plant Posidonia oceanica21. One isolate of this fungal collection, Penicillium aurantiogriseum var. viridicatum, MUT4330, was shown to harbor six distinct proposed virus species including a fusari-like virus, Penicillium aurantiogriseum fusari-like virus 1 (PaFV1), a Totivirus, Penicillium aurantiogriseum totivirus 1 (PaTV1), a +stranded RNA virus named Penicillium aurantiogriseum foetidus-like virus 1 (PaFlV1) due to its similarity to Aspergillus foetidus slow virus 2, a bipartite virus named Penicillium aurantiogriseum bipartite virus 1 (PaBV1), a Partitivirus, Penicillium aurantiogriseum partitivirus 1 (PaPV1), and a virus with low similarity to the family Partitiviridae named Penicillium aurantiogriseum partiti-like virus 1 (PaPlV1). With a simple protocol we were able to isolate and enrich for particles of several viruses belonging to different taxonomic clades and with both dsRNA (4 viruses) and (+) ssRNA genomes (2 viruses); four viruses encode for a CP and are therefore purified as virions ; a fifth ssRNA virus (PaFlV1) is likely encapsidated by PaTV1, as it is the case of the Yado-kari virus22.Despite these reports of plant viruses replicating in fungal cells, surprisingly, to date there are still no reports on replication of mycoviruses in plant cells. This is surprising particularly in light of the fact that viruses infecting fungal endophytes must also be continuously exposed to the plant cells which are hosts for the fungus. For this reason we decided to test the ability of a number of representative mycoviruses to infect plant cells. In previous workNicotiana benthamiana because it is the model plant for virus-host interaction. N. benthamiana displays a well-studied general susceptibility to plant virus infections25 that makes it the ideal species for our experimental setup. The second experimental system to test mycovirus replication is based on protoplasts derived from N. tabacum bright yellow 2 (BY2) cell line27, a very reliable plant cell system that can be maintained indefinitely and from which protoplast can be easily obtained in axenic conditions and monitored for virus accumulation for up to 6–7 days.From an evolutionary perspective, two are the requirements for a fungal virus to become a “bona fide” plant virus: i) the virus must be able to replicate in plant cells, and ii) the virus must acquire the ability to infect systemically the host plant. Systemic infection relies fundamentally on two strategies: ability to infect meristematic tissue (a strategy employed by cryptoviruses) or acquisition of a movement protein (a strategy employed by most plant viruses). Here we will test the first step of this evolutionary scenario, i.e. ability to infect plant cells. In order to avoid the movement components, we choose to work with plant protoplast systems, and in specific we choose N. benthamiana and N. tabacum BY2 cell line.We are here reporting the first evidence that two “bona fide” mycoviruses replicate in protoplasts of two different plant hosts, P. aurantiogriseum (isolate MUT4330) and transfect them to plant protoplasts. We decided to perform our experiment using protoplasts from N. benthamiana, a model plant for virus-host interaction, due to its wide susceptibility to plant virus infection25. In each experiment we analyzed three different transfection events for each time point of a time course. The T0 time point is representative of the virus RNA associated to the protoplast at the time of inocula . The T48 time point is the upper time limit for N. benthamiana protoplasts before a dramatic decrease in cell viability is observed (not shown). We decided to use the same T48 time point also for BY2 cells, in order to compare directly the two systems.In order to test if mycoviruses can replicate in plant cells, we decided to enrich and partially purify virus particles from a single monoconidial isolate of The partially purified virus suspension was filtered through a 0.22 μm mesh filter before transfection and an aliquot of the suspension was layered on fungal culture media in order to rule out the presence of contaminating mycelia in the protoplasts.N. benthamiana WT protoplasts the only virus able to increase the amount of RNA in absolute terms between the T0 time point and the T48 time point is the totivirus PaTV1 . Another ssRNA virus (PaFV1) shows also limited decrease in RNA accumulation, likely because of its protection from anti-viral RNAse activity in host derived membranes, as it is the case of other members of the Hypoviridae family28.Maintenance of a relatively high level of viral RNA in transfected plant protoplast 48 hours after transfection could be due to protection from RNAse degradation provided by the virion .The internal control 30: a further evidence of true viral replication would come from showing that in the presence of a silencing suppressor, virus accumulation increases specifically31. For this purpose, protoplasts for transfection were derived from a transgenic line of N. benthamiana expressing a silencing suppressor (HC-Pro) from Turnip mosaic virus (TuMV) shown to be able to enhance plant viral replication32. In this experiment we transfected side by side WT and HC-Pro protoplasts using the same virus preparation and then compared results. As previously observed, in WT plants the absolute RNA amount of PaTV1 was 5 times higher at T48 than at T0. By contrast, in HC-Pro protoplasts the amount was 15 to 20 times higher than at T0   we decided to test also tobacco BY2 cells to compare to the data observed using ies Fig. .Figure 3N. benthamiana WT and N. tabacum BY2 protoplasts. For both experiments we observed replication for PaTV1 only in protoplasts transfected with the untreated viral inocula  with untreated inoculum in ula Fig. . By contHypoviridae family – a family of capsid-less viruses-, could only partially be concentrated with the protocol we used (more oriented to virus species possessing true virions). For this reason we decided to test if another virus belonging to the Hypoviridae family, and to the species Cryphonectria hypovirus 1 (CHV1), was able to replicate in BY2 cells: in this case we could bypass the inefficiency of our concentration protocol because we can take advantage of an infectious cDNA clone that can be used for the synthesis in vitro of full length viral RNA33.Among the six virus species present in the fungal isolate used as source for virus inoculum, one species, PaFV1, a fusari-like virus closely related to the C. parasitica protoplasts, and resulted in CHV1 infected C. parasitica isolates (not shown).Real time PCR data clearly show that CHV1 was not able to replicate in BY2 cells bringing to complete clearance of the infectious transcript in 48 hours 37. However, in a few cases evidence of wider natural host ranges were reported: Botrytis porri virus 1 (BpRV1), a bipartite dsRNA mycovirus, originally detected in Botrytis porri was also found in B. squamosa and in S. sclerotiorum38. Because of the quasispecies nature of virus infection in an individual host, virus variants can quickly adapt to new environments39. For this reason, in the last few years, the classic hypothesis of a long coevolution history between mycoviruses and fungi is now flanked by the hypothesis that viruses can move easily from fungal host to new hosts belonging to unrelated (distant) taxonomic clades4. This latter hypothesis seems to fit cases in which fungi are in close physical relationship with other organisms, such as is the case of fungal-plant interface for plant pathogenic or plant endophytic fungi. In our case we can envision the possibility for a mycovirus associated to Posidonia oceanica endophytes to become a plant virus: nevertheless previous small RNA characterization from P. oceanica plants failed to reveal any virus infection2. Certainly evolutionary and phylogenetic analysis support viruses changing and adapting to new types of hosts. One recent example is that of a new mycovirus with a genomic sequence related to Hepatitis virus E which was reported from Sclerotinia sclerotiorum40, a plant pathogen. This suggests the possibility for inter-kingdom host jumps that can occur not only from fungi to plants and vice versa, but also from fungi to animals and vice versa.The diversity of mycoviruses was unknown or underestimated for many years and their importance in virus evolution has not been properly considered until recentlyPotyvirus8. Failure of CHV1 to replicate in plant cells can be explained by the fact that although it was the first mycovirus for which a phylogenetic link with plant viruses was shown, such a link is fairly distant, and in fact, the hypovirus-like clade does not harbor a mosaic of plant and fungal hosts, as is the case of the families Partitiviridae and Totiviridae41.A new evolutionary model that linked plant and fungal viruses was first proposed based on studies on the Cryphonectria hypovirus complex  which showed phylogenetic relationships of these viruses with plant-infecting viruses of the genus −ΔΔCt approach42 the fold change of replicating viruses was greater than considering absolute quantity  but in case of HC-Pro cells the final concentration was at least twice that present in WT cells. This is a further indication of viral replication, because, as expected, in presence of the HC-Pro RNAi suppressor, accumulation was greater. Moreover increase of the partitivirus PaPV1 RNA in HC-Pro protoplasts but not in WT protoplasts further confirmed replication. In fact active RNA silencing machinery present in WT plants can be the limit for potential viral replication preventing increase in viral RNA amount, becoming possible instead in the absence of this defense mechanism. Interestingly both mycoviruses replicating in plant protoplasts belong to two families, Partitiviridae and Totiviridae, that show a mix of plants and fungal hosts44. The two mycoviruses replicating in plant cells have both dsRNA genomes, and are encapsidated in isodiametric virions. Both genomes encode only for two proteins (the CP and the RdRp) in two distinct genome segments (for the partitivirus PaPV1) or in one genome segment through frameshift (for the totivirus PaTV1).The totivirus PaTV1 showed replication differences between Totivirus PaTV1 RNA, this virus seems to have a similar capability to replicate in N. benthamiana and N. tabacum cells. On the other hand the Partitivirus PaPV1, able to replicate only in HC-Pro but not in WT N. benthamiana cells, showed a good increase in RNA accumulation in BY2 cells. This result can be explained by host specificity. Both cell types come from plants of the genus Nicotiana, but they are different species and host specific components required for replication could play a role in host-specific response45.An interesting observation comes from the results observed in BY2 transfected cells. Comparing the ratio of initial and final amount of the N. benthamiana expressing red clover necrotic mosaic virus MP or tobacco mosaic virus MP complemented the ability of FHV to move systemically in these plants46. This experimental approach is supported also from the evolutionary point of view at least in the case of ourmiaviruses: this taxonomic group displays a chimeric genome, generated by the reassortment of at least two distinct viruses; the proposed hypothesis for the origin of this family is that a capsid-less narnavirus of a plant associated fungus became a plant virus acquiring movement protein (MP), and coat protein (CP) from other plant viruses, most likely from members of Tombusviridae10.Future studies on ability of mycoviruses to replicate in plants could entail whole organism experimental systems complementing the absence of a movement protein (MP) in mycoviruses: this approach was taken for Flock House virus (FHV), a (+)ssRNA insect virus: transgenic line of 4. With the report of more than 1400 new viruses, some of which are from host taxa previously unexplored, almost all the viral families that we previously thought to be host-specific are now showing a mosaic of hosts belonging to distant taxonomic clades suggesting that strict virus-host co-divergence cannot always be assumed. Clear example of viral cross-species transmission between different taxa was proposed for viruses of plants and arthropods4. Here in this work we reported for the first time the experimental evidence that these events can occur also for mycoviruses.Recent work on the characterization of the viromes of a number of invertebrate phyla deeply changed our understanding of the RNA virosphereP. aurantiogriseum var. viridicatum (MUT4330)20 was maintained on solid CYA prepared as previously described2. Virus inoculum was prepared by concentrating virus particle from fungus grown in liquid media, harvested after 72 hours of rotary shaking at 120 rpm and lyophilized, as previously described2. Inoculum was passed through a 0.22 µm filter to avoid any contamination of the virus suspension by fungal hyphae or conidia. At the time of transfection, an aliquot of the virus suspension was deposited on CYA solid media in order to rule out any fungal contamination post filtration.in vitro through T7 transcription of linearized plasmid pLDST as previously described33 and ability to infect was tested on Cryphonectria parasitica protoplasts.For CHV1, infectious RNA was obtained N. benthamiana seeds, WT or HC-Pro, were sterilized by washing in 70% ethanol for 5 minutes first and then 5% NaClO and Tween 20 0.1% for 15 minutes. Seeds were then washed 10 times with sterile water and sowed in Magenta boxes containing MS organic 0.44%, sucrose 1.5% and agar 0.7% supplemented with light 16 hours per day.myo-inositol, 0.2 mg/l 2–4 D) on a rotary shaker at 120 rpm and refreshed in new media with a ratio of 1/10 every 72 hours.BY2 cells were maintained in modified KMCS media  1.25%, Macerozyme  0.125% and Bovine serum albumin (BSA) 0.125%. Petri dishes containing leaves floating on the digestion mix were gently shaken at 65 rpm for 4 to 5 hours. Cells were sedimented in Corex tube by centrifuging 6 minutes at 100 g. Protoplast were then washed twice with 10% mannitol and then cleaned from cells debris on a 20% sucrose cushion. Protoplasts were counted and adjusted to 3 × 106/ml.Forty days after sowing, 2 5%, shaken for 10 seconds and later mixed in 1 ml of ice cold 10% mannitol. Thirteen minutes later, protoplasts were sedimented and resuspended in 1 ml of AOKI solution . Protoplasts harvested at T0 were sedimented again and stored at −80 °C; biological replicates harvested at T48 were sedimented and freezed at −80 °C before RNA extraction.For each transfection event 1 ml of protoplast suspension was distributed in sterile glass tubes and sedimented at 100 g for 3 minutes. Protoplasts were then resuspended in 20 µl of inoculum, then transfected with 100 µl of a solution of PEG1450 40% and CaCl2, 12 mM Na-Acetate, 425 mM Mannitol, pH 5,8) in which the cells were left floating for at least 40 minutes. After that the supernatant was removed with a sterile pipette and replaced with 30 ml of enzyme solution . Cells were digested on a rotary shaker for 4 to 6 hours at 50 rpm. To collect protoplasts the cell suspension was passed through a sterile 70 µm nylon filter and collected in a 50 ml tube. Enzyme solution was removed by centrifugation (90 g for 5 minutes) and cell washed two times in MM wash solution. After the second washing step, cells were then resuspended in 20 ml of MM wash solution, counted in a Burker chamber and the concentration adjusted to 2 × 106 cells/ml. One ml of protoplasts for each transfection event were then aliquoted in 15 ml polystyrene tubes, centrifuged at 90 g for 3 minutes and supernatant removed. Inoculum was added (20 µl) to the protoplasts which were then resuspended and transfected by adding 200 µl of sterile PEG solution 2). After 20 seconds of gently shaking, 1 ml of MM wash solution was added and protoplasts were kept on ice for at least 15 minutes. Transfection solution was then eliminated by centrifugation (90 g for 3 minutes) and 10 ml of filter sterilized culture media  were added. Protoplasts were maintained in 60 mm petri dishes at 25 °C without light for 48 hours and then collected by centrifugation (90 g for 3 minutes).Protoplasts from BY2 cells were obtained from 72 hours subculturing in modified KMCS media. Cells were harvested in a 50 ml tube by centrifuged (100 g for 6 minutes), and then collected supernatant was conserved as conditioned medium; protoplasts were then washed in MM washing buffer (5 mM CaCl47. In standard experiments for both N. benthamiana and BY2 protoplasts the rate of infected protoplasts was over 80%.Efficiency of transfection was estimated using purified virions TMV expressing GFP (from agroinfectious clone pJL24)48. A radio-labeled probe for PaTV was prepared trough T7 transcription from linearized plasmid as already described2.Total RNA was extracted from cells from each transfection event and then separated by denaturing agarose gel electrophoresis  using HEPES-EDTA buffer−ΔΔCt method42.RNA extractions were performed with Total Spectrum RNA Reagent  and RNA concentration was quantified with a NanoDrop 1000 Spectrophotometer. Copy DNA was obtained with High-Capacity cDNA Reverse Transcription Kit , using 5 µl of total RNA without normalizing the amount between samples, in order to be able to check for absolute increase in virus accumulation among different time points. For each virus or gene analyzed in the three biological replicates we did three technical replicates in Real time PCR . Information about each nucleotide position derives from at least 3 distinct clones.Specific primers designed on PaTV1 and PaPV1 sequences were used to obtain cDNA from protoplasts total RNA extraction with Invitrogen Thermo-Script SuperScript IV RT kit. Obtained cDNAs were used as template in a classic PCR protocol using specific primers . When raw data were not normally distributed and variances were not homogeneous, they were log-transformed before analysis. The t-test was used to compare virus quantities measured at different sampling times. Statistical tests were performed with SIGMAPLOT 13 (Systat Software).Supplementary figures and tables


Beet curly top Iran virus, Turnip curly top viruses, Oat dwarf viruses, the first from Iran, and Wheat dwarf virus from leafhoppers feeding on beet, parsley, pumpkin, and turnip plants.Implementation of a vector-enabled metagenomics approach resulted in the identification of various geminiviruses. We identified the genome sequences of  Beta vulgaris; n = 1), parsley , pumpkin , and turnip  plants. The insects were homogenized in SM buffer and processed as described by Dayaram et al. (–de novo assembled using ABySS 1.9 (Oat dwarf virus (ODV) genomes that were recovered from leafhoppers feeding on beet and turnip share 99.8% identity and 97% with the only other ODV identified infecting oat (Avena sativa) in Germany. To date, ODV has not been reported in Iran, and therefore, these genome sequences (accession numbers KX533458 to KX533459) represent the first genome sequences of ODV from Iran. Six Wheat dwarf virus (WDV) genomes recovered from leafhoppers feeding on beet (n = 2), turnip (n = 2), pumpkin (n = 1), and parsley (n = 1) display 13.6% diversity (accession numbers KX533460 to KX533465); however, compared with genomes of WDV in public databases, they are most closely related to recently identified sequences from Iran, sharing >97% genome-wide identity. The Beet curly top Iran virus  and Turnip curly top virus  sequences share 94% and 99% identity with previously described isolates, respectively. The BCTIV and TCTV genomes were recovered from leafhoppers feeding on turnip, and the two TCTV genomes share 90% identity.New molecular-based methods have facilitated the rapid identification of various plant and animal viruses, especially small single-stranded DNA viruses. Furthermore, vector-enabled metagenomic (VEM) approaches using these methods have proven very useful for the identification of plant virus circulation in various agricultural regions –4. Here,–m et al. –9. The vBySS 1.9 , and virBySS 1.9 , 11 werePsammotettix alienus has been shown to transmit ODV , KX533458 to KX533459 (ODV), KX533467 to KX533468 (TCTV), and KX533460 to KX533465 (WDV).The complete genome sequences for the four viruses have been deposited in GenBank under accession numbers


In 2016, World Health Organization announced Zika virus infection and its neurological sequalae are a public health emergency of global scope. Preliminary studies have confirmed a relationship between Zika virus infection and certain neurological disorders, including microcephaly and Guillain–Barre syndrome (GBS). The neuroimaging features of microcephaly secondary to Zika virus infection include calcifications at the junction of gray–white matter and subcortical white matter with associated cortical abnormalities, diminution of white matter, large ventricles with or without hydrocephalus, cortical malformations, hypoplasia of cerebellum and brainstem, and enlargement of cerebellomedullary cistern. Contrast enhancement of the cauda equine nerve roots is the typical neuroimaging finding of GBS associated with Zika virus. This review describes the nervous system disorders and associated imaging findings seen in Zika virus infection, with the aim to improve the understanding of this disease. Imaging plays a key role on accurate diagnosis and prognostic evaluation of this disease. Zika virus was first isolated from the specimens of sentinel rhesus monkey in 1947 . An incrAedes species mosquito. Mosquitos become infected when they feed on the Zika virus carriers. The infected mosquitoes can spread the virus to humans by transmitting the virus through a bite when they feed. Multiple studies have shown that Zika virus may have a variety of other transmission routes. Zika virus can be transmitted from mother to fetus through placenta or transmitted to the newborn during delivery. Zika virus RNA has even been detected in breast milk  and evaluation the development of the corpus callosum and the degree of myelination . ConventThe correlation between Zika and GBS was first reported in 2014 in French Polynesia . At presThe Zika virus infection can also cause acute myelitis, meningoencephalitis, and acute disseminated encephalomyelitis. On spine MRI, The abnormal signal of acute myelitis often involves more than three segments of spinal cord, and spinal cord may be enlarged due to edema. In the involved segments of the spinal cord, we may seen variable degrees and patterns of post-contrast enhancement. Mecharles et al.  reportedToxoplasma infection and other infectious agents, such as rubella virus, cytomegalovirus, and herpes simplex virus. Among them, Cytomegalovirus infection is most similar to the congenital Zika syndrome (TORCH syndrome is a viral or protozoan infection of brain tissue causing encephalitis, occurring primarily in the embryo or during the delivery process, referred to as congenital intrauterine infection or congenital TORCH infection. The word TORCH is an English acronym for several pathogens causing brain infection, including syndrome .Toxoplasma gondii infection usually lies on the periphery and can be scattered in the brain parenchyma. The calcification of herpes virus infection can occur very late after 3 years of age. However, Zika infection mainly occurs at the junction of cortex. In addition, TORCH syndrome can also affect other systems, such as involving the retina, can cause retinal dysplasia or retinitis. Cytomegalovirus infection can cause abnormal fetal brain development, such as pachygyria, polymicrogyria malformation lissencephaly. In general, given the different shapes, locations of intracranial calcifications in combination with other clinical and laboratory findings, these diseases may be differentiated from each other without difficulty.TORCH infected brain tissue mainly causes necrotizing encephalitis, especially prone to violations of the periventricular white matter, focal necrosis resulting in limitation of calcification. On CT scan, TORCH syndrome was characterized by multiple and scattered nodular calcifications in the brain parenchyma. The calcification caused by cytomegalovirus infection is usually located around the ventricle, while the calcification caused by Tuberous sclerosis is a congenital, familial, and hereditary diseases. The clinical manifestations of sebaceous adenoma, epilepsy, and mental retardation in triad of features. The CT examination of the disease often presents with multiple intracranial calcification were the main manifestations of calcification after the age of two. Calcification is often located in subependymal or cerebral cortex, characterized by multiple nodular calcification in the subependymal zone. However, most of the patients with tuberous sclerosis have a skin sebaceous adenoma, or other characteristic lesions that are frequently detected simultaneously .Idiopathic hypoparathyroidism may be familial or sporadic with unknown etiology, or may be secondary to autoimmune disease, and may occur alone or in combination with other autoimmune diseases. The head CT examination can show multiple calcifications in the brain parenchyma, usually diffusely distributed in the basal ganglia and thalamus, cerebellar dentate nucleus, in cerebral hemisphere cortex and corticomedullary junction area, with bilateral, usually symmetrical distribution and patchy, strip-like, crescent shaped, or punctate appearance. For the metabolic and endocrine disorders, the location and morphology of calcification are not characteristic. The diagnosis of hypoparathyroidism should be made in combination with clinical information, especially biochemical tests .Aicardi–Goutières syndrome is a rare group of the nervous system and skin involvement in early-onset hereditary diseases. Its main clinical features include multiple intracranial calcifications, white matter lesions, CSF increased in chronic lymphocytic and frostbite like lesions. It was first reported by Aicardi and Goutieres in 1984. Intracranial calcification mainly occurred in more than 90% children with AGS, The location of calcifications is usually at the basal ganglia, periventricular white-matter, and dentate nuclei in AGS. However, congenital Zika infection usually at the corticomedullary junction. Additionally, the lack of abnormal cortical development in AGS may help to differentiate this disorder from congenital Zika infection .Mutations in RNASET2 are associated with an autosomal recessive disorder characterized by early-onset severe developmental disorders, usually microcephaly, seizures, and sometimes hearing impairment. This disorder is caused by the mutations in RNASET2 gene, which have been hypothesized to result in accumulation of ribosomal RNA within neuronal lysosomes. In this disease, calcification is not very common, only a few patients were seen showing subtle spot calcification at the basal ganglia, periventricular, and deep white matter. In addition, cortical malformation has not been described. It is important to be aware of this condition, as it may be clinically and radiologically indistinguishable from congenital Zika infection  Table 11.Neurologic manifestations of Zika virus infection are primarily seen as microcephaly and GBS. The imaging examinations including fetal ultrasound, CT, and MRI are quite helpful to diagnose and evaluate this disease. MRI can identify more associated abnormalities than CT and should be the first choice of investigation where available. Imaging may be very useful in providing evidence of congenital Zika syndrome and in improving our understanding of this disease. These imaging findings can alert radiologists to the possibility of congenital Zika virus infection in infants.BG and ML designed the direction of the article and provided professional guidance. SW and YZ systematically collected, sorted out the relevant researches, and completed the manuscript. AL revised the manuscript’s professional issues and grammatical errors.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MS and handling Editor declared their shared affiliation.