Ebola virus (EBOV) is an enveloped, single-stranded RNA virus that can cause Ebola virus disease (EVD). It is thought that EVD survivors are protected against subsequent infection with EBOV and that neutralising antibodies to the viral surface glycoprotein (GP) are potential correlates of protection. Serological studies are vital to assess neutralising antibodies targeted to EBOV GP; however, handling of EBOV is limited to containment level 4 laboratories. Pseudotyped viruses can be used as alternatives to live viruses, which require high levels of bio-containment, in serological and viral entry assays. However, neutralisation capacity can differ among pseudotyped virus platforms. We evaluated the suitability of EBOV GP pseudotyped human immunodeficiency virus type 1 (HIV-1) and vesicular stomatitis virus (VSV) to measure the neutralising ability of plasma from EVD survivors, when compared to results from a live EBOV neutralisation assay. The sensitivity, specificity and correlation with live EBOV neutralisation were greater for the VSV-based pseudotyped virus system, which is particularly important when evaluating EBOV vaccine responses and immuno-therapeutics. Therefore, the EBOV GP pseudotyped VSV neutralisation assay reported here could be used to provide a better understanding of the putative correlates of protection against EBOV. Filoviridae, is an enveloped, single-stranded RNA virus that can cause Ebola virus disease (EVD), a highly lethal illness with up to 90% mortality1. Since its discovery in 1976, EBOV has caused sporadic outbreaks across Central Africa and was responsible for the 2013–2016 EVD epidemic in West Africa2, which was the largest EBOV outbreak on record and resulted in more than 28,600 cases and over 11,300 deaths3. This outbreak constituted a public health emergency of international concern and highlighted the urgent need for vaccines and therapeutics against EBOV.Ebola virus (EBOV), a member of the family 4. Surface GP is critical for host cell attachment and fusion6 and is a target for neutralising antibodies7. Survivors of EVD are thought to protected against subsequent EBOV infection and neutralising antibodies to the viral surface GP are possible correlates of protection9. Serological assays, such as the plaque reduction neutralisation test (PRNT), are central to evaluate neutralising antibodies against EBOV GP. However, because of its severe pathogenicity, potential transmission from person-to-person and lack of approved vaccines or antiviral treatments, handling of EBOV is restricted to containment level (CL) 4 laboratories. High containment facilities are expensive and are not readily available, especially in countries and organisations with limited resources. Furthermore, the assay format and time required for plaque development, which can take approximately nine days, makes it time-consuming and restricts high-throughput sample processing. Development of novel serological assays that utilise genetically modified recombinant or chimeric viruses with attenuated pathogenicity have enabled more widespread investigation of neutralising antibodies against highly pathogenic viruses including EBOV11.The EBOV RNA genome is approximately 19 kb in length and encodes seven main proteins. The envelope glycoprotein (GP) of EBOV forms homotrimeric spikes that project from the surface of the viral particles13, including for EBOV15. A number of EBOV GP pseudotyped virus neutralisation assays have been developed to investigate immune responses to EBOV infection and vaccination18, as well as for evaluation of monoclonal antibody (mAb) therapies21.Pseudotyped viruses are replication-defective chimeric virions that comprise the structural and enzymatic core of one virus, bearing the envelope protein or glycoprotein of another, and encode a quantifiable reporter gene. Retroviruses, including lentiviruses and gammaretroviruses such as human immunodeficiency virus (HIV) and murine leukaemia virus (MLV), respectively, and rhabdoviruses, such as vesicular stomatitis virus (VSV), have been used extensively as cores for pseudotyped viruses22. The aim of this study was to assess the suitability of EBOV GP pseudotyped HIV-1 and VSV systems to measure neutralisation by EVD survivor plasma, in comparison with results from a live EBOV neutralisation assay.There are many factors that need to be considered when developing and optimising pseudotyped virus neutralisation assays, to assess experimental parameters that can affect assay performance and to ensure accuracy and reproducibility. These include, choice of core virus and reporter gene, determination of target cell line and amount of pseudotyped virus input, as well as correlation with live virus neutralisation50/ml values were observed in 293T/17 cells, followed by Huh-7 cells  were generated and quantified by measuring luminescence in a range of target cell lines, in order to determine the optimum cell line to use in neutralisation assays. Cells only controls were used to determine background levels of luminescence  of pseudotyped virus neutralisation were estimated by model of nonlinear regression dose–response curves  was similar to that expected according to the manufacturer’s product data sheet (0.06 µg/ml). Therefore, a target input of approximately 3.7 × 104 RLU/well was used in subsequent EBOV GP pseudotyped VSV neutralisation assays.To determine the optimal pseudotyped virus input to use in the HIV- and VSV-based assays, neutralisation of different amounts of the EBOV GP pseudotyped viruses by plasma from a Guinean EVD survivor donor or human anti-EBOV GP mAb KZ52 was assessed. KZ52 was selected as it is commercially available and there is accompanying information regarding its neutralisation activity against EBOV GP pseudotyped VSV expressing luciferase. However, as the EBOV GP pseudotyped HIV-1 was not neutralised by KZ52 Fig. a,b and 5ves Fig. c,d. Plasves Fig. a. Lower ted Fig. b and IC5put Fig. . When us50 of pseudotyped virus neutralisation were estimated by model of nonlinear regression dose–response curves . In the HIV-1-based assay, dose–response curves were unable to be fitted for three of the 30 EVD survivor samples and six of the samples were deemed below the background level of neutralisation. In contrast, a dose–response curve was unable to be fitted for only one of the EVD survivor samples tested in the VSV-based neutralisation assay. In the HIV-1-based assay, three of the 10 negative plasma samples tested were above the background level of neutralisation, whereas only one of the negative samples tested was above the background level of neutralisation in the VSV-based assay. Although some differences in the discriminatory power of positive and negative samples between the assays were observed, a statistically significant difference in neutralisation titres was detected between the EVD survivors and negative plasma samples in the HIV-1-based assay    Fig. . Remarka50 values of EBOV GP pseudotyped HIV-1 neutralisation of the 30 EVD survivor and 10 negative plasma samples were compared with GMT values for the live EBOV neutralisation assay, a positive correlation (rs = 0.54) was determined using the nonparametric Spearman correlation coefficient . Remarkably, a stronger statistically significant (p < 0.0001) positive correlation (rs = 0.86) was observed when IC50 values of EBOV GP pseudotyped VSV neutralisation were compared with GMT values for the live EBOV neutralisation assay  and 0.69 (p < 0.0001), respectively. Therefore, the VSV-based EBOV GP pseudotyped virus neutralisation assay correlated better with live EBOV neutralisation than the HIV-1-based neutralisation assay.The neutralising capacity of the individual plasma samples against authentic EBOV was assessed by a live virus neutralisation assay 26, influenza (H5N1 and H7N9)29, rabies31 and chikungunya virus32, for example, found that results correlated well with those from replication-competent or live virus assays. A high degree of correlation has been demonstrated between EBOV CL4 PRNT and an EBOV pseudotyped VSV CL2 fluorescence reduction neutralisation test (FRNT)33. However, pseudotyped virus assays may not always accurately determine neutralisation35. Live EBOV and EBOV GP pseudotyped neutralisation assays have previously been shown to yield variable results36, which could be due to differing experimental conditions and viral systems. It is therefore important to optimise pseudotyped virus neutralisation assays in context of the particular viral GP being studied in order to obtain reliable specificity and sensitivity. The aim of this study was to assess the suitability of EBOV GP pseudotyped HIV-1 and VSV systems to measure the neutralising ability of plasma from EVD survivors, when compared to live EBOV neutralisation.Pseudotyped viruses can be used as alternatives to infectious virus in serological assays to measure neutralising antibodies to viral envelope glycoproteins37. Highest TCID50 values were obtained following EBOV GP pseudotyped HIV-1 and VSV infection of 293T/17 and Vero E6 cells, respectively. There seemed to be large variability of the luminescent measurement for the VSV-based platform, which may be caused by the sensitive nature of the luciferase signal detection. This highlights the importance of titrating each pseudotyped virus batch before use in neutralisation assays, and the inclusion of multiple replicates.Reporter activity was detected in all cell lines  infected with EBOV GP (Mayinga) pseudotyped HIV-1 and VSV, demonstrating the broad tissue range conferred by EBOV GP, although differences in luminescence were observed. This may reflect general defects in viral entry in different cells. A relatively lower level of EBOV GP pseudotyped HIV-1 transduction was exhibited by Vero E6 cells, which might be due to an intrinsic restriction factor, TRIM5α, which restricts retroviral infection by specifically recognising the HIV-1 capsid and promoting its rapid, premature disassembly38. However, within the range tested here, KZ52 did not display neutralisation against EBOV GP pseudotyped HIV-1, suggesting that the EBOV GP on the pseudotyped HIV-1 might be at higher levels, thereby reducing assay sensitivity, and neutralisation may be observed using a higher concentration of KZ52. In contrast, KZ52 was able to neutralise the EBOV GP pseudotyped VSV.The EBOV GP pseudotyped viruses were used to assess the neutralising activity of a human anti-EBOV GP mAb, KZ52. KZ52 has been shown previously to neutralise EBOV pseudotyped viruses50 of pseudotyped virus neutralisation decreased with decreasing amounts of EBOV GP pseudotyped VSV input. The variability in neutralisation observed between different amounts of pseudotyped virus input highlights the importance of including standards or reference material with a known activity or potency when comparing neutralising activity, allowing calibration of results39.To assess the effects of differing amounts of pseudotyped virus input on neutralisation, plasma from an EVD survivor of the 2013–2016 EBOV outbreak and KZ52 were screened against different amounts of the EBOV GP pseudotyped HIV-1 and VSV, respectively. Decreasing quantities of pseudotyped HIV-1 led to more variable and unreliable results, and the KZ52 ICBoth pseudotyped virus systems were able to measure neutralising antibodies in plasma from EVD convalescent patients, and results correlated positively with a live EBOV neutralisation assay. However, the discriminatory power of the HIV-1-based assay with regards to differing antibody titres appeared to be low. Some of the samples tested, which showed neutralising activity against live EBOV, did not display neutralisation against the pseudotyped virus and vice versa, therefore raising questions on the sensitivity and specificity of the pseudotyped HIV-1 assay.40. Therefore, the use of anti-VSV-G hybridoma cell culture supernatant could give rise to pseudotyped virions covered by anti-VSV-G antibodies, but are still infectious due to Ebola GP. This could potentially induce plasma specific reactivity of virions due to bound anti-VSV-G antibodies more than EBOV GP specific reactivity.In the current study, human embryonic kidney (293T/17) cells were used for the pseudotyped HIV-1 neutralisation assays, whereas African green monkey kidney (Vero) cells were used in the VSV-based assay and also the live EBOV assay. Therefore, this could account for some of the differences in results observed between the two assays and for the better performance of the VSV-based assay in relation to live EBOV neutralisation. Also, the HIV-1- and VSV-based pseudotyped virus systems assessed in the current study utilise different transfection methods, which could have implications on the composition of the pseudotyped viruses, density and/or glycosylation of the viral envelope protein on the surface, and consequently neutralisation results. This highlights the importance of assessing experimental conditions and methodology when developing and optimising pseudotyped virus neutralisation assays. A limitation to this study was that the level of EBOV GP incorporation per pseudotyped virus type could not be assessed. Also, for the VSV-based pseudotyped virus system, traces of VSV-G from the rVSV-ΔG-Luc-VSV-G virus could be recycled into newly pseudotyped virions8. Due to their non-replicating nature, such pseudotype systems do not recapitulate all steps in the viral life cycle that may potentially be targeted by neutralising antibodies41. In addition, the round, spherical shape of EBOV GP pseudotyped HIV-1 or bullet shape of EBOV GP pseudotyped VSV compared to the filamentous shape of authentic EBOV could affect their susceptibility to neutralisation. Also, the density of GP on the surface of the pseudotyped virus may not be the same as that found on live EBOV and may result in the loss or masking of quaternary epitopes42. Furthermore, GP maturation and assembly in live EBOV could be different in the generation of an EBOV pseudotyped virus and may result in different targets and/or conformational epitopes when using whole live EBOV as opposed to EBOV GP alone in a pseudotyped virus. The presence of shed GP or secreted GP (sGP) in the live EBOV assay compared to absence in the EBOV GP pseudotyped virus assays could also have an effect on neutralisation. In the live EBOV assay, shed GP and sGP could reduce neutralisation of circulating virus by cross-reactive antibodies to surface GP. However, in the current study, weaker relative neutralisation was observed in the HIV-1 based pseudotyped virus assay. Therefore, it is possible that cell debris or free GP generated during EBOV GP pseudotyped HIV-1 production by polyethylenimine (PEI) transfection could be interfering with neutralisation. Finally, detection of infected cells via measurement of luminescence in the EBOV GP pseudotyped virus neutralisation assay compared to plaque formation in the live EBOV neutralisation assay could affect neutralisation readout.There are several differences between EBOV GP pseudotyped and live EBOV neutralisation assays that could affect their resultsEBOV GP pseudotyped virus neutralisation assays have value for vaccine evaluation and assessment of convalescent blood products and mAbs for use as immunotherapeutics. However, pseudotyped virus assays may not always accurately determine neutralisation when compared with neutralisation against live virus. In this study, both EBOV GP pseudotyped HIV-1 and VSV assays were able to detect neutralisation of plasma from EVD survivors and correlated positively with live EBOV neutralisation. However, the VSV-based assay performed better than the HIV-1-based assay in relation to specificity, sensitivity, and correlation with the live EBOV neutralisation assay. This research has highlighted the importance of optimising pseudotyped virus neutralisation assays in context of the particular viral GP being studied, especially when evaluating vaccine responses and therapeutics, and could provide a better understanding of the correlates of protection against EBOV.gag-pol plasmid p8.9143, the firefly luciferase reporter construct pCSFLW44 and a pCAGGS EBOV (Mayinga) GP (GenBank accession number NC_002549) expression construct were kind gifts from Edward Wright.The HIV-1 2 in Dulbecco’s Modified Eagle Medium (DMEM), high glucose, with l-glutamine  supplemented with 10% fetal bovine serum (FBS), heat inactivated . HeLa cells (ECACC 93021013) were also used as a target cell line and were cultured in Minimum Essential Media (MEM) + GlutaMAX  supplemented with 10% FBS and 1 × MEM Non-Essential Amino Acids (NEAA) solution (Life Technologies).Human embryonic kidney (HEK) 293T clone 17 cells , Teddington, UK, CRL-11268) were used for all transfections and as a target cell line for titration and pseudotyped HIV-1 neutralisation assays. Vero E6. All methods were carried out in accordance with the relevant guidelines and regulations under ethical approval No. 33/CNERS/15. Informed consent was obtained from all participants.Plasma samples from EVD survivors of the 2013–2016 EBOV outbreak recruited 3 to 14 months post-infection from two regions of Guinea (Guéckédou and Coyah) and from negative control blood donors in the UK and Guinea, who were not knowingly exposed to persons with EVD and did not attend high risk events such as funerals, were heat inactivated at 56 °C for 30 min. The samples were obtained from a pre-existing biobank, for which live EBOV neutralisationProtein A purified human anti-EBOV GP mAb KZ52 , USA) was also tested in the EBOV GP pseudotyped virus neutralisation assays.47. Twenty-four hours prior to transfection, approximately 8 × 105 293T/17 cells were seeded into sterile, 6-well cell culture plates  and incubated at 37 °C, 5% CO2 and 95% humidity until 60–80% confluence. The HIV gag-pol plasmid, p8.91, and the firefly luciferase reporter construct, pCSFLW, were transfected simultaneously with the EBOV (Mayinga) GP expression vector at a ratio of 0.6:0.9:0.6 µg (core:reporter:envelope) using 10 µl of 1 µg/ml polyethylenimine (PEI) (Sigma-Aldrich) per 1 µg DNA in Opti-MEM medium (Gibco). Following overnight transfection, the cells were incubated with fresh medium and incubated at 37 °C, 5% CO2. Pseudotyped virus supernatants were harvested at 48 and 72 h post-transfection, passed through a 0.45 µm pore filter  and stored at − 80 °C.The generation of HIV-1 pseudotyped viruses was performed as detailed previously48. Twenty-four hours prior to transfection, approximately 2.4 × 106 293T/17 cells were seeded into sterile, 100 mm cell culture dishes (Corning) and incubated at 37 °C, 5% CO2 and 95% humidity until 60–80% confluence. The cells were transfected with the EBOV GP expression vectors using TransIT-LT1 Transfection Reagent , USA) as per the manufacturer’s instructions. Following overnight transfection, the medium was removed and the cells were infected with rVSV-ΔG-Luc that was pseudotyped with the VSV glycoprotein (rVSV-ΔG-Luc-VSV-G)  at a multiplicity of infection (MOI) of 5 in Opti-MEM medium and incubated at 37 °C, 5% CO2. After 2 h, the inoculum was removed, cells were washed twice with Dulbecco’s phosphate buffered saline (DPBS) (Gibco) and fresh medium was added. Pseudotyped virus supernatants were harvested at 18–24 h post-infection, clarified twice by centrifugation at 200xg for 5 min at 10 °C and stored at − 80 °C. Prior to use, the pseudotyped viruses were incubated with anti-VSV-G hybridoma cell culture supernatant  at a 1:125 dilution for 1 h at 37 °C to reduce background infection mediated by residual virus possessing VSV-G, which can be carried over during preparation48.EBOV GP pseudotyped VSVs were prepared using recombinant VSV, in which the VSV-G gene had been deleted (rVSV-ΔG) and replaced with a luciferase reporter gene (rVSV-ΔG-Luc) by a method similar to that described previouslyAll experiments involving pseudotyped viruses were performed in a CL2 facility at Public Health England (PHE), Porton Down, UK.48.Titration and neutralisation assays were performed in 96-well solid white flat bottom polystyrene TC-treated microplates (Corning) and were based upon previously described protocols4 293T/17, Huh-7 or Vero E6 cells, or 1 × 104 HeLa cells were then added to each well and incubated at 37 °C, 5% CO2 for 48 h. The medium was removed and 50 µl of a 50:50 mix of Bright-Glo luciferase assay reagent :fresh medium was added to each well and incubated for at least 2 min at room temperature to allow complete cell lysis. Luminescence was measured using a Glomax-Multi + detection system luminometer (Promega) and relative luminescence units per ml (RLU/ml) were determined. The negative cut-off was set at 2.5 times the average RLUs of the cells only control wells. 50% tissue culture infectious dose (TCID50)/ml values were determined using the Reed-Muench method49.For pseudotyped HIV-1 titration assays, five-fold serial dilutions of pseudotyped virus at a starting dilution of 1:5 were prepared in quadruplicate in Opti-MEM medium at a final volume of 100 µl/well. 100 µl of approximately 2 × 105 293T/17 cells were then added to each well and incubated for 48 h at 37 °C, 5% CO2, prior to taking a chemiluminescent readout as described above. Infectivity was calculated using the formula: Percentage (%) infectivity = [(RLU with sample)/(RLU without sample)] × 100.For the pseudotyped HIV-1 neutralisation assay, two or threefold serial dilutions of plasma samples at a starting dilution of 1:5 or 1:10, respectively, were prepared in duplicate in Opti-MEM medium at a final volume of 50 µl/well and incubated with 50 µl of a standardised RLU per well of pseudotyped virus , prepared in Opti-MEM medium, for 1 h at 37 °C. 100 µl of approximately 2 × 104 293T/17 or 1 × 104 Huh-7, HeLa cells or Vero E6 cells were seeded in 96-well microplates and incubated at 37 °C, 5% CO2 and 95% humidity. The medium was removed and two-fold serial dilutions of pseudotyped virus in Opti-MEM medium, starting with neat pseudotyped virus were added to each well in quadruplicate at a final volume of 100 µl/well. After 24 h, a chemiluminescent readout was taken and TCID50/ml values were determined as described above.For pseudotyped VSV titration assays, 24 h prior, approximately 2.5 × 104 Vero E6 cells were seeded and incubated as for titration above. Twofold serial dilutions of plasma samples at a starting dilution of 1:10 were prepared in duplicate in Opti-MEM medium at a final volume of 120 µl/well in 96-well microplates, and incubated with 120 µl of a standardised RLU per well of pseudotyped virus , prepared in Opti-MEM medium, for 1 h at 37 °C. The medium was removed from the cells, 50 µl of the plasma-pseudotyped virus mixtures were added to each well in quadruplicate at incubated at 37 °C, 5% CO2. After 1 h, 50 µl of fresh medium was added to each well. Luminescence was measured after 24 h and infectivity was calculated as described above.Twenty-four hours prior to pseudotyped VSV neutralisation, approximately 1 × 1050 of pseudotyped virus neutralisation were estimated by model of nonlinear regression fit with settings for log (inhibitor) vs. normalised response curves using GraphPad Prism v5 , USA).Pseudotyped virus neutralisation assay raw data were normalised as percentage (%) infection relative to mean values for pseudotyped virus only controls , then ICStatistical comparison between two unpaired groups was performed using the Mann–Whitney test (GraphPad Prism v5). Correlation between two variables was quantified using Spearman nonparametric correlation (GraphPad Prism v5).Supplementary Information.


Coagulation Factor IX-rich protrhombin complex concentrate (FIX-PCC) is a therapeutic biologic product that consists of a mixture of several human plasma-derived proteins, useful for treating hemophilia B. Due to its complex composition, FIX-PCC is very challenging to bioprocess through virus removing nanofilters in order to ensure its biosafety. This article describes a two-step filtration process of FIX-PCC using a nanocellulose-based filter paper with tailored porosity. The filters were characterized with scanning electron microscopy (SEM), cryoporometry with differential scanning calorimetry, and nitrogen gas sorption. Furthermore, in order to probe the filter’s cut-off size rejection threshold, removal of small- and large-size model viruses, i.e., ΦX174 (28 nm) and PR772 (70 nm), was evaluated. The feed, pre-filtrate, and permeate solutions were characterized with mass-spectrometric proteomic analysis, dynamic light scattering (DLS), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and analytical size-exclusion high-performance liquid chromatography (SEHPLC). By sequential filtration through 11 μm pre-filter and 33 μm virus removal filter paper, it was possible to achieve high product throughput and high virus removal capacity. The presented approach could potentially be applied for bioprocessing other protein-based drugs. Replacement therapy using plasma-derived Factor IX (FIX) products is a life-saving treatment for patients with hemophilia B. Both recombinant and plasma-derived FIX show high efficacy in clinical trials . ProductAs it is with all plasma-derived products, the viral safety of FIX-rich PCC is a critical issue . AccordiIt is known that the levels of different impurities are highly dependent on the type of chromatographic separation that was used during plasma treatment ,18,20. TSo far successful virus removal filtration of FIX products has been described in the literature only for a limited number of commercial filters. A novel type of virus removal filter paper was developed at Uppsala University, which is produced by adapting traditional paper making technology and consists of 100% cellulose nanofibers ,32. The In this article, for the first time the filtration of FIX-rich PCC using a nanocellulose-based virus removal filter paper is described. Furthermore, a two-step size-exclusion nanofiltration process is developed to remove foulants and ensure efficient virus removal filtration of FIX-rich PCC using nanocellulose-based virus removal filter paper. FIX-rich PCC was used as a model for a highly complex plasma-derived product to simulate industrial bioprocesses where impurities may greatly affect product yield and biosafety.® TGX Stain-Free™ protein gels (4568125), tris/glycine/SDS running buffer (1610732), 4x Laemmli Sample Buffer (1610747), and Precision Plus Protein™ unstained protein standards (1610363) were purchased from Bio-Rad .Cladophora cellulose was provided by FMC Biopolymer . FIX-rich PCC was provided by National Center for Hematology, Moscow, Russia, as lyophilized powder. Coliphages ΦX174 (ATCC 13706-B1™) and PR772 (BAA-769-B1), and the host bacteria Escherichia coli (Migula) Castellani and Chalmers C (ATCC 13706) and K12 J53-1(R15) [HER 1221] (BAA-769) strains were obtained from ATCC . Agar (214530) was obtained from BD . Tryptone (LP0042B) and yeast extract (Oxoid) (LP0021) were obtained from Thermo Fisher Scientific. Phosphate-buffered saline (P4417), 2-mercaptoethanol (M3148), sodium chloride (S5886), sodium phosphate dibasic (71640) and 2-mercaptoethanol (M3148) were purchased from Sigma-Aldrich . Any kD™ Mini-PROTEANFilters of different thickness were prepared from Cladophora cellulose dispersion (0.1 wt.%) made by microfluidization with 200 μm (twice) and 100 μm hole sized chambers at 1800 bar using LM20 Microfluidizer . Furthermore, the wet cake was made by draining the dispersion over a membrane  in a funnel, driven by vacuum. Obtained cellulose cakes were dried at 140 °C to produce pre-filters and 80 °C for filter papers using hot-press .−1 and 7.4, respectively. Lyophilized FIX-rich PCC samples were reconstituted by dissolving in phosphate-buffered saline (PBS). No visible particles could be seen after reconstitution, and the solution was clear and transparent. Upon dissolution, the conductivity and pH values were 15.4 mS cmPre-filtration and filtration steps were performed in a 47 mm diameter Advantech KST 47 filter holder. Prior to filtration, the pre- and filter papers were wetted in order to extrude the air by running 20 mL of PBS. The pre-filtration steps with 6 and 11 μm pre-filters were performed at 1 bar transmembrane pressure, and the filtrations with 33 μm filters were carried out at 1 or 3 bar. The permeate solutions were collected and for filtrations of the larger volume, permeate was collected in one or three fractions and saved.2 mbar and 35 mA, and the sputtering time was 30 s.For top-view images samples were fixed onto aluminum stubs with double-adhesive carbon tape, and for cross-section images the samples were mounted onto aluminum sample holders with screw. Imaging was performed using Zeiss Merlin FEG-SEM instrument . To reduce charging effects samples were sputtered with Au/Pd with a sputter coater  was used. The sputtering settings were 4 × 10−1 followed by heating to 277.15 K (4 °C) at a rate of 0.7 K min−1. Measurements were performed in five replicates.Filter paper samples (1.5–2 mg) were soaked into deionized water overnight at room temperature. Water was decanted, and the samples were placed in aluminum crucibles with a lid. Samples were cooled down to 248.15 K (−25 °C) at a rate of 10 K minpr is the radius of pore (nm) and ΔT is the difference between the peak maximum for melting of pore-confined water and peak value for melting of bulk water, experimentally determined at 0.6 ± 0.01 °C.The pore size was calculated according to Landry :(1)ΔΤ =−Particle size distribution was obtained from dynamic light scattering (DLS) using a Zetasizer Nano ZS  instrument. All experiments were performed in triplicates.v/v) with PBS and Laemmli buffer, and boiled for 10 min. Electrophoretic separation was carried out at 270 V with Mini-PROTEAN Tetra Vertical Electrophoresis Cell . Protein bands were detected with Gel Doc™ EZ System , and quantified using Image Lab 6.0 analysis software (Bio-Rad).Protein separation was performed by reducing polyacrylamide gel electrophoresis (SDS-PAGE). Samples were diluted  analytical column. Chromatography was performed with 100 mM sodium phosphate, pH 6.8 mobile phase at 0.3 mL minEqual amounts (20 µg) of protein samples were taken out for digestion. After reduction and alkylation, the proteins were on-filter digested by trypsin using 3 kDa centrifugal filters  according to a standard operating procedure. Obtained peptides were dried using a speedvac system. Pellets were resolved in 60 μL of 0.1% formic acid and further diluted four times prior to nano-LCMS/MS. Tandem mass spectrometry was performed by applying HCD in the QEx-Orbitrap mass spectrometer , equipped with a reversed-phase C18-column by 35 min long gradient. Database searches were performed using the Sequest algorithm, embedded in Proteome Discoverer 1.4  against Homo Sapience proteome extracted from Uniprot, Release June 2019 with 95% confidence level per protein.6 plaque forming units (PFU) mL−1 before filtration was performed. Bacteriophage titer was determined by PFU assay by double agar overlay method. Briefly, ten-fold serially diluted bacteriophage samples were mixed with host E. coli strains and melted soft agar, and poured on the surface of prepared hard agar plate, followed by incubation at 37 °C for 5 h. Coliphages PR772 and ΦX174 were spiked to the pre-filtered solutions to obtain final titer about 10N is the number of plaques, V is the volume  of added virus and d is the dilution factor.Bacteriophage titer was calculated using Equation (1):log10 reduction value (LRV):The virus retention was expressed as −2 volumetric load was filtered through the 33 μm mille-feuille filter paper, a rapid flux decline was observed, e.g., from about 80 L m−2 h−1 to about 10 L m−2 h−1 at 3 bar overhead pressure. DLS analysis of the feed and permeate samples revealed that the feed sample showed widely distributed fraction of protein impurities above 70 nm, which were not detectable after filtration as shown in When the FIX-rich PCC at 20 L mTo investigate if significant changes were recorded in the protein molecular weight distribution in the permeate sample, SDS-PAGE analysis was performed, as shown in The nanocellulose-based filter paper platform provides the possibilities to relatively easily tailor the pore-size distribution of the filter paper to a specific cut-off value. This could be achieved for instance by varying the thickness of the filter paper. To derive information about the pore size of the filter cryoporometry analysis was performed. −2 h−1 bar−1, and the highest virus removal capacity for both small- and large-size viruses, i.e., LRV ≥5.7. The 6 µm filter in the series exhibits the fastest flux, i.e., 405 L m−2 h−1 bar−1, but poor virus removal capacity, i.e., LRV <1 and <2 for 28 nm and 70 nm model phages. The flux and virus removal properties of 11 µm filter are intermediate to the other two filters, wherein the 11 µm filter paper shows high clearance towards 70 nm virus, i.e., >5.7, and moderate clearance toward 28 nm one, i.e., LRV 3.5–4.5, and hydraulic flux of 125 L m−2 h−1 bar−1. Interestingly, the small-size virus removal capacity of 11 µm filter decreased with increasing load volume, whereas that of 33 µm filter remained unaffected under the experimental conditions. The latter could probably be due to redistribution of flow through the larger pores when the smaller pores become clogged in 11 µm filter paper. To assess the particle rejection cut-off for each filter, model probes with 2 different particle sizes were used in the form of bacteriophages, i.e., PR772 (70 nm) and ΦX174 (28 nm) phages, see Overall, the results from the filtration with 6 μm/33 μm sequence suggest that the large Mw impurities were not removed during the pre-filtration step and, subsequently, caused filter fouling and thereby low product yield during the second step. In another set of experiments, the pre-filtration was performed using 11-μm filter paper followed by filtration with 33 μm filter at 1 bar. The results of the SDS-PAGE analysis for 11 μm /33 μm filtration sequence are summarized in −2. −2, which is a drastic improvement from 20 L m−2 when filtering in a single-step process through 33 µm filter paper. Furthermore, the filter paper showed high model small-size virus removal capacity, wherein LRV was ≥ 5 in all collected fractions  was detected. Thus, it was confirmed that the two-step 11 µm/33 µm filtration provides enhanced throughput and good capacity to remove small-size virus without abrupt fouling even when challenged with a relatively large load. Based on the above results, it was concluded that pre-filtration with 11 µm pre-filter removes the aggregates, which in turn greatly enhances the yield of the 33 µm filtration. To confirm the high virus removal capacity of 33 µm filter, the filter paper was loaded with much larger volume than that tested earlier, i.e., 175 L mractions B. In parIn this article, the filtration of a highly challenging hematologic product was investigated. Considering that FIX-rich PCC inherently consists of many bioactive components and some impurities, the virus removal filtration of this product is difficult without fouling. The virus removal filtration of PCC was previously reported using Ultipor DV50 filters, which are dedicated for removal of large-size viruses but do not ensure viral safety against parvoviruses . FiltratIn this work, in order to achieve high virus removal capacity combined with reduced fouling, a tailored two-step process of filtration with nanocellulose-based filter paper was developed. In particular, sacrificial pre-filters with a thickness of 6 and 11 μm were tested. The increased thickness of the filters resulted in tighter pore structure as detected by cryoporometry. The observed effect is explained as follows and illustrated in Overall, the two-step approach presented here is based on the size-exclusion principles and is therefore robust. It could thus further be adapted in the manufacturing of other protein-based pharmaceutics, too, including recombinant proteins wherein impurities in the form of host cell proteins may greatly affect the final yield of the biologics during virus removal nanofiltration.A two-step process was developed to both enhance filtration capacity (25-fold) and achieve high clearance of small-size viruses (LRV >5) using appropriate pre-filter paper. Large-size aggregates were the main foulants in the feed solution, and by tailoring the properties of the pre-filters the foulants were efficiently removed. In particular, 11 μm/33 μm filtration was found most suitable. The presented approach could potentially be applied for bioprocessing other protein-based drugs, both derived from plasma and produced by recombinant approaches. The article further provides new insights regarding the mechanism of virus removal in the nanocellulose-based filter paper, highlighting the combined effect of size exclusion and tortuosity of pore network.


Many viruses can cause respiratory diseases in humans. Although great advances have been achieved in methods of diagnosis, it remains challenging to identify pathogens in unexplained pneumonia (UP) cases. In this study, we applied next-generation sequencing (NGS) technology and a metagenomic approach to detect and characterize respiratory viruses in UP cases from Guizhou Province, China. A total of 33 oropharyngeal swabs were obtained from hospitalized UP patients and subjected to NGS. An unbiased metagenomic analysis pipeline identified 13 virus species in 16 samples. Human rhinovirus C was the virus most frequently detected and was identified in seven samples. Human measles virus, adenovirus B 55 and coxsackievirus A10 were also identified. Metagenomic sequencing also provided virus genomic sequences, which enabled genotype characterization and phylogenetic analysis. For cases of multiple infection, metagenomic sequencing afforded information regarding the quantity of each virus in the sample, which could be used to evaluate each viruses’ role in the disease. Our study highlights the potential of metagenomic sequencing for pathogen identification in UP cases.


The small molecule macrocyclic lactone ivermectin, approved by the US Food and Drug Administration for parasitic infections, has received renewed attention in the last eight years due to its apparent exciting potential as an antiviral. It was identified in a high-throughput chemical screen as inhibiting recognition of the nuclear localizing Human Immunodeficiency Virus-1 (HIV-1) integrase protein by the host heterodimeric importin (IMP) α/β1 complex, and has since been shown to bind directly to IMPα to induce conformational changes that prevent its normal function in mediating nuclear import of key viral and host proteins. Excitingly, cell culture experiments show robust antiviral action towards HIV-1, dengue virus (DENV), Zika virus, West Nile virus, Venezuelan equine encephalitis virus, Chikungunya virus, Pseudorabies virus, adenovirus, and SARS-CoV-2 (COVID-19). Phase III human clinical trials have been completed for DENV, with >50 trials currently in progress worldwide for SARS-CoV-2. This mini-review discusses the case for ivermectin as a host-directed broad-spectrum antiviral agent for a range of viruses, including SARS-CoV-2. Streptomyces avermitilis )An instinctive response in developing antiviral agents is to strive for high specificity, making the idea of virus-targeted agents specific to a particular viral component or function attractive, since, ideally, they circumvent the possibility of impacting host function. However, the high propensity of viral genomes, and particularly those of RNA viruses, to mutate and evolve means that selection for resistance can be all too prevalent . Importantly, the high specificity of an agent to a particular virus also inevitably means that its utility against a distinct virus may be limited or non-existent. Thus, it is not surprising that repurposed antivirals active against influenza or HIV, for example, may prove in efficacious against distantly related flaviviruses or coronaviruses.In contrast, antivirals that are host-directed can be repurposed more easily, as long as the viruses in question rely on the same host pathway/functions for robust infection, simply because the host pathway/function targeted is the same ,28. Alth


Background and Objectives: Germany was affected by Bluetongue virus serotype 8 (BTV-8) from 2006 to 2009 and recorded new cases since December 2018. We assessed the economic impact of the epidemic from the first cases in 2006 until 2018. Direct costs include production losses, animal deaths, and veterinary treatment. Indirect costs include surveillance, additional measures for animal export, disease control (preventive vaccination and treatment with insecticides), vector monitoring, and administration.Methodology: To estimate the financial impact of BTV-8 on different species and production types at the animal level, we performed a gross margin analysis (GMA) for dairy and beef cattle, and sheep. To estimate the impact on the national level, we used a modified framework described by Rushton et al. . This figure consisted of 132 (73%) and 48 (27%) million Euros for indirect and direct costs. Indirect costs included 89 million Euros (67%) for vaccination, 18 million Euros (14%) for insecticide treatment, 15 million Euros (11%) for diagnostic testing of animals dispatched for trade, 8 million Euros (6%) for monitoring and surveillance, and 3 million Euros (2%) for administration. The highest costs were induced by a compulsory vaccination campaign in 2008  and the disease impact on cattle in 2007 .Discussion: We compare the outcome of our study with economic analyses of Bluetongue disease in other countries, and discuss the suitability of GMA and the developed tools for a wider application in veterinary economics. Orbivirus within the family Reoviridae. The virus is transmitted by biting midges of the genus Culicoides. At least 27 BTV serotypes have so far been detected worldwide (Bluetongue (BT) is a non-contagious infectious disease of domestic and wild ruminants caused by the BT virus (BTV), which belongs to the genus orldwide . All rumorldwide –7. Effecorldwide .https://tsn.fli.de; public site TSIS: https://tsis.fli.de).In August 2006, BTV-8 emerged for the first time almost simultaneously in Belgium, France, Germany, and the Netherlands , 10. TheTo determine the distribution and spread of BTV-8, the European Commission issued instructions for monitoring and surveillance in the member states of the European Union (SANCO/10581/2006 Rev 4). These included serological surveys and testing sentinel animals for antibodies to detect potential new cases as early as possible in 2007. Based on this working document, the European Commission regulation (EC) No 1266/2007 was launched, which established harmonized disease control measures, including preventive vaccination, a sentinel program, vector monitoring and monitoring in wild ruminants.The following measures were initiated in Germany : (i) a cDespite these measures BTV-8 re-occurred in May 2007. The disease spread over wide parts of Germany and affected more than 20,000 farms, causing the death of animals and substantial production losses, especially in sheep , 13–16.As soon as commercial vaccines against BTV-8 had become available, they were tested for safety and efficacy , 18. GerIn August 2015, BTV-8 re-emerged in France . Comparehttps://www.destatis.de/). Livestock farming is the main source of income in agriculture in the country (There are ~11.8 million cattle in Germany (thereof about 40% dairy) and 1.6 million sheep . The spreadsheets for both, the GMA and the economic model, as well as user manuals, are provided in To calculate direct losses on the animal level, we used a gross margin analysis (GMA). To estimate the economic impact of BT on the national level, we applied a modified framework previously described by Rushton et al. , 27 Fig and a sthttps://ec.europa.eu/eurostat), the official German animal disease notification system , the Federal statistical office , the Identification and Information System for Animals , and the Federal Office for Agriculture and Food . Other input parameters were obtained from the Bavarian State Agency for Agriculture , the German Association for Technology and Structures in Agriculture , the animal health services of the federal states (Tiergesundheitsdienste), and the animal disease compensation funds of the federal states (Tierseuchenkassen). Values for the surveillance costs were obtained from reports of the federal states to the German Federal Ministry for Food and Agriculture and the annual applications of the Federal Ministry to the European Commission for co-financing animal disease control and surveillance . Parameters with fluctuation  were resampled from known values with 10,000 iterations. Details are given in The national average of herd performance as well as epidemiological and economic data were collected from Eurostat (py), were estimated by calculating the difference between the gross margin (GM) of a healthy animal and the GM of a clinically ill animal. The GM was calculated per year (2006–2018) separately for dairy cattle (GMDy), beef cattle (GMFy), and sheep (GMSy). Since infected calves and heifers were rarely reported to show clinical signs, we focused on adult animals. The GMA was performed according to standard procedures (https://www.stmelf.bayern.de/idb/default.html). To calculate the impact of BTV-8 at the animal level, we included the value of lost animal production with the disease-related intervention costs. Details of the GMA are provided in Dy), Fy), Sy). For example, GMDy was calculated as follows:Direct costs at the animal level, i.e., production losses due to clinical illness (dCmiy), animals (Rany), and manure (Rmay), and the variable costs (VC) for restocking (VCry), feed (VCfey), calf rearing (VCcry), veterinary treatment (VCvy), water/electricity (VCway), insemination (VCinsy), machines (VCmacy), hired labor (VClaby) and miscelaneous (VCmisy).i.e., including the revenues (R) for selling milk , lower milk yield, and costs for restocking . In beef cattle, the main impact of BTV-8 was due to a drop in feed intake during the first days of disease, resulting in reduced daily weight gain and thus in a prolonged fattening period . For sheep, losses were mainly attributed to reduced revenues for selling animals (due to reduced slaughter weight) and the need to purchase new ewes (increased replacement rate resulting from death of ewes and lamb losses). In all animal species, the disease increased the costs for veterinary treatment. Details on the influence of BTV-8 on the GM are provided in BT) includes direct (DCy) and indirect costs (ICy) and was calculated as follows:The results of the GMA were extrapolated from the animal level to the national population level separately for each species , production type , and year (2006–2018). Details on the economic model are provided in y) include production losses due to clinical illness (DCcy) and the value of the animals that succumbed to the disease (DCdy):Direct costs at the national level per year , we multiplied the number of animals that had developed clinical signs with the average direct costs per animal , which had previously been calculated in the GMA . The number of animals that developed clinical signs were estimated by multiplying the number of newly infected cattle (nCiy) and sheep (nSiy) with the estimated morbidity for cattle (rcc) and sheep (rsc), and in case of cattle, with the proportion of dairy (pd) or beef (pf) cattle in the total cattle population.To estimate the production losses caused by clinical illness (DCDcFor cattle (rcc), morbidity was estimated to range between 5 and 15%, and for sheep (rsc), between 15 and 25%. The number of newly infected cattle and sheep per year were estimated as follows:sy is the yearly incidence per species , and nczy and nszy the number of cattle and sheep in the restriction zones.where Isy for the year 2006, we used the results of a cross-sectional study performed in early 2007 (y) and Isy remained constant over the years. Isy was therefore estimated as follows:To estimate Irly 2007 . Since ty) and sheep (nSiy), we multiplied the number of cattle (nczy) or sheep (nszy) in the restriction zones with the respective incidence. Regarding the number of animals in the restriction zones, we used the numbers of cattle and sheep kept in the BT-affected federal states for the year 2006, and the whole German cattle population for the years 2007–2011. Since 2012, no restriction zones for BT had remained.To estimate the numbers of newly infected cattle (nCiy) and sheep (vsy). The numbers of dead cattle (nCdy) or sheep (nSdy), respectively, were estimated based on data provided by the animal disease compensation funds and animal health services for the year 2007, assuming that the relation between newly infected  and dead animals  in 2007  remained constant throughout the years. Compensation includes the common value of the animals and for cattle also the disposal costs.To estimate the value of animals that succumbed to disease (DCd), the number of dead animals was multiplied with the compensation paid by the animal disease compensation fund for cattle (vcy) include the costs for all legal provisions successively implemented to control BTV-8, including surveillance (ICSy), measures for animal export (ICEy), treatment with insecticides (ICIy), vaccination (ICVy), vector monitoring (ICMy) and administration time for establishing restriction zones and reporting (ICAy):Indirect costs at the national level per year (ICy) include the costs for the cross-sectional study performed in winter 2007, the sentinel program (early detection) performed in early 2007, and the BT monitoring for disease detection performed between 2007 and 2018. For cattle, sheep and goats, respectively, the costs for BT monitoring were calculated as follows:The costs for BT surveillance according to SANCO/10581/2006 Rev 4 and Commission Regulation (EC) No 1266/2007  or polymerase chain reaction (PCR), and cELI and cPCR the respective costs for testing.where nfshttps://ec.europa.eu/food/funding/animal-health/national-veterinary-programmes_en.The numbers of tested farms and animals, as well as the costs for sampling and laboratory analysis were retrieved from the national applications for co-financing . These documents are published at f) were estimated as follows:Travel costs for official veterinarians (ctwhere k is the fee per km and d the average distance between the veterinary office and a farm.f) were estimated as follows:Personnel costs for official veterinarians  had to be borne by the farmers and were estimated as follows:Following Commission Regulation (EC) No 1266/2007, Germany was between 2006 and 2008 requested to confirm that all animals intended for movement to BT-free EU member states or export to third countries were negative either in a BT-specific ELISA or by PCR. These additional costs for movement or export testing  were calculated as follows:The costs for treatment with insecticides  treated with insecticides, nisfy the number of infected sheep farms and sf the mean number of sheep per farm.where nczy) and sheep (ICVsy), we accounted for the costs per vaccinated animal and the costs per vaccinated farm. The costs per vaccinated animal were estimated by multiplying the number of vaccinations (cattle nvdcy or sheep nvsy) with the sum of the costs for the vaccine (cattle cvcd or sheep cvsd) and vaccination per immunization dose (cattle cvacd or sheep cvasd). Since vaccines had to be applied by a veterinarian, vaccination costs at the farm level include the numbers of vaccinated farms (cattle nvcfy or sheep nvsfy) and the herd fee charged by the veterinarian (cattle ccf or sheep csf) according to the following equations:Depending on the animal species and the vaccine, two or three injections were required for a complete basic immunization. After that, the animals had to be re-vaccinated once a year. To calculate vaccination costs at the animal level for cattle (ICVcy) account for the costs for vector traps and data loggers (cvmty), trap management (cvmmy), and entomological tests (cvme):The costs for vector monitoring , for the establishment of restriction zones and the time required for reporting. Personnel and travel costs for farm visits of official veterinarians were also taken into account, so that calculations were performed according to the following equation:y ist the prevalence of BT , d the average distance between the veterinary office and the affected farm, k the fee charged per driven km, tf the average time spent per farm, and ph the average personnel costs for an official veterinarian per working hour.where tPhttps://kb.palisade.com/index.php?pg=kb.page&id=248): (1) all iterations are ranked by ascending values of the input; (2) the ranked iterations are attributed to 10 bins ; (3) the mean of the output values of each bin is computed; (4) 10 output means from the bins are compared. The lowest output mean gets the number at the left edge; the highest of the 10 output means receives the number at the right edge.We analyzed the effect of the input variables where we entered a distribution on the output mean . The sensitivity analysis was performed in @Risk 7.0.0  with a one-at-a-time method , 30, wheFinally, the results of the sensitivity analysis were assessed qualitatively using a tornado plot, which shows how the mean of the model varies over the range of each input variable.For the dairy sector, direct costs ranged between 119 and 136 Euros per infected animal, depending on the milk price . Most ofThe net total costs of the BTV-8 epidemic in Germany, including prevention and control measures over the last 13 years (2006–2018), ranged between 157 and 203 million Euros  . This fiMean indirect costs included 106.5 million Euros for disease control measures , 14.9 million Euros for additional measures relating to export (12.3 million only for cattle), 7.9 million Euros for BT monitoring and surveillance (including 1.2 million Euros for vector monitoring in 2007 and 2008), and 2.8 million Euros for administration. Disease control measures consisted of 88.6 million Euros for vaccination  and 18.0 million Euros for treatment with insecticides (16.9 and 1.1 million Euros for cattle and sheep) see , 3.Mean direct costs mainly arose in the cattle sector  . In the The yearly costs were highest in 2008 and 2007, with 66.8  and 59.1 million (32%) Euros, respectively . After pIn 2007, the total costs were mainly attributable to direct costs caused by BTV-8 infections. In 2008, total costs accrued mainly from vaccination  . In 2009Between 2012 and 2018, no animal trade restrictions were in place, but monitoring and surveillance were still carried out. These measures caused costs of about 150 thousand Euros in 2013–2015. In 2015, monitoring and surveillance costs increased due to the voluntary vaccination program .Sensitivity analysis showed that the proportion of infected animals that develop clinical signs and the impact on milk yield were strongly related to the veterinary treatment costs and production losses. The costs per vaccination dose had the strongest impact on the indirect costs .When BTV-8 emerged in Germany in 2006, no validated contingency plans were available, because the disease had never before occurred in the country and came completely unexpected. Within a short time, BTV-8 had a substantial impact on animal health in the affected livestock species and far-reaching consequences on animal trade, causing severe economic losses. According to our calculations, direct costs amounted to 40 million Euros within a single year (2007). While the direct costs were mainly borne by the farmers, the main proportion of the costs (vaccination) had to be covered by the animal disease compensation funds of the German federal states, and were co-financed by the European Union in 2008 and 2009.To capture the full impact of BTV-8, we chose a study period of 13 years, starting in 2006, when BTV-8 first emerged in Germany, and ending in 2018, 6 years after the disease-free status was re-gained. Yet, since 2018, a new voluntary vaccination campaign is in place in western and southern regions of Germany, due the evolving BT-situation in neighboring countries, in particular Belgium, France and Switzerland.Our study supports the view that the measures taken in reaction to a disease sometimes have a greater financial impact than the production losses caused by the disease itself . With 74After the initial introduction of BTV-8 in 2006, the last outbreak occurred in Germany in November 2009 and the country re-gained the official BT-free status 26 months later, in February 2012. Possibly, the numbers of new infections and thus the direct costs might have decreased anyway due to immunity after natural infection, even without vaccination. Yet, we still regard compulsory vaccination as economically beneficial, as it substantially contributed to reducing virus circulation and eventually to eradicating the disease within a short period . TherefoTo assess the costs of BTV-8 at the animal level, we used the GMA because it is widely used by farmers and can be easily adapted to assess the economic impact both, at the animal and farm level, for any disease with clinical symptoms.Uncertainty regarding some input parameters limited the accuracy of our estimates. A number of key input parameters for the GMA had to be derived from expert opinion. Due to the large variation in BTV-8-associated morbidity, mortality and the severity of clinical disease, as well as large price differences for milk and vaccination  between different regions, farms and years, our estimations were highly variable. Therefore, our model might have under- or overestimated the total costs. A sensitivity analysis identified the parameters that had the highest impact on the model outcome . The fact that these parameters were not included in the calculation may have led to an underestimation of costs in 2006 and 2007. Despite these limitations, our results indicate that Germany has benefited from re-gaining its BT-free status within a short time and that the country is likely to benefit again from vaccination in the event of a new BT epidemic.The economic impact of the BTV-8 epidemic has so far been assessed for Switzerland  and the Livestock production and the epidemiological situation regarding BT in Germany is most likely comparable to the conditions in the Netherlands. The Netherlands and Germany are part of the Common Market of the European Union. Landscape structures on both sides of the border between the two countries are similar. The epidemiological situation regarding Bluetongue disease was comparable, as the BTV-8 epidemic started in the border area between Belgium, Germany and the Netherlands in 2006 and spread rapidly in the entire region, reaching a high prevalence in the affected area of these countries . FarmersNonetheless, our cost estimations are relatively low as compared to the Dutch figures, especially when considering that the number of cattle in Germany is about three times higher than in the Netherlands. For 2006, we estimated a financial impact of about 9 million Euros, compared to 28–32 million Euros in the Netherlands , 33. In The main difference between our analysis and previous studies conducted for other countries consists in the estimation of the direct costs (production losses and veterinary treatment), which was relatively low  in our assessment. In contrast to the study of Velthuis et al. , we estiCulicoides vectors for BTV-8 (C. obsoletus and pulicaris complex) were found to occur also indoors  within 56 days after the first insemination compared to non-infected cows in Dutch herds . The difFor Austria, the total net costs of the BTV-8 surveillance and vaccination programmes 2005–2013 were estimated at 22.8 million Euros . In the In conclusion, our study shows that the BTV-8 epidemic caused high direct costs in Germany in 2007 and high indirect costs for the compulsory vaccination programme in 2008–2009. The measures taken in reaction to the emergence of BT had a greater financial impact than the production losses caused by the disease itself. It should be pointed out, however, that vaccination proved effective with regard to disease eradication within a short time, thus reducing the suffering of animals and allowing international trade without restrictions.The tools we developed are widely applicable for analyzing the economic impact of livestock diseases at both, the animal and the national level. They were implemented in widespread software (Excel and @Risk), so that they can be easily used, also by decision makers without programming skills. The use of GMA for assessing the economic impact at the animal or farm level ensures that we speak “the same language” as farmers who are used to communicate with GMA figures, when they analyse and discuss their economic situation. @Risk  is an Excel add-in that allows using distributions rather than fixed values, i.e., stochastic modeling. Furthermore, @Risk supports the analysis of stochastic models. It is easy to use for persons who are familiar with Excel and is also used by other groups for economic analysis , which We developed an economic model to calculate the direct and indirect costs BTV-8 for the years 2006–2018 in Germany, a country where BTV-8 has been successfully eradicated in the past. The model may assist stakeholders and decision makers in the planning of future control strategies. The results of the model may be useful to decide on further preventive and control measures in the current BTV-8 epidemic in Germany. The model may also be adapted for other countries and other vector-borne diseases.All datasets generated for this study are included in the article/JG, FC, and CP contributed conception and design of the study. JG and CP developed and performed the economic analyses. CP, FC, and JG wrote the manuscript.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.


Wolbachia, which spreads in insect populations and blocks viruses from replicating. While this strategy has been successful, details of how this “pathogen blocking” works are limited. Here, we use a combination of virus infections, fly genetics, and transcriptomics to show that Wolbachia and virus interact at host nucleotide metabolism pathways.Recently developed arbovirus control strategies leverage the symbiotic bacterium  Wolbachia is a maternally transmitted bacterium that manipulates arthropod and nematode biology in myriad ways. The Wolbachia strain colonizing Drosophila melanogaster creates sperm-egg incompatibilities and protects its host against RNA viruses, making it a promising tool for vector control. Despite successful trials using Wolbachia-transfected mosquitoes for dengue control, knowledge of how Wolbachia and viruses jointly affect insect biology remains limited. Using the Drosophila melanogaster model, transcriptomics and gene expression network analyses revealed pathways with altered expression and splicing due to Wolbachia colonization and virus infection. Included are metabolic pathways previously unknown to be important for Wolbachia-host interactions. Additionally, Wolbachia-colonized flies exhibit a dampened transcriptomic response to virus infection, consistent with early blocking of virus replication. Finally, using Drosophila genetics, we show that Wolbachia and expression of nucleotide metabolism genes have interactive effects on virus replication. Understanding the mechanisms of pathogen blocking will contribute to the effective development of Wolbachia-mediated vector control programs. Wolbachia is an alphaproteobacterium that establishes intracellular infections within arthropod and nematode hosts. Wolbachia is well characterized for inducing reproductive manipulations of arthropods in order to facilitate maternal transmission and spread throughout a population. In many cases, this reproductive manipulation is linked to the ability to protect the same host from secondary infections with pathogens, especially RNA viruses (Wolbachia strain infecting Drosophila melanogaster (wMel) both induces sperm-egg incompatibilities (known as cytoplasmic incompatibility [CI]) and blocks pathogens  pathway, and induction of immune pathways via reactive oxygen stress  immune gene expression via qRT-PCR (Drosophila cell lines with and without wMel (Drosophila and wMel across fly development (but without a comparison to flies without Wolbachia)  Droout wMel , 19, (C)lbachia) .Drosophila melanogaster is the native host for wMel, representing a stable host-microbe relationship  in Drosophila melanogaster  with a time series , to assess the effect of Wolbachia and virus on Drosophila and Wolbachia gene expression. We generated ∼1.56 billion reads with a mean quality score of 34.21 across 48 libraries. On average, each library had 32.5 million reads. We detected no significant contamination in our libraries: libraries derived from Wolbachia-free flies had few reads mapping to the Wolbachia genome, and they were likely from the microbiome as they mapped only to conserved portions of rRNA genes and had perfect BLAST hits to genera such as Lactobacillus and Acetobacter, which are core components of the Drosophila melanogaster gut microbiome . The first dimension of the MDS plots separated samples by time, highlighted by the arrows overlaid on Wolbachia colonization, whereas dimension three separated samples based on virus infection . There were also significant effects of Wolbachia alone  and time alone . Indeed, by 48 h postinjection (hpi), for Wolbachia-free flies, SINV genome abundance increased 6-fold, whereas Wolbachia-colonized flies experienced only a 2-fold increase in SINV genome abundance  are much stronger  plots of the global similarity in fly gene expression revealed clustering of samples based on their nfection . Three-dINV-time . In conteviously . To infeeviously . SINV abbundance . It shoustronger .10.1128/mBio.03472-20.1FIG S1FIG S1, DOCX file, 0.02 MB.Changes in gene expression. Download Copyright © 2021 Lindsey et al.2021Lindsey et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Wolbachia colonization, regardless of time and virus infection (https://doi.org/10.5061/dryad.x69p8czh5]). Of these, 123 were upregulated and 114 were downregulated in the Wolbachia-colonized flies. We also detected significant differences is isoform usage due to Wolbachia: 8 of the differentially expressed genes (DEGs) also displayed differential isoform usage, and an additional 48 genes displayed differential isoform usage without any significant changes in the overall level of gene expression (see Tables S2 and S6 at Dryad [https://doi.org/10.5061/dryad.x69p8czh5]). Changes in isoform usage included changes to both exon usage and/or the transcribed regions of 3′ and 5′ untranslated regions (UTRs). In total, 285 genes were either differentially expressed and/or displayed differential isoform usage.Differential expression analyses revealed 237 loci that were significantly differentially expressed due to 10.1128/mBio.03472-20.2FIG S2Wolbachia colonization. Download FIG S2, DOCX file, 1.1 MB.Transcriptomic response to Copyright © 2021 Lindsey et al.2021Lindsey et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Wolbachia colonization. These include stress responses, ubiquitin-related processes, metabolic functions, transcription and translation, RNA binding and processing, and recombination and cell cycle checkpoint.We identified a core set of these 285 differentially expressed genes/isoforms that were predicted to interact with each other . Annotathttps://doi.org/10.5061/dryad.x69p8czh5]). For 15 of these genes, time also had significant interactive effect on their level of expression, which is consistent with the MDS analyses (see Table S4 at Dryad [https://doi.org/10.5061/dryad.x69p8czh5]). Virus infection resulted in significant differences in isoform usage for 38 genes, two of which were also significantly differentially expressed at the gene level (see Table S6 at Dryad [https://doi.org/10.5061/dryad.x69p8czh5]). In total, 193 genes were differentially expressed and/or displayed differential isoform usage due to SINV. Again, we clustered genes with significant differences in expression due to virus, or virus*time based on their predicted interactions and identified a core network of genes   .Wolbachia and virus, it is clear that on a global level, Wolbachia-free flies responded more dramatically to virus infection . It should be noted that these differences are subtle enough on a per-gene basis that they would not meet the criteria for an interactive effect of Wolbachia and virus, but across the set of upregulated DEGs, we identified significant differences in the average log-fold change in gene expression between Wolbachia-free and Wolbachia-colonized flies. Upregulated DEGs were significantly more highly expressed due to the interaction of Wolbachia colonization and time postinfection . There were also significant effects of Wolbachia alone  and time alone . Indeed, at 6 hpi, for Wolbachia-free flies, upregulated virus-responsive DEGs had an average of a 3.79-fold increase in expression relative to flies without virus, whereas Wolbachia-colonized flies on average experienced only a 2.57-fold increase in expression of the same DEGs . Additionally, Wolbachia colonization alone had no significant effect on the change in expression of downregulated virus-responsive DEGs . In other words, genes that were downregulated in response to virus infection did not show a significant effect based on Wolbachia colonization. Time postinfection was the only factor that had a significant effect on the level of DEG expression , as downregulated DEGs were most strongly downregulated at 6 hpi, and expression levels increased as flies recovered .In contrast, the interaction between ecovered . HoweverWolbachia and virus (either including or excluding the time factor), we identified 34 genes that responded interactively to Wolbachia*virus and/or Wolbachia*virus*time at the level of isoform usage (https://doi.org/10.5061/dryad.x69p8czh5]). These genes with interactive effects at the level of splicing were also significantly differentially expressed due to either Wolbachia or virus alone. These 34 differentially spliced genes include a range of predicted functions including transcription and translation , cytoskeletal organization , nucleotide metabolic processes (Pde11), and immune and stress responses (Irc and cert), among others (https://doi.org/10.5061/dryad.x69p8czh5]).While we did not identify any genes with expression levels that changed due to the interaction of Wolbachia- and virus-responsive gene sets are. Each gene was classified as either “Wolbachia-responsive.” “virus-responsive.” or “interaction-responsive” (for the 34 genes mentioned above) or as those affected by both Wolbachia and SINV, but noninteractively . We identified one core network that includes genes across all responses, with numerous connections between Wolbachia-responsive, virus-responsive, and interactive response genes . Enrichments included amino acid metabolic processes, purine biosynthesis, and other small-molecule metabolic processes.Next, we clustered all infection-responsive genes (at the level of either gene expression or/and isoform usage) to determine how interconnected the se genes . This clWolbachia colonization and virus infection affected expression of the entire de novo purine and pyrimidine synthesis pathways ] ] . Interesleotides , 32 and leotides . While p1.7-fold .prat2 in virus-infected flies, the slight upregulation in Wolbachia-colonized flies, and the presence of prat2 within the central “hub” of the joint network , with expression induced using heat shock conditions (Hsp.70-GAL4 driving UAS-anti-prat2). Sibling controls without the prat2-targeting shRNA recapitulated the increase in prat2 expression seen in Wolbachia-colonized flies , similar to what was observed in the RNA-Seq data set with the w1118 flies (1.7-fold increase). In both Wolbachia-colonized and Wolbachia-free flies, prat2 knockdown was effective, resulting in prat2 mRNA levels being reduced to 24.3% and 39.6% of the sibling controls, respectively . Neither heat shock nor knockdown had a significant effect on Wolbachia titer , which is known to affect the efficiency of pathogen blocking . Sibling controls (no shRNA) with and without Wolbachia recapitulated the pathogen-blocking phenotype, with SINV titers significantly reduced, by approximately half a log, in the Wolbachia-colonized flies , typical of what has previously been seen in this system  and antiviral in the absence of Wolbachia , indicating that nucleotide metabolic processes are likely a point of interaction between host, Wolbachia, and virus in this system.Given the strong downregulation of  network , we chosectively . There wia titer   stress responses, (B) ubiquitination, (C) transcription and translation, (D) RNA binding and processing, (E) metabolism, and (F) cell cycle checkpoint and recombination. Many of these have been previously explored in host-Wolbachia relationships in more targeted studies   and/or uitylase , 42). Thexplored , which io acids) . WolbachWolbachia, the magnitude of response was significantly muted in flies with Wolbachia. This may be due to a priming effect due to Wolbachia’s established presence, or the virus may be so impaired from the initiation of infection that the host elicits a milder response. The virus-responsive network contained fewer cellular processes than did the Wolbachia-responsive network: the response to virus mainly affected the expression of endomembrane system-associated genes and metabolic pathways. Like other intracellular infections, viruses can have strong effects on host cell metabolism that may be a combination of proviral cascades initiated by the virus or antiviral responses by the host. It is notable that the virus-responsive metabolic pathways that we identify here are largely distinct from the Wolbachia-responsive metabolic pathways, though there is likely the potential for interaction at the level of metabolites and flux in the cell.We next identified the changes in gene expression and isoform usage due to the presence of virus. While the genes that responded to the viral infection were the same in flies with and without Wolbachia’s restructuring of the intracellular space could lead to changes in localization, posttranslational modification, or the availability of cofactors and substrates that may be critical for the expression of an antiviral effect  that result in dissimilar downstream events that are dependent upon both (A) the host and (B) the combination of other Wolbachia-induced changes in physiology  of pathogen blocking between different ciations ). In manWolbachia and virus. This agrees with previously published studies , which was significantly differentially expressed due to Wolbachia colonization in our study. Similarly, an excess of pyrimidines rescues virus replication in the presence of this antiviral compound. A separate group of antivirals, brequinar, leflunomide, and derivatives, are also known to interfere with dihydroorotate dehydrogenase and pyrimidine pools, which is responsible for the broad-spectrum antiviral effect , a w1118 background infected with Wolbachia strain wMel2, and its Wolbachia-cleared counterpart were used in transcriptomic experiments  supplemented with 1% l-Gln, 1% antibiotic-antimycotic (Gibco), 1% nonessential amino acids, and 10% heat-inactivated fetal bovine serum (FBS) (Corning). SINV  to generate a P0 virus stock, which was then used to infect new BHK-21 cells to generate P1 virus (BHK-21 cells (American Type Culture Collection) were grown at 37°C under 5% CO3’2J-GFP ) was preP1 virus . The supP1 virus .Wolbachia and virus infection on fly gene expression, and the effect of virus on Wolbachia gene expression, we established in vivo systemic viral infections in adult Drosophila, using a block design with a time series. Flies with or without Wolbachia (W+/W−) were injected with either virus or saline (SINV+/SINV−) and collected at 6, 24, and 48 h postinjection (hpi). For each unique condition of W-SINV-time, we generated four biological replicates (A toD), with each replicate consisting of a pool of five virgin females. Specific conditions for generating the fly infection conditions are as follows. Five-day-old virgin female Drosophila flies were anesthetized with CO2 and injected with either (a) 50 nl sterile PBS or (b) 50 nl of freshly grown SINV (1010 PFU/ml in PBS) using a nanoinjector (Drummond Scientific). Pools of five flies  were injected in a randomized order across a 5-h time period, and capillary needles were changed between fly types (Wolbachia colonized or not) and injection type (PBS or SINV) to avoid cross-contamination. The exact time of injection was recorded, and the pool of five females was placed in a vial containing standard cornmeal-agar medium supplemented with antibiotic-antimycotic (Corning) and a fresh Kimwipe. Subsequently, 6-, 24-, or 48-hpi flies were flash frozen in liquid nitrogen and stored at −80°C until further processing.To determine the effect of Wolbachia colonization status, SINV infection status, and time were split as evenly as possible across three runs on an Illumina NextSeq to generate 75-bp single-ended reads. Each lane contained 1 to 2 of the biological replicates for each condition. An average of 32.5 million reads was generated for each library. Further details and mapping statistics can be found in Table S1 at Dryad (https://doi.org/10.5061/dryad.x69p8czh5).RNA was extracted from pools of flash-frozen flies using TRIzol reagent (Invitrogen) following bead-beating and according to the manufacturer’s instructions. rRNAs and other uncapped RNA species were depleted from RNA samples using Terminator 5′-phosphate-dependent exonuclease (Lucigen). Following a standard phenol-chloroform-isoamyl precipitation, cDNA libraries were prepared with the NEBNext Ultra II directional RNA library prep kit (New England Biolabs) following manufacturer’s recommendations, including a 7-min fragmentation time, 10 cycles of PCR amplification, and use of a specific barcode from the NEBNext Multiplex Oligos for Illumina Index Primer Set 1 or 2 (New England Biolabs). Quality and quantity of total RNA, depleted RNA, and final libraries were assessed using a TapeStation 2200 (Agilent). Libraries were pooled in groups of 16 such that biological replicates of Drosophila melanogaster reference genome (release 6.16) (wMel strain Wolbachia genome (GenBank accession no. NC_002978.6 [Wolbachia * SINV * time’ for Drosophila expression or ‘∼SINV * time’ for Wolbachia expression), with quasilikelihood F tests (function ‘glmQLFit’). Splicing was assessed with the ‘diffSpliceDGE’ function using the ‘Simes’ method. Genes that were significantly up- or downregulated were defined as those with a false discovery rate (FDR) q value of <0.05. To check for SINV reads, libraries were mapped to the SINV TE3’2J-GFP   or the w002978.6 ) using t3’2J-GFP  referenc3’2J-GFP , and map3’2J-GFP . To calcWolbachia-host and SINV-host relationships (see Results), we chose to study key fly pathways to further define these relationships. Stocks were reared and screened for Wolbachia using the same protocols detailed above (see “Drosophila husbandry”). We used a fly stock which carries a UAS-prat2-specific short hairpin silencing trigger . This stock is Wolbachia colonized. To generate balanced heterozygous offspring, we crossed virgin females homozygous for the hairpin to males with a third chromosome balancer . To knock down the expression of prat2, the Wolbachia-colonized, balanced flies carrying the UAS-anti-prat2 insert were crossed to a Wolbachia-free, homozygous, inducible Hsp70:Gal4-driver line . Crosses were performed in both directions to generate Wolbachia-free and Wolbachia-colonized offspring. Virgin females with and without Wolbachia, which contained either (i) both the Gal4-driver and the UAS-anti-prat2 or (ii) sibling controls with the driver and the TM3 balancer, were collected and aged 4 days. At 4 days old, all flies were heat shocked at 37°C for 10 min to induce Gal4 expression. Twenty-four hours post-heat shock, flies were either injected with virus or flash frozen to assess knockdown of prat2 or Wolbachia titer. For virus infections, flies were injected intrathoracically with SINV following the same injection and recovery protocol as used for setting up the transcriptomics experiment. At 48 hpi, flies were harvested and viral titers from single flies were assessed with standard plaque assays on BHK-21 cells using technical duplicates of each fly  according to the manufacturer’s recommendations with specific primers PP25361  , and RNA was extracted and DNase treated according to manufacturer’s instructions. CATT-3′)  and normTCTTG-3′ ) using tWolbachia titer was determined by amplification of the single-copy Wolbachia gene wsp and normalized to abundance of the host gene rpl32 according to previously established protocols (DNA was extracted from single flies using the Qiagen DNeasy blood and tissue kit (Qiagen), according to the manufacturer’s instructions. rotocols  using PoWolbachia. Variation in SINV abundance was assessed with a generalized linear model including Wolbachia colonization status, hours postinjection, and their interaction as fixed effects, and a Gaussian error distribution. Protein-protein interaction networks were constructed with STRING v.1.4.2 .The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus  and are