S-transferase-effector protein (GST-effector protein) can then be attached to the surface of each set. For the assay, users can incubate bead sets individually or in a multiplex format with lysates for rapid, selective capture of active, GTP-bound GTPases from a single sample. After that, flow cytometry is used to identify the bead-borne GTPase based on red bead intensity, and the amount of active GTPase per bead is detected using monoclonal antibodies conjugated to a green fluorophore or via labeled secondary antibodies. Three examples are provided to illustrate the efficacy of the effector-functionalized beads for measuring the activation of at least five GTPases in a single lysate from fewer than 50,000 cells.Small, monomeric guanine triphosphate hydrolases (GTPases) are ubiquitous cellular integrators of signaling. A signal activates the GTPase, which then binds to an effector molecule to relay a signal inside the cell. The GTPase effector trap flow cytometry assay (G-Trap) utilizes bead-based protein immobilization and dual-color flow cytometry to rapidly and quantitatively measure GTPase activity status in cell or tissue lysates. Beginning with commercial cytoplex bead sets that are color-coded with graded fluorescence intensities of a red (700 nm) wavelength, the bead sets are derivatized to display glutathione on the surface through a detailed protocol described here. A different glutathione- Genet3 integrin-mediated cellular entry of Sin Nombre virus (SNV) in the course of a productive infection , 20see122.18 beads/mL, 1 mL of each set (Thermo Fisher Scientific): We use the 5.4 μm sized beads.Cyto-Plex™ far-red fluorescent carboxylated microspheres (beads), uniform 4–5 μm in diameter, 12 sets with 12 discrete dye levels, at 10Carboxyl polystyrene beads, 5% w/v, 10 mL (Spherotech): Our batch was 5.28 μm.Amino polystyrene beads, 5% w/v, 10 mL (Spherotech): Our batch was 3.57 μm.Quantum™ FITC MESF  beads, five sets of commercial beads in which each subset is functionalized with discrete titers of fluorescein conjugates (Bangs Labs).Refrigerated microcentrifuge with swinging bucket rotor and 0.65 mL microcentrifuge tubes.Flow cytometer with a far-red laser, such as an Accuri C6.pH meter.Rotator, nutator.Nitrogen-bubbling apparatus.2.21% (v/v) Tween-20 stock.pH 6 buffer: 0.1 M 2-(4-morpholino)-ethane sulfonic acid (MES), pH 6.0, 0.15 M NaCl, 0.01% (v/v) Tween-20.1-Ethyl-3-(dimethylaminopropyl) carbodiimide hydrochloride (EDAC).Sulfo-N-hydroxysuccinimide (sNHS).Rinse solution: 0.15 M NaCl, 0.01% (v/v) Tween-20, with no pH buffer.3, pH 8.4, 0.01% (v/v) Tween-20.pH 8.4 buffer: 0.1 M NaHCO2 M 1,6-diaminohexane (hexamethylenediamine), pH 8.4.pH 7 buffer: 0.1 M Sodium phosphate, pH 7.0, 0.01% (v/v) Tween-20.Bifunctional crosslinker: 0.2 M Sulfosuccinimidyl 4-[N-maleimidomethyl] cyclohexane-1-carboxylate (sSMCC) in dimethyl sulfoxide (DMSO). Store at −80 °C.0.2 M Reduced glutathione, pH 7.0: Store in 50 μL aliquots at −20 °C.5 mg/mL Alexa Fluor 488 NHS ester (Thermo Fisher Scientific) in DMSO: Store at −80 °CS-transferase-green fluorescent protein (GST-GFP) to measure glutathione on the GST-functionalized beads, or your laboratory’s GST fusion protein and a fluorescent detection agent that binds to it.A fusion protein such as glutathione-2.3seeThe G-Trap assay is used to measure GTP loading of multiple GTPase targets, found in cell lysates , 17. The2.4Following GST-effector chimeras are used for the studies described here:p21 activated kinase protein-binding domain (PAK-1 PBD), a Rac1 effector (MilliporeSigma).Raf-1  RBD, a Ras effector protein (MilliporeSigma).Rhotekin-RBD, a Rho effector protein (Cytoskeleton).Ral-GDS RBD, a Rap-1 effector protein (Thermo Fisher Scientific).GST-RILP, prepared as previously described .2.5Antibodies: Monoclonal rabbit anti-Rap1 (Santa Cruz Bio-technology); monoclonal mouse antibodies anti-Rho  clone 55, anti-Rac1, anti-Rab7, and the secondary antibody goat anti-mouse IgG (H + L) conjugated to Alexa Fluor 488 (MilliporeSigma); monoclonal mouse anti-Ras antibody (Abcam).Activators and inhibitors: Rap1 activator 8-Cpt-2me-cAMP (50 μM) (R&D Systems); Rac1 inhibitor NSC23766 (100 μM) and Rho activator calpeptin (1 μM) (Millipore-Sigma); recombinant epidermal growth factor (EGF) (10 nM) (Thermo Fisher Scientific); mP6, a myristoylated hexapeptide (myr-FEERA-OH), custom synthesized at New England Peptide, H-Ras and K-Ras inhibitor, FTI 277 (100 nM) (Tocris); Rap1 inhibitor (GGTI 298) (10 μM).3VO4, 2% (v/v) NP-40, 0.5% (w/v) sodium deoxycholate. Just before adding to the culture medium supplement with 2 mM phenylmethylsulfonyl fluoride (PMSF) and 2× protease inhibitors .2× RIPA buffer: 100 mM Tris–HCl, pH 7.4, 300 mM NaCl, 2 mM ethylenediaminetetraacetic acid (EDTA), 2 mM NaF, 2 mM Na2, and 1.802 g/L glucose.HHB buffer: 7.98 g/L HEPES , 6.43 g/L NaCl, 0.75 g/L KCl, 0.095 g/L MgCl2, 0.01% (v/v) Tween-20.HPSMT buffer (an intracellular mimic): 30 mM HEPES, pH 7.4, 140 mM KCl, 12 mM NaCl, 0.8 mM MgClBlocking buffer 1: 0.1% Bovine serum albumin (BSA) in HPSMT.Blocking buffer 2: 5% BSA in HPSMT.10 mM EDTA and 0.2% sodium azide for use at 1:10 dilution in storage buffer.33.1seeHigh-site-density glutathione-derivatized beads used for flow cytometry have been synthesized previously from 13 μm dextran-cross-linked agarose beads , 27, andA bead set in its bottle is rocked gently on its side for 2 min, rotated ¼ turn and rocked again for 2 min, and continued until the beads are in a milky suspension. 15 s of immersion in a low-power ultrasonic bath can help the resuspension.seePlace 4 μL of 1% Tween-20 in a 0.65 mL centrifuge tube, add 400 μL of the bead suspension, mix gently with a pipette, and then allow the suspension to settle overnight to coat the beads and the tube with Tween-20, decreasing bead aggregation and adhesion to the tube see.g for 2 min, remove 100 μL of supernatant, and resuspend the remaining 10 μL of beads with a vortex mixer. This standard wash assures that a nominal factor of 10× dilution of the undesired solute is achieved. Resuspension in minimal buffer ensures equal exposure of all beads to the next reagent.Remove all but ~10 μL of the supernatant, resuspend the beads, and give two standard washes. For a regular wash, add 100 μL of pH 6 buffer to 10 μL of suspension, mix with a vortex mixer, centrifuge at 3–5000 × Weigh 4 mg of EDAC and 8 mg of sNHS into a microfuge tube, add 100 μL of pH 6 buffer, immediately dissolve by vortexing, add this to a bead set, and mix. Place the microfuge tube in a rotator with a horizontal axis of rotation for 30 min to keep the beads in suspension, away from the tube lid and sides, while the site density of sNHS ester intermediate builds on the beads.g for 2 min, remove all but 10 μL of the supernatant, resuspend the beads, and then wash two times with 100 μL of rinse solution, which will dilute the EDAC and sNHS while keeping the pH low and the sNHS ester intact.Centrifuge at 3–5000 × step 4 for 30 min. Centrifuge at 3000 × g for 2 min, remove all but 10 μL of supernatant, and resuspend the beads.Resuspend the beads in 180 μL of pH 8.4 buffer, immediately add 20 μL of 2 M 1,6 diaminohexane, mix, and rotate as in seeWash four times with pH 8.4 buffer and resuspend the amino beads into a total of 90 μL of pH 8.4 buffer. We derivatize six sets of beads at a time and leave the six sets overnight at this stage. The amino site density can be measured in a pilot assay to ensure optimal conversion of carboxyl- to amino-terminal groups see.step 4 for 30 min while the site density of the crosslinker’s maleimide builds on the beads, centrifuge, and resuspend the beads in 10 μL.Add 10 μL of 200 mM sSMCC in DMSO, mix, rotate as in Wash with 100 μL of pH 7 buffer and resuspend to 360 μL with pH 7 buffer.seePrepare and test the nitrogen-bubbling apparatus to give a slow series of bubbles see.Add 2 μL of 100 mM EDTA and 20 μL of 200 mM glutathione, pH 7, and bubble nitrogen slowly through the suspension for 2 min to remove most of the oxygen. Cap the tube and rotate it slowly for 30 min.g for 2 min, remove all but 10 μL of supernatant, and resuspend the glutathione beads. Wash beads four times in the storage buffer of your choice, reducing the concentration of glutathione from 20 mM to below 2 μM. Add 1 mM EDTA and 0.02% sodium azide in the storage buffer to inhibit bacterial growth. Store at 4 °C at a concentration of 108 beads/mL. The beads have been stable for over 2 years. A portion of each bead set is diluted 10× in a storage buffer for ease of assay. Each assay uses 104 beads per target GTPase or 1 μL of diluted beads.Centrifuge at 3000 × see2), fluorophores on a bead surface undergo self-quenching with increasing site occupancy [It is useful to quantify the number of GST-binding sites on the newly functionalized beads using commercial Quantum™ FITC MESF see or otherccupancy . It is t3.2Two days before an assay seed a 48-well plate with 20,000 target cells in 100 μL of culture medium per well, resulting in about 50,000 cells the next day. The rate of cell proliferation might vary based on cell type and conditions. The critical target is 50,000 cells at the start of an experiment.Remove the culture medium and replace with 100 μL of serum-free medium overnight. Specific inhibitors of signaling can be added to the cells for the desired amount of time depending on the requirements of the reader’s assay to establish proper inhibition before stimulation.seeAfter stimulating the cells (g for 2 min. The 200 μL of cleared lysate is enough for triplicate assays using 50 μL for each test.Transfer the lysate into a 0.65 mL microfuge tube and centrifuge at 3–5000 × 3.3θ in Kd ~ 80 nM) [Briefly, glutathione beads are mixed with the desired, purified GST-effector protein of desired concentration , incubat~ 80 nM)  measured6 ligand sites/bead. 10 sites or 3.3 nM in 20 μL. Incubating 800 nM (10× Kd) GST ligand with 10,000 beads is expected to yield an occupancy, θ, of 0.91 (or 91%).Site occupancies of ligand-binding sites at saturation are in the range of 1–4 × 104 beads) of each set of 700 nm color-coded glutathione beads with a tenfold excess (120 μL) of HPSMT blocking buffer #1 for 20 min at room temperature, to block the nonspecific binding sites on the particles.Mix 12 μL  separately to the five particle sets, where specific effector proteins are associated with the 700 nm intensity register of the bead. Mix the suspensions gently with a nutator overnight. Centrifuge at 3–5000 × g for 2 min to reduce the supernatants to 5 μL, resuspend the pellet, and dilute it in 50 μL of HPSMT, giving about 8 nM GST-effector. The beads are ready for use and can be stored at 4 °C overnight.Wash the bead sets. For this, add 50 μL of HPSMT to each set and mix, centrifuge at 3000 × 3.4g for 2 min, and reduce the supernatant to about 5 μL. Resuspend the beads in 65 μL of HPSMT, giving approximately 0.8 nM of each GST-effector. Add 5 μL of this suspension to twelve 0.65 mL microcentrifuge tubes for 12 multiplex assays. Leftover beads can be used later to set up the cytometer.Just before the addition of lysates, mix the five different effector beads, centrifuge at 3000 × Add 50 μL of a cleared lysate to each of the 12 tubes, mix, and rotate for 1 h. When prepared as in g for 2 min, reduce the supernatant to about 5 μL, and resuspend the beads in the residual volume.Centrifuge the tubes at 5000 × g for 2 min, and resuspend in 5 μL of residual buffer  against the 5 GTPases to each tube, mix, and rotate the tubes for 1 h.g for 2 min, and resuspend in 5 μL of residual buffer. Add 50 μL of goat anti-mouse antibody fluorescently labeled with Alexa488 (1:100 dilution) to each tube, mix, and rotate the tubes for 1 h.Wash the beads with 50 μL of blocking buffer #2, centrifuge at 3000 × g for 2 min, reduce the supernatants to 5 μL, and resuspend the beads in the 5 μL of residual buffer.Centrifuge the tubes at 3000 × Dilute the beads from each tube with 100 μL of blocking buffer #1 just before each flow cytometric reading.3.53.5.1The single-target format of this assay recapitulates published data . The exa3.5.23 integrin plexin-semaphorin-integrin (PSI) domain and initiates integrin outside-in signaling downstream of Gα13 activation [see13-dependent outside-in signaling caused by SNV [see3 integrin cytoplasmic tail and Gα13 with mP6 inhibits GTP loading of all GTPases associated with integrin activation (Rap1), cytoskeletal remodeling (Rac1), and trafficking (Rab7). The reader is referred to ref. [Integrins are cell adhesion receptors that signal bidirectionally (“inside-out” and “outside-in”) across the plasma membrane . Inside-tivation . In the tivation . The sigtivation , cytosketivation , and cartivation . Here wetion see. We alsotion see to inhibd by SNV . In this to ref.  for the  to ref. .3.5.3de-identified subjects previously hospitalized for hantavirus cardiopulmonary syndrome (HCPS). Sample use was approved under UNM IRB#15–166. The bead sets were prepared as described in Here we use the G-Trap assay to measure in parallel RhoA·GTP, Rac1·GTP, and Rap1·GTP levels in endothelial cells exposed to plasma samples from 12/G13–RhoA·GTP–MLCK (myosin light chain kinase) and Gi-Rac·GTP (Gq-Rap1·GTP) signaling axes are cytoskeletal altering pathways that control cell contraction and spreading, respectively (seeKi ~ 10−8 M), can be used to block thrombin activity [seeseeseeThrombin activates PARs and causes loss of cell barrier function –47. G12/vely see. These sactivity . Becauseactivity , we testactivity . We firs3.5.4Bacteria overcome host defenses, by hijacking Rho GTPases that regulate the actin cytoskeleton , 12, 51.S. pneumoniae on hospital admission) and treated with antibiotics. Vero E6 cells from a cell culture were treated with 10 μL of plasma samples/test. Following a 30-min incubation, Vero cell lysates were prepared as described in S. pneumoniae produces a toxin, pneumolysin, which activates Rac1 GTPases [Here we test the applicability of the G-Trap assay for detecting bacterially induced GTPase activity in serial plasma samples from a de-identified septic patient (UNM IRB #13–312). The patient was diagnosed with community-acquired pneumonia  to amino beads. We use commercial amino beads of similar size with known amino group site density for comparison, with our synthesis. The two amino bead sets are then reacted with NHS-Alexa488 in parallel. Approximately 0.1 mg of NHS-Alexa488 is dissolved in 20 μL of dry DMSO to give about 5 mg/mL, which is stored at −80° C. Ten thousand synthesized amino beads and ten thousand commercial amino beads are put in 20 μL of pH 8.4 buffer, 2 μL of NHS-Alexa488 solution is added, the suspension is mixed, and reagents are allowed to react for 30 min in the dark. The beads are washed twice with pH 7 buffer, diluted to 50 μL of buffer, and analyzed by flow cytometry. We determine nonspecific binding of NHS-Alexa488 to beads by mixing carboxyl beads with the fluorophore. In our setting the fluorescence from the nonspecific attachment of NHS-Alexa488 to carboxyl beads was 20% of the conjugated fluorophores. Our amino beads were comparable to the commercial beads.Bubbling nitrogen slowly through 400 μL of suspension in a 1.6 mL microfuge tube is not easy. We use a narrow nitrogen line and very low nitrogen pressure, and notice that the angle of the tube of suspended beads matters: tipping the slowly bubbling microfuge tube from horizontal to upright can stop bubbling, probably due to increased hydrostatic pressure. Another technique to prevent bubbling is to use a soft nitrogen tubing line, which can be pushed against the bottom of the centrifuge tube to stop bubbling. Tween-20 gives an observable bubble running up the microfuge tube, and we estimate that the volume of air above the suspension is displaced about ten times during the 2 min of bubbling.Blocking of nonspecific binding sites for primary and secondary antibodies with BSA is critical for limiting nonspecific binding. It is also important to test new antibodies in single-target format before using in a multiplex format. In our experience new antibody batches from “trusted sources” can be highly nonspecific, and could bind to all bead surfaces regardless of effector functionalization, and either raise the background intensity for all beads in the multiplex assay or at worst degrade the readout of all the beads in a multiplex configuration.


Andean potato mottle virus from Peru (isolate Lm) was obtained. Comparison of its RNA1 and RNA2 sequences with variants of this virus isolated in Brazil revealed RNA1 and RNA2 nucleotide identities of 81 to 83% and 70 to 71%, respectively.A complete coding sequence of the type strain of  Andean potato mottle virus from Peru (isolate Lm) was obtained. Comparison of its RNA1 and RNA2 sequences with variants of this virus isolated in Brazil revealed RNA1 and RNA2 nucleotide identities of 81 to 83% and 70 to 71%, respectively.A complete coding sequence of the type strain of  Andean potato mottle virus  , and one infected Tetragonia expansa (Aizoaceae) , complete APMoV sequences are lacking.In 1972, virus isolate Lm was obtained from a potato plant showing leaf mottle growing at La Molina in Lima, Peru. It constitutes the type strain of zoaceae) . Later, zoaceae) , 5 and pzoaceae)  was repozoaceae)  and partSequencing methods were as previously described –11. Brie–Comovirus sequences. Amino acid sequence comparisons with Brazilian APMoV isolates showed that Lm’s combined CPs  had 68% amino acid identity with these sequences, whereas their Pro-Pol had 94% amino acid identity. In sequence comparisons between Lm and partial Chinese APMoV isolates’ CP and Pol, amino acid identities were 74% (CP) and 96% (Pol). The nearest comoviruses were Squash mosaic virus (42% CP identity) and Turnip ringspot virus (45% Pro-Pol identity). The latest Secoviridae International Committee on Taxonomy of Viruses (ICTV) report (https://gd.eppo.int/taxon/AVBO00), such studies are needed to ascertain the plant health status of its divergent isolates.Lm’s RNA1 sequence had 81 to 83% nucleotide identities with partial RNA1 sequences of Brazilian APMoV isolates , 8, wher) report  states tMN176101 (RNA1) and MN176102 (RNA2). In the SRA, raw data were deposited under BioSample number SAMN12259772 and BioProject number PRJNA491634.The APMoV genome sequences were deposited in GenBank under the accession numbers


UAG trinucleotide in their core. We systematically analyzed the properties of Musashi binding elements (MBEs) in the 3′UTR of flaviviruses with a thermodynamic model for RNA folding. Our results indicate that MBEs in ZIKV 3′UTRs occur predominantly in unpaired, single-stranded structural context, thus corroborating experimental observations by a biophysical model of RNA structure formation. Statistical analysis and comparison with related viruses show that ZIKV MBEs are maximally accessible among mosquito-borne flaviviruses. Our study addresses the broader question of whether other emerging arboviruses can cause similar neurotropic effects through the same mechanism in the developing fetus by establishing a link between the biophysical properties of viral RNA and teratogenicity. Moreover, our thermodynamic model can explain recent experimental findings and predict the Msi1-related neurotropic potential of other viruses.Zika virus (ZIKV) belongs to a class of neurotropic viruses that have the ability to cause congenital infection, which can result in microcephaly or fetal demise. Recently, the RNA-binding protein Musashi-1 (Msi1), which mediates the maintenance and self-renewal of stem cells and acts as a translational regulator, has been associated with promoting ZIKV replication, neurotropism, and pathology. Msi1 predominantly binds to single-stranded motifs in the 3′ untranslated region (UTR) of RNA that contain a  Flaviviridae family. Researchers have been describing recent outbreaks of these viruses that have not been previously detected for decades3.Flaviviruses are an emerging group of arboviruses belonging to the Flavivirus comprises more than 70 species that are mainly transmitted by mosquitoes and ticks, typically classified into four groups: Mosquito-borne flaviviruses (MBFVs), tick-borne flaviviruses (TBFVs), insect-specific flaviviruses (ISFVs), that do not have vertebrate hosts, and no known arthropod vector flaviviruses (NKVs), which typically infect bats and rodents. Flaviviruses represent a global health threat, including emerging and re-emerging human pathogens such as Dengue (DENV), Yellow fever (YFV), Japanese encephalitis (JEV), West Nile (WNV), Tick-borne encephalitis (TBEV) and Zika (ZIKV) viruses5.The genus 7. There are two main ZIKV lineages, the original African (type strain MR766) and an Asian (type strain FSS13025)9, the latter also comprising American strains such as PE243.Initially isolated in 1947 from a sentinel rhesus macaque in the Ziika forest, Uganda, ZIKV has not been associated with severe disease, apart from skin rashes, body pain, and fever. Likewise, ZIKV has been circulating across equatorial zones in Africa and Asia for 60 years, until the first outbreak was reported in Yap Island, Micronesia in 2007. Subsequently, the virus spread eastwards to French Polynesia and other Pacific islands in 2013 and reached the Americas in 201510. While MBFVs are typically transmitted by host-vector interaction, vertical transmission from mother to child during pregnancy via transplacental infection has been reported11.The 2015–2017 outbreak in the Americas raised the possibility of a link between ZIKV infection and congenital abnormalities, which included placental damage, intrauterine growth restrictions, eye diseases and microcephaly in children as well as acute motor axonal neuropathy-type Guillain-Barré syndrome in adults13. Vertical transmission has been observed with JEV in mice14 and human15 and a case of human fetal infection have been reported after YFV vaccination16. Other transmission pathways of ZIKV include blood transfusions and sexual transmission18. Despite enormous efforts in studying ZIKV infections in the last years, the biological reasoning and mechanisms behind arbovirus congenital neurotropism remain elusive.The neurotropic potential of ZIKV-related flaviviruses has been known since the 1970s, when Saint Louis encephalitis virus (SLEV) has been attributed to a severe neurological disorder in infected mice22.Flaviviruses have the structure of an enveloped sphere of approximately 50 nm diameter. They are single-stranded positive-sense RNA viruses of 10–12 kb in size, and their genomic RNA (gRNA) encodes a single open reading frame (ORF) flanked by highly structured untranslated regions (UTRs). Upon translation of the ORF, a polyprotein is produced which is processed by viral and cellular enzymes, yielding structured  and unstructured proteins . Both flavivirus UTRs are crucially related to regulation of the viral life cycle, mediating processes such as genome circularization, viral replication and packaging23, are stable decay intermediates derived from exploiting the host’s mRNA degradation machinery24.The central role of flavivirus 3′UTR in modulating cytopathicity and pathogenicity became apparent when an accumulation of both gRNA and viral long non-coding RNA (lncRNA) has been observed upon infection. These lncRNAs, also known as subgenomic flaviviral RNAs (sfRNAs)26. The enzyme stalls at highly conserved RNA structures in the viral 3′UTR, so-called Xrn1-resistant RNAs (xrRNAs), resulting in sfRNAs of variable lengths28. Xrn1-resistant RNAs and sfRNAs appear to be ubiquitously present in many flaviviruses. They have been described in MBFVs, including DENV29, YFV30, JEV31, and ZIKV32, TBFVs33, and recently in ISFVs and NKVs35. There is typically more than one xrRNA, given the diverse molecular architecture of different flavivirus 3′UTRs. Pseudoknot interactions have been proposed in some, but not all flavivirus xrRNAs36. While they may form transiently under certain conditions28, conclusive validation of their ubiquitous presence is missing. Hence, we will exclude them in this work. Earlier studies in our group have identified conserved RNA structural elements in viral 3′UTRs41, some of which have later been attributed to xrRNA functionality23. Stem-loop (SL) as well as dumbbell (DB) structures are found in 3′UTRs of flaviviruses in single or double copies , by serving as a template for microRNA (miRNA) biogenesis44. Conversely, in host cells sfRNA modulates the anti-viral interferon response45, e.g., by binding proteins to inhibit the translation of interferon-stimulated genes46. Moreover, sfRNA has been shown to inhibit Xrn1 and Dicer activity, thereby altering host mRNA levels48.The inhibition of Xrn1 by viral RNA yields sfRNAs that affect many cellular processes, both in the vector and the host43 for a comprehensive overview of host proteins that bind flavivirus 3′UTR/sfRNA). Although notoriously underrepresented in literature, one can expect that many of these proteins also bind sfRNA due to sequence and structure conservation.At the same time, a variety of host proteins bind the 3′UTR of flaviviruses, thereby mediating viral replication, polyprotein translation or the anti-viral immune response  domains, whose sequence specificity has been determined by an in vitro selection method and NMR spectroscopy55. The trinucleotide sequence UAG, whose thermodynamic binding specificity was determined by fluorescence polarization assays, has been identified as core Musashi binding element (MBE). Nucleotides enclosing the main MBE recognition motif make minor contributions to binding affinity56. While earlier SELEX experiments identified the binding aptamer sequence (G/A)UnAGU (n = 1 − 3)51, iCLIP experiments with Msi1 in human glioblastoma cells confirmed the preferential binding of Msi1 to single-stranded (stem-loop) UAG sequences in 3′UTRs, but not in coding regions57. Zearfoss et al.56 observed that both GUAGU and AUAGU are recognized by mouse Msi1, whereas Drosophila Msi1 has a higher affinity for GUAGU. NMR-derived structures of the two Msi1 RNA recognition motifs in complex with RNA also show that both RNA-binding domains bind GUAGU (PDB IDs 2RS2 and 5X3Z).One of these groups of host factors is the Musashi (Msi) protein family. Msi is a highly conserved family of proteins in vertebrates and invertebrates that act as a translational regulator of target mRNAs and is involved in cell proliferation and differentiation. While the two Msi paralogs in mammals, Musashi-1 (Msi1) and Musashi-2 (Msi2), are expressed in stem cellsUAG is central to all proposed Musashi binding motifs. Therefore, we focus our calculations around this trinucleotide, and provide evidence that the availability of UAG in pentanucleotides expands to the accessibility of the entire motif.In summary, there is a strong consensus in the literature that 10, de Bernardi Schneider et al.7 reported the presence of the same element with a higher binding affinity for human Msi1 in all ZIKV sequences that belong to the Asia-Pacific-Americas clade in an in silico screen and implied that there could be a change of tropism for the viral lineage. Chavali et al.58 tested the possibility of Msi1 interaction with the ZIKV genome in vivo and found that Msi1 not only interacts with ZIKV, but also enhances viral replication. They noted that ZIKV RNA could compete with endogenous targets for binding Msi1 in the brain of the developing fetus, thereby dysregulating the expression of genes required for neural stem cell development. Based on their data the authors concluded that Msi1 is involved in ZIKV neurotropism and pathology and raised the question whether MBEs present in other flavivirus genomes could exhibit similar functionality. In a recent study, Platt et al.59 investigated whether ZIKV-related arboviruses can cause congenital infection and fetal pathology in utero in immunocompetent mice. They tested two emerging neurotropic flaviviruses, WNV, and Powassan virus (POWV), as well as two alphaviruses, Chikungunya virus (CHIKV) and Mayaro virus (MAYV). All four viruses caused placental infection, however, only WNV and POWV resulted in fetal demise, indicating that ZIKV is not unique among flaviviruses in its capacity to be transplacentally transmitted and cause fetal neuropathology.An interesting, yet understudied hypothesis is the possibility that the stem cell regulator protein Musashi could be related to ZIKV tropism. Based on the identification of a MBE in the 3′UTR of the ZIKV genomein silico. We investigate structural features of MBEs in viral 3′UTRs by a thermodynamic model of RNA structure formation and work out the biophysical properties of conserved RNA structures harboring MBEs in order to build a theoretical ground for future in vivo studies.In this contribution, we systematically analyze the Musashi-related neurotropic potential of well-curated flavivirus genomes https://www.ncbi.nlm.nih.gov/refseq/) on 15 December 2017. We filtered for all complete viral genomes under taxonomy ID 11051 (genus Flavivirus), resulting in 72 genomes, 51 of which had 3′UTR sequences and annotation available  refseq database  occur independently and with equal probability, the expected probability to observe a subsequence of length l is equal to (1/4)l. For L is Ni is the nucleotide count of i. For any trinucleotide XYZ, the expected trinucleotide frequency EXYZ is then computed from mononucleotide frequencies as The core Musashi binding element is only three nucleotides long, hence one can expect to observe a certain number of 60, we were looking to include this sequence into our analysis. Nikos Vasilakis  generously provided SPONV sequence data. The 338 nt 3′UTR sequence of the SA-Ar strain  has been added to the set of flavivirus sequences analyzed here.The refseq genome for Spondweni virus  does not include a 3′UTR sequence. Since SPONV is phylogenetically closely related to ZIKVUAG trinucleotides in the 3′UTRs, consequently it has been discarded from our dataset. The remaining virus species contain between 1 and 19 MBEs in their 3′UTRs.Kama virus (KAMV) does not contain nearest neighbor energy model as implemented in the ViennaRNA Package61. This allows for computing equilibrium properties of RNA such as the single most stable, minimum free energy (MFE) structure, as well as the partition function sE(s) is the free energy of the structure, R the universal gas constant and T the thermodynamic temperature of the system. The equilibrium probability of a secondary structure s is then defined asThe biophysical model employed here is based on a description of RNA at the level of secondary structures, building upon the thermodynamic 62 and allows calculation of individual base pair probabilities, even for large sequences63. In this line, the accessibility  can be computed asThe partition function mentclass2pt{minim63 to compute local pairing probabilities of UAG trinucleotide motifs to assess the likelihood of single-strandedness of and around MBEs. RNAplfold is part of the ViennaRNA Package61 and can compute the accessibilities or single-strandedness of all intervals of an RNA in cubic time65. We select 97 nt windows upstream and downstream of MBEs in viral 3′UTRs and compute local pairing probabilities for base pairs within 100 nt windows. Opening energies for trinucleotides are then evaluated from averaged pairing probabilities with RNAplfold.The opening energy of a region within an RNA is directly related to local RNA secondary structure. In this line, low opening energy is a reliable indicator for single-strandedness. We employ the sliding window approach of RNAplfoldz score statistics. The normalized z score is defined asEopen(XYZ) is the opening energy of trinucleotide XYZ in its genomic context, μ and σ are the mean and standard deviations, respectively, of the opening energies of XYZ computed over a large sample of randomized sequences. Randomization with regard to keeping sequence composition is achieved here by applying dinucleotide shuffling to the 97 nt windows upstream and downstream of MBEs, while keeping XYZ in place. The same idea applies to calculations of pentanucleotide motifs.The significance of a calculated MBE opening energy is assessed by comparison with a large number of randomized sequences of the same length and same base or dinucleotide composition. We compute the opening energies of trinucleotides both in a genomic as well as a shuffled sequence context and apply a 61 scripting language interface for thermodynamics calculations, the ViennaNGS66 suite for extraction of genomic loci and the uShuffle Perl bindings67 for k-let shuffling. The tool reports for each requested trinucleotide the opening energy in a genomic context as well as an opening energy z score obtained from n shuffling events of upstream and downstream sequences. Here, n = 10,000 dinucleotide shuffling events were used.The approach outlined above is implemented in the Perl utility plfoldz.pl, which is available from https://github.com/mtw/plfoldz. The script employs the ViennaRNA68 covariance models for conserved xrRNA elements. The structural RNA alignments underlying the infernal models were computed with locarna69 and further analyzed with RNAalifold61 and RNAaliSplit70.To localize MBEs within homologous substructures in flavivirus 3′UTRs we constructed infernalUAG motifs in 3′UTRs57. To evaluate the thermodynamics of Msi-UAG affinity more broadly, we set out to analyze the single-strandedness of all possible trinucleotides in ZIKV genomes. To this end, we computed the opening energies of all trinucleotide motifs present in the coding sequence (CDS) and 3′UTR of the African (ZIKV-UG) and Asian/American (ZIKV-BR) Zika strains. A z score was calculated for each occurrence of trinucleotide XYZ according to Eq. XYZ in its genomic context with n = 10,000 dinucleotide-shuffled upstream and downstream regions of 97 nt, using 100 nt windows in RNAplfold.The Musashi family of proteins preferentially bind single-stranded z scores indicate increased accessibility, i.e., UAG trinucleotides in viruses with overall low z scores are likely to occur in an unpaired structural context within the 3′UTR. Through the distribution of z scores, sorted by median z score .To assess the Musashi-related neurotropic potential of other flaviviruses, we evaluated the accessibilities of MBEs in related species. To this end, all 435 57, consequently UAG motifs that contribute with low z scores have a high affinity for Msi1 binding. Within the MBFV group, the Asian/American lineage Zika virus (ZIKV-BR) has the lowest median z score, followed by Saint Louis encephalitis virus (SLEV), Nounané virus (NOUV) and the African lineage Zika virus (ZIKV-UG). Among others, two lineages of West Nile virus  and Yellow fever virus (YFV) appear with a negative median z score. ZIKV-BR turns out to be the only isolate among MBFVs that has just negative z score values in our simulations, i.e., all UAG motifs within the 3′UTR of the Brazilian ZIKV isolate appear in an unpaired structural context. Likewise, Karshi virus (KSIV), Alkhumra hemorrhagic fever virus (ALKV) and Langat virus (LGTV) have a strictly negative z scores distribution among the TBFV group. POWV, Omsk hemorrhagic fever (OHFV) and Louping ill virus (LIV) have negative mean opening energy z scores. Interestingly, UAG trinucleotides are relatively depleted in all TBFV species analyzed here (Table z scores. Culex flavivirus (CxFV), Cell fusing agent virus (CFAG), Parramatta River virus (PaRV) and Ochlerotatus caspius flavivirus (OCFVPT) tend to have singe-stranded MBEs among the ISFVs. Here, OCFVPT is the only isolate with a strictly negative z score distribution emerging species like JEV and Usutu virus (USUV), which contain 15 and 19 MBEs, respectively.Several species appear to the right of the plots in Fig. UAG motif within their SL and 3SL elements. Conversely, DB elements, which are conserved in MBFVs and NKVs , dumbbell (DB) and 3′ stem-loop (3SL) Fig.  by meansKVs Fig. , stand oUAG motifs calculated through opening energies in Flavivirus 3′UTRs is indicative of the Musashi-related neurotropic potential of virus species. Our computational analyses show that there is little difference in the distribution of opening energies for all trinucleotides within the polyprotein (CDS) region of ZIKV. When comparing CDS and 3′UTR regions, we see a difference in behavior, as different trinucleotides do possess different opening energies, UAG being highly accessible in ZIKV. Although it is not possible to quantify the impact of the accessibility on the patient phenotype, it is interesting to see the UAG motifs in the Brazilian ZIKV isolate more accessible than in the Ugandan ZIKV isolate. This result raises the question once again if the increased pathogenicity seen in ZIKV today is due to changes in the sequence over time or simply lack of better surveillance71.Our findings lead to the conclusion that the accessibility of 73. Although our results indicate that this may be true for well-studied viruses such as DENV and WNV, other viruses which have not caused recent outbreaks may have been neglected.Previous experiments lead toward the idea that ZIKV is unique among flaviviruses regarding the clinical outcomes resulting from congenital infectionUranotaenia mashonaensis, a Culicidae mosquito not known to harbor flaviviruses before74. While replication has been tested in human and non-human cell lines, vertebrate infection and pathogenesis could not be observed75.Looking in depth at other viruses, Nounané virus (NOUV), a dual-host affiliated insect-specific flavivirus is found among the viruses with high MBE accessibility. NOUV was isolated in Cote d’Ivoire in 2004 from Ornithodoros papillipes ticks in Uzbekistan in 197276 it currently does not present history of infection in humans. Conversely, Powassan virus (POWV), another TBFV with negative MBE opening energy, first isolated in Powassan, Ontario, Canada in 1959 from a child who died of acute encephalitis77 can cause transplacental infection59 and has been associated with severe neuropathology and death in mice and human78.Within the TBFV serocomplex, KSIV has the lowest overall MBE opening energies. Originally isolated from UAG can be regarded as the primary Msi1 binding motif, we can argue that ZIKV has the highest affinity for binding Msi1 among all MBFVs. Platt et al.59 showed that besides ZIKV, the neurotropic flaviviruses WNV and POWV, as well as the alphaviruses Chikungunya (CHIKV) and Mayaro (MAYV) infect placenta and fetus in immunocompetent, wild-type mice. However, only WNV was shown to infect the placenta and the fetal central nervous system, causing injury to the developing brain.Given that 13, WNV79, YFV80 and POWV59.Congenital infection in humans is documented for WNV, JEV, YFV, and ZIKV. CHIKV and MAYV did not show this behavior. In this line, our results are in agreement with experimental studies that reported teratogenicity for SLEV81, a neurotropic virus from the Japanese encephalitis serocomplex, as well as WNV in humans83 and in mice84, USUV86 and DENV88. The fact that these viruses line up more on the positive side of the opening energy plots in Fig. Bizarre neurological manifestations were also observed in patients infected by Ntaya virus (NTAV)Flavivirus DB elements do not only show structural conservation over the MBFV and NKV serocomplexes, but even maintain their primary sequence within a region of approx. 20 nt of the distal stem-loop Figs  and 5. TUAG trinucleotides are the core nucleotides within MBE motifs to contribute the highest binding energy56. Our current analysis underlines that there seems to be evolutionary pressure on keeping UAG motifs within the DB elements unpaired. In ZIKV we see that not only the UAGs within DB elements but also those that overlap with SL elements show negative opening energy z-score.58, this interaction could be a critical reason why ZIKV persists in sperm for a long time after the individual has been infected90, allowing the virus to be transmitted sexually and also why the virus would harbor itself in neuronal cells, allowing it to interfere with and dysregulate neurodevelopment.The presence of Msi1 proteins in both sperm and neural precursor cells highlights the importance of studying the Msi1-MBE interaction in flaviviruses. Given that Msi1 has been shown to enhance ZIKV replication91. Ribosome profiling experiments have corroborated this down-regulatory effect of Msi1, while keeping mRNA levels92. This allows for a speculative explanation of the findings by Chavali et al.58, i.e., that Msi1 enhances ZIKV replication, and a possible role of Msi1 in the viral life cycle: Flaviviruses need to “donate” a few copies of the quasispecies ensemble for Xrn1 degradation and subsequent sfRNA production. In this line, Msi1 could serve as an agent that provides a reasonable amount of gRNAs that are not translated but subject to Xrn1 degradation. The resulting sfRNAs can then down-regulate the host response93.Msi1, which binds to the 3′UTR of target mRNAs, has been shown to repress translation initiation by competing with the translation initiation factor eIF4G for binding to poly(A)-binding protein (PABP), thereby inhibiting the assembly of the 80S ribosomal unitin silico. Our results underline experimental studies suggesting that ZIKV is not alone in its capacity to cause severe neuropathology to infants through the MBE mechanism. While several tick-borne and mosquito-borne flavivirus species like Karshi virus (KSIV), Alkhumra hemorrhagic fever virus (ALKV) or Nounané virus (NOUV) line up with ZIKV in our theoretical model, their tropism might have been overseen due to the lack of reported significant outbreaks. However, some of them appear to have similar neurotropic potential and thus might be potent emerging pathogens.We studied a specific aspect of flavivirus congenital pathogenicity, i.e., the neurotropic effect inferred by the presence of MBEs in the 3′UTR of flavivirus genomes. Employing an established biophysical model of RNA structure formation, we analyzed the thermodynamic properties of MBEs z scores with large scale epidemiologic data could be employed in a machine learning framework that also considers structural conservation and homology of flavivirus 3′UTR elements. Such a tool could play a role in categorizing viruses.The approach presented here could in principle be used for developing a tool to predict the Musashi-related neurotropic potential of novel viruses or (re-)emerging strains of known viruses. Combination of opening energy Supplementary Data


Salmonella control policy. However, the rationale of Salmonella control in pig feeds has been debated after a European Union (EU)-wide cost–benefit analysis, which provided mixed, country-specific results on whether control measures are economically beneficial. The aim of this study was to analyze the costs and benefits of current pig feed Salmonella control in Finland compared to a reduced control scenario. In addition, this study contributes to the literature by looking at the costs across stakeholder groups. The costs of preventive and monitoring measures were assessed, and a Monte Carlo model was developed to simulate costs caused by Salmonella contaminations along the pork supply chain  and because of human salmonellosis originating from contaminated feed. The data were collected from official records and feed sector operators by surveys and interviews. The prevalence of Salmonella was obtained from a previously conducted risk assessment study. The total costs of pig feed Salmonella control were estimated on average to be €4.2–5.4 million per year (95% of simulated years between €2.1 and €9.1 million) for the current control scenario, and €33.8–34.8 million per year (95% €2.2 to €26.0 million) for the reduced control scenario. In the reduced control scenario, the monitoring and prevention costs were decreased down to €1.1–2.1 million, and the costs of Salmonella contaminations and human salmonellosis were up by €32.7 million when compared to the current control scenario. The results suggest that the current pig feed Salmonella control policy of Finland is economically profitable. It can reduce the costs caused by feed-related Salmonella contaminations on average by €29.4 million per year and provides public health benefits. Pig feed Salmonella control can support the effectiveness of the Finnish Salmonella Control Programme. The current pig feed Salmonella control policy benefits the consumers, while a substantial part of the costs are covered by feed operators. In order to increase the acceptability of current policy, greater attention to the allocation of financial responsibilities regarding the control measures may be required.To promote public health, Finland has adopted a stringent  Salmonella is a bacteria which can cause food-borne illness and negatively affect human health. It can be transferred between humans and nonhuman animals through contaminated food, drink, or the environment. Salmonellosis can incur economic losses to society due to increased health care costs, lost working days when people are ill, and mortality  was 10.3%. The estimates ranged by member state from 0% in Finland to 29% in Spain    covers te market .Salmonella control in the pig sector or for feedstuffs has not been investigated. Salmonella control in pig feeds has been considered only by an EU-wide cost–benefit analysis  was positive]: these included an establishment of a Salmonella control support unit and some increased sampling, as well as feed control measures either with or without transport and slaughterhouse measures. By contrast, an establishment of a Salmonella control support unit and some increased sampling with or without specific feed practices and farm-level biosecurity were not financially viable . This principle is called strict liability. The prevalence of Salmonella in the Finnish pork chain is low [e.g., Maijala et al.  treatment and other measures to reduce the risk of Salmonella contamination, cleaning measures and pest control at different stages of the supply chain, statutory Salmonella sampling and official control checks made by authorities, and self-monitoring measures related to Salmonella control in commercial feed manufacturing. The second type of costs includes costs caused by realized Salmonella outbreaks and Salmonella arising from the contamination of pig feed. These costs included the costs of cleaning facilities where Salmonella-contaminated feed or pigs had been detected; the costs of treating contaminated feed with substances permitted to treat feed; losses due to idle production capacity at feed manufacturing, feed storage, or farms; costs due to Salmonella observed at slaughterhouse or in pork; costs due to human cases of salmonellosis; and tracing, product recalls, and labor and material input associated with these measures. The model considered these two types of costs to different stakeholders across the pork supply chain. The stakeholders included feed importers, commercial feed manufacturers, feed transporters, mobile feed mixers, pig farms, slaughterhouses, taxpayers (government), and consumers of pork. The benefits of effective Salmonella control were because of a reduced costs burden caused by realized Salmonella outbreaks and Salmonella arising from the contamination of pig feed (possibly leading to contamination of pigs or their environment).In order to assess the costs and benefits of pig feed L) of control and prevention measures plus costs caused by Salmonella contaminations and human infections in each scenario were calculated as:The total annual costs ; i, j, k, and r are indices representing feed material (i), feed , or animal type (r), respectively, in connection with measures associated with the treatment of Salmonella-contaminated materials, animals, or humans; m refers to “severity” of human salmonellosis; pa′i pa″j, Pftk, Pappr, and Pm represent the probability of Salmonella contamination or prevalence of Salmonella contamination occurring in i, j, k, r, or m; w is the cost caused by Salmonella contamination, or eradication of the pathogen, in i, j, r, k, or m; dk is the proportion of true infections that will be detected; dm is the proportion of each type of human infection; θ is the proportion of infections related to contamination in feed; and Q represents the quantity of pig feed materials, pig feed, pigs, or humans in the study population.where i is the apparent prevalence (pa′) of Salmonella in feed material batches of 25 tons. For costs incurred at the industrial feed manufacturing stage, the apparent prevalence of Salmonella in manufactured compound or complete feed (pa″j) was used. The occurrence of Salmonella contamination in pigs at the farm was modeled by using the probability of contamination (Pftk), and the probabilities were specific to feeding type and animal . As this was the true prevalence, only the proportion dk was considered to result in costly eradication measures.For feed materials at import and storage prior to feed manufacturing, pa′Salmonella in slaughter pigs was assigned with the observed prevalence of infections (Papp) represented by the prevalence in the lymph node samples, and the costs for infection (wr) were relative to the number of pigs that were assumed to be influenced in the batch when a Salmonella-positive pig was detected. Finally, the annual prevalence of Salmonella infections in humans Pm was determined as a proportion of observed infections that could, according to the source attribution model, be linked to pig feeds. PmwmQmθmfdm therefore represent the product of the prevalence in humans, size of the population in Finland, reporting factor f = 11.5 , which has been called the Finnish Food Authority since January 1, 2019, the Finnish Farm Registry, and from a questionnaire that administered to the feed producers in Finland. The data were collected, and the simulations were carried out for 2013.Data on the volume of pig meat and feed production, and the number of pig farms and pigs in Finland were based on the statistics of Luke  and EvirThe questionnaire was sent to nine feed mill operators, of which six responded. From the 432 pig farms that had reported feed manufacturing, 61 returned completed questionnaires and 53 other farms informed that they no longer had pork production. Only 2 mobile mixers out of 12 filled in the questionnaires. All the respondents did not answer all of the questions. Therefore, any missing operator information was added by using information sourced from other similar operators. Besides the questionnaire, complementary data were gathered by interviewing a mobile mixer and the staff of a feed mill. In addition to the survey and the interviews, cost and price information was collected from laboratories; service providers collaborating with the feed industry, such as pest control operators and warehouse operators; and experts in the feed industry.Salmonella sampling , possible fees by authorities, and quarantine storage for high-risk feed materials. The Finnish Food Authority (formerly Evira) is responsible for controlling Salmonella in feed. The control is based on legislation and described in the annual control plans. This covers the control of feed mills and other operators. The authorities carry out spot checks for the imported and non-imported feeds and control that feeds meet legal requirements.Costs of preventive measures related to the import of feed and feed materials are caused by statutory Salmonella samples are taken as official sampling from high-risk feed imported from outside the EU member states, and mainly as self-monitoring from the high-risk feed within the EU member states. More intensive monitoring is currently required for high-risk than non-high-risk feed materials. A Ministry of Agriculture and Forestry decree on the pursuit of activities in the animal feed sector (548/2012) states that high-risk feed materials listed in annex 3 of the decree  and feed imported from outside the EU member states must be analyzed by official sampling, and by self-monitoring when importing from the member states. The amounts of imported high-risk feed materials used for pig feeds were evaluated based on the amount of manufactured pig feed per operator and the sample pig feed recipes obtained from feeding experts. The imported high-risk feed material attributed to pig feed production was about 55,000 tons in 2013. The additional warehouse capacity for the prolonged storing of feed at the harbor because of waiting for laboratory results for 4–6 days was included in the costing.In Finland, Salmonella sampling, the treatment of feed, maintaining appropriate hygiene and cleanliness in the facility, self-monitoring, pest control, and official inspections, including the official Salmonella samples. Feed manufacturing was controlled by inspections and sampling based on the authorities' control plan, which focuses on those control points considered most risky. All the feed manufacturers were required to have a self-control system for a hazard analysis and critical control points (HACCP). Sampling and other measures are defined by the HACCP. Large feed mills were inspected annually. It was mandatory for all feed operators who produced more than 6 million kilograms of feed per year to treat their products with heat or acid to mitigate Salmonella in feed . Based on the survey, only two of the operators used other treatments than heat treatment.For the commercial feed manufacturers, such as feed mills, costs related to preventive measures consisted of Salmonella control measures applied by mobile feed mixers. In the case of pig farms, costs included in the assessment were Salmonella sampling, pest control, maintaining appropriate hygiene and cleanliness in feed storages and feeding facilities, and acid treatment when using liquid feeding (about 70% of farms).Acid treatment, maintaining appropriate hygiene related to mobiles, self-monitoring measures, and official inspections were considered as Salmonella control, as all the measures besides Salmonella sampling were assessed to be carried out also to prevent other diseases than Salmonella. The share attributed to Salmonella was evaluated by the feed sector experts individually to each measure, and they represent the proportion of costs that could be saved if Salmonella control were to be discontinued. This approach was chosen in order to take into account that preventive measures may mitigate both Salmonella and other diseases. As feed heat treatment would be carried out to some extent also when there was no mandatory Salmonella control, zero percent of the costs of treatment equipment maintenance and installation costs, and 20% (feed mills), 50% (mobile mixers), and 10% (farms) of the labor and material costs were assigned to Salmonella. Overall, 25% of the costs of official feed control, maintenance of appropriate hygiene and cleanliness, pest control (except 14% for feed mills), and self-monitoring (except 50% for feed mills) were assumed to be attributed to Salmonella. Potential impacts of preventive costs to market-clearing prices and quantity traded were not considered in the current analysis because the costs were fairly small when compared to the volume of Finnish pork production.The costs were assessed by first estimating the total annual cost of monitoring and preventive control measures. These costs were obtained from the stakeholder survey and interviews. Second, a share of these costs was attributed to pig feed in relation to the share of manufactured pig feed of all feed, since especially commercial feed production operators purchase materials and produce feed for many types of animals, and further to Salmonella control scenario when compared to the current control policy scenario.The parameters assumed to represent the costs of preventive measures in the current control scenario are provided in Salmonella control, fewer Salmonella contaminations along the pork supply chain and fewer human cases of salmonellosis can occur, thus reducing the costs of illness and contaminations along the food supply chain. The costs related to Salmonella were first estimated per Salmonella case, and then the number of cases was simulated for the two control scenarios by using a seeded Monte Carlo simulation model programed in MATLAB R2014b 8.4.0.150421  to calculate the total annual costs of Salmonella contaminations and infections.As a consequence of the Salmonella contaminations included the statutory measures and additional voluntary measures taken by feed importers, feed mills, mobile feed mixers, pig farms, and slaughterhouses in accordance with the current control policy to eliminate Salmonella when it was simulated to occur in the pork supply chain. Measures included additional samples taken to verify Salmonella contamination and freedom from the bacterium; washing, cleaning, and disinfecting of facilities contaminated with Salmonella; and the treatment of contaminated feed. Salmonella-positive findings had to be communicated to authorities who are in charge of further actions carried out in cooperation with the feed business operator. If a sample from a feed consignment imported from the EU or from outside the EU was found positive for Salmonella, the contaminated feed was assumed to be treated with heat or acid. In the event of Salmonella contamination in pigs or pig farms, the cost included the treatment or culling and rendering of infected animals, business interruptions caused by restrictive measures which prevent the farm from selling animals, labor effort by authorities and stakeholders to handle the case of Salmonella contamination, and costs caused by infections in humans .Costs caused by Salmonella and its sequela in humans was estimated by using the disability adjusted life year (DALY) method. DALY is a non-monetary approach to estimate health implications of a disease. The average cost per human infection was estimated to range from €530 to €620 per case. This includes the cost of health care and productivity loss of acute symptoms (gastroenteritis with a raised body temperature and bloody diarrhea), sequela , and death. Death was valued at €55,000 per lost human life year , percentiles) describing the prevalence of Salmonella at different stages of the supply chain were obtained from Rönnqvist et al. , the probability for infection due to feed (Pftk), and the annual prevalence of Salmonella infections in humans (Pm), were the most important parameters differing between the scenarios, because in the reduced control scenario, Salmonella contamination of feed was not considered to lead to an action. Under the current control policy scenario, the apparent prevalence of Salmonella in pigs was assumed to be presented by a parameter value of 0.139% (SD 0.061), when feed was given to sows, and by a parameter value of 0.074% (SD 0.030), when feed was given to fattening pigs. The number of human cases was simulated by using three distributions. It was assumed that of 337 reported cases in 2013, multiplied by an underreporting factor of 11.5, 12.29% (SD 3.756) were associated with pig meat, and of cases associated with fattening pigs, 33.63% (SD 14.62) were associated with pig feed. Under the reduced control scenario, the number of cases in humans and pigs was simulated to be 55.42 (SD 31.54) times the number of cases simulated under the current control policy scenario.Parameters, which represent the prevalence of Salmonella control, Salmonella contaminations, and human cases associated with the current pig feed Salmonella control, as well as with a reduced control policy scenario. In addition to these, several sensitivity analysis scenarios were simulated. In the sensitivity analysis scenarios reported in the Results section, the costs parameters for the prevention and monitoring measures were doubled , compared to the baseline scenario or the cost parameters for measures taken when Salmonella has been detected (contaminations or human cases), which were halved . The parameters were adjusted (either increased or decreased) separately for feed importation, feed manufacturing, pig farms and the slaughtering phase, and human cases (one stakeholder group at a time); for all prevention and monitoring measures simultaneously; and for all contaminations and human cases simultaneously.Previous sections described the baseline parameter values used to simulate the costs of Salmonella control policy scenario, the total costs of measures to monitor and prevent Salmonella in pig feeds were €1.8–3.0 million per year .Salmonella control were substantially lower in the current control policy scenario than in the reduced control scenario. In the current analysis, the costs of human cases were simulated assuming a fixed average cost per case. Separating the costs by different types of human infections would have further increased the variation of simulated costs as fatality cases carried a high cost.The results showed a substantially larger variation in the costs of the reduced control scenario than the current control scenario ; Table 4Salmonella were doubled, or the cost parameters of measures taken when Salmonella has been detected were halved. As Salmonella also had a potentially substantial impact of the total costs. Adjusting assumptions regarding the cost parameters of prevention and control measures before Salmonella had occurred had a fairly small impact on the total costs.The results were the most sensitive to costs associated with a contamination in pigs (at farms or at slaughterhouses) and feed on pig farm. This can be anticipated because in the reduced control scenario, these costs represented approximately three-fourths of the total costs. Changes in the modeling assumptions regarding human cases of Salmonella contamination or associated with human cases had to decrease by at least 90% (ceteris paribus) before the costs of reduced control policy would have been, on average, at the same level, as costs simulated for the current control policy scenario. However, even then, the reduced control policy was simulated to show a larger variation of costs when compared to the current control policy. This was because the costs of contaminations and human cases varied more than the costs of prevention and monitoring measures.Further analyses indicated that the costs associated with measures taken upon Salmonella control policy concerning pig feeds were assessed and compared to a reduced control scenario. The results suggested that the current pig feed Salmonella control policy is financially profitable as it reduced costs caused by Salmonella contaminations in pigs, in their environment, or in pork and human infections. Currently Salmonella is controlled already early in the pork supply chain. While rather small amount of costs could be saved by relaxing the current prevention and monitoring measures, simultaneously much larger additional costs would be incurred through increased human infection costs and costs caused by eradicating Salmonella from pigs, pig farms, and slaughterhouses. Therefore, pig feed Salmonella control provides both public health benefits to society and supports FSCP in it goals. The results extend earlier research results on that that FSCP is economically viable in the poultry sector [e.g., Kangas et al.  under the current Salmonella control policy. Therefore, the pig feed Salmonella control was justified already because of public health issues. Most of the saved costs were associated with lower costs incurred due to contaminations in pigs (whether observed at farm or at slaughterhouse) or in their environment. These costs were saved because of reduced prevalence of Salmonella in pigs or in their environment and measures associated with these contaminations because of FSCP. Hence, effective pig feed Salmonella control can support effectiveness of FSCP, which further supports public health in Finland. Pig feed Salmonella control policy and FSCP should therefore be examined jointly. An important aspect which can be generalized beyond the context of this study is that risk management measures can be complementary when applied in a livestock supply chain and the use of joint inputs is involved, and therefore, possible joint effects of risk management measures affecting the same outcome indicators should be considered.Reducing feed-related Salmonella control policy and FSCP are adjusted from their current status. The scenarios were also developed by using information from a limited number of feed operators, which, together with missing responses, causes uncertainty about the parameter values used. Specific conditions prevailing in Finland may limit the applicability of the results to other contexts. Another potential limitation is related to the appraisal of joint costs. This refers to the costs of measures such as biosecurity, which are applied to mitigate several diseases. Accounting for a higher proportion of these costs to be related to Salmonella prevention would increase the costs of the current control scenario. However, apart from feed heat treatment, the costs were rather modest.Potential limitations of our study are related to the scenarios which were investigated. Besides the two scenarios, we did not look at other intervention scenarios. Hence, there may be other scenarios with slightly reduced or increased control options which could be preferred over the current control policy. This includes novel combinations where both pig feed Salmonella contaminations. These liabilities are mainly faced by the commercial feed manufacturers as they must indemnify damage caused by contaminated feed for buyer if their feed does not meet the requirement of the law, even though the contamination is not caused by intent or negligence. This can be a financially heavy responsibility. The reduced control scenario examined a situation where more responsibility on the contamination costs and human cases was transferred to the pig industry and consumer. Since the beneficiaries of strict liability are mainly farms which purchase pig feed, the meat industry, and consumers who face reduced risk of salmonellosis both directly and indirectly through support that it provides to FSCP's goals, an important policy question is whether the feed suppliers are able to recover their costs through feed prices.Strict liability currently defines responsibilities regarding feed-related Salmonella control policy would be relaxed, many similar actions, and thus their costs, would be taken as they are part of the policy to control animal diseases and to maintain appropriate feed hygiene. Official control and self-control measures should therefore be considered jointly.The incentive aspect can be extended beyond the context of this study. In order to provide sufficient incentives to comply with a given level of liability, it would be important that feed suppliers can recover their costs, for instance, through an insurance policy, a co-finance mechanism involving the supply chain parties, or from the markets. Even if the official pig feed Salmonella and its estimated cost [Niemi et al. , which further enhances public health. Pig feed Salmonella control policy and FSCP should therefore be examined jointly. In order to increase the acceptability of current policy, greater attention to the allocation of financial responsibilities (costs and benefits) regarding the control measures may be required.The current pig feed jarkko.niemi@luke.fi.The datasets for this manuscript are not publicly available because the data contain confidential information which cannot be revealed to parties other than scientists who were involved in the study. Requests to access the datasets should be directed to Salmonella contaminations. JN and KH drafted the manuscript. All authors contributed to the planning of the study and reporting the results.KH carried out a financial analysis on the current control program. KH and MS carried out most of the data collection. PT led the risk assessment work. JN led the economic analysis and conducted stochastic simulations to assess the overall costs and costs caused by 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.


Data from SIV-infected macaques indicate that virus-specific cytotoxic T lymphocytes (CTL) are mostly present in the extrafollicular (EF) compartment of the lymphoid tissue, with reduced homing to the follicular (F) site. This contributes to the majority of the virus being present in the follicle and represents a barrier to virus control. Using mathematical models, we investigate these dynamics. Two models are analyzed. The first assumes that CTL can only become stimulated and expand in the extrafollicular compartment, with migration accounting for the presence of CTL in the follicle. In the second model, follicular CTL can also undergo antigen-induced expansion. Consistent with experimental data, both models predict increased virus compartmentalization in the presence of stronger CTL responses and lower virus loads, and a more pronounced rise of extrafollicular compared to follicular virus during CD8 cell depletion experiments. The models, however, differ in other aspects. The follicular expansion model results in dynamics that promote the clearance of productive infection in the extrafollicular site, with any productively infected cells found being the result of immigration from the follicle. This is not observed in the model without follicular CTL expansion. The models further predict different consequences of introducing engineered, follicular-homing CTL, which has been proposed as a therapeutic means to improve virus control. Without follicular CTL expansion, this is predicted to result in a reduction of virus load in both compartments. The follicular CTL expansion model, however, makes the counter-intuitive prediction that addition of F-homing CTL not only results in a reduction of follicular virus load, but also in an increase in extrafollicular virus replication. These predictions remain to be experimentally tested, which will be relevant for distinguishing between models and for understanding how therapeutic introduction of F-homing CTL might impact the overall dynamics of the infection. A better understanding of immune response dynamics and virus control in HIV infection is an important goal of current research. While measurements are often recorded in the blood, intricate dynamics occur in the lymphoid tissue. Recent data indicate that killer T cell responses, or CTL, show reduced homing to the follicular compartment of the lymphoid tissue, while the majority of the CTL remain in the extrafollicular site, which appears to contribute to the observed unequal distribution of virus load in the two locations. Here, these dynamics are studied with 2-compartment mathematical models. They reproduce previously published as well as newly presented experimental data from CTL depletion studies. Beyond this, the models indicate that so far unknown details of the CTL dynamics, in particular the potential of CTL to undergo antigen-induced expansion in the follicular compartment, can be important determinants of outcome. We find that antigen-induced expansion of CTL in the follicular site can result in more pronounced virus compartmentalization, and essentially in clearance of virus-producing cells from the extrafollicular site. We use the models to predict how experimental addition of engineered, follicular-homing CTL to macaques, influence the overall infection dynamics and level of virus control. Understanding these dynamics is an important step in attempts to improve the level of immune-mediated virus control. Human immunodeficiency virus HIV-1) causes a persistent infection that eventually progresses to AIDS, following an asymptomatic phase that is variable in duration. Immune responses have been shown to play a major role in determining the level of virus load and the rate of disease progression  causes a. CytotoxThe majority of HIV-1 and SIV replication occurs in secondary lymphoid tissues including lymph nodes, spleen, and mucosal associated lymphoid tissues –10. WithHere, we investigate these dynamics with the help of two-compartment mathematical models. In agreement with published and newly presented data, the models show that variation in the strength of the CTL response can influence the degree of virus compartmentalization, with stronger CTL responses (that result in lower virus load) correlating with a more unequal distribution of the virus population among the two compartments. Interestingly, details of the outcome of these dynamics can depend on assumptions about CTL activity in the follicular compartment. If it is assumed that CTL can be stimulated and expand to an extent in the follicular compartment, the model predicts a relatively low number of infected cells in the extrafollicular compartment, maintained mostly by immigration from the follicle rather than by successful replication in the extrafollicular compartment itself. If, in contrast, the model assumes that follicular CTL cannot be stimulated to expand, an unequal virus distribution among the compartments still occurs in the model, but higher virus loads are predicted for the extrafollicular compartment, maintained by successful and sustained viral replication in this site rather than by immigration from the follicle. The models further suggest that future experiments involving the addition of follicular-homing CTL to SIV-infected macaques could distinguish between these two assumptions. Without follicular CTL expansion, addition of F-homing CTL is predicted to result in a significant reduction of follicular virus load, and a lesser reduction of extrafollicualr virus load. In contrast, if CTL expansion is allowed to occur, the reduction of follicular virus load upon addition of F-homing CTL is predicted to be accompanied by a significant rise of extrafollicular virus load. A better understanding of these dynamics also has implications for potentially developing the therapeutic use of chimeric antigen receptor T cells that express the follicular homing molecule CXCR5 to improve the overall degree of virus control.f and Yf, respectively. The corresponding populations in the extrafollicular compartment are denoted by Xe and Ye, respectively. The main CTL dynamics are assumed to occur in the extralfollicular compartment, and this population is denoted by Ze. CTL are also assumed to be able to enter the follicular compartment, and the CTL population there is denoted by Zf. The model is thus given by the following set of ordinary differential equations, which describe the average time evolution of the populations.We consider a two-compartment mathematical model for virus replication . The vire, die with a rate d, and upon contact with virus are infected with a rate βe. Infected cells die with a rate a, and are killed by CTL with a rate pe. The same basic virus dynamics occur in the follicular compartment. Thus, uninfected cells are produced with a rate λf, die with a rate d, and upon contact with virus are infected with a rate βf. Infected cells die with a rate a, and are killed by CTL with a rate pf. We assume that infected cells can migrate between the two compartments with a rate η. The dynamics of CTL expansion only occur in the extrafollicular compartment. Hence, the CTL expand in response to antigenic stimulation with a rate c. In the absence of stimulation, CTL are assumed to die with a rate b. Extrafolliclar CTL can migrate to the follicular compartment with a rate g. In the follicular compartment, no CTL stimulation / expansion is assumed to occur. CTL can die with a rate b, and they can migrate back to the extrafollicular compartment with a rate h. We note that this model assumes no migration of uninfected cells between the two compartments. A low migration rate would not change the model properties in a meaningful way. If uninfected cells moved between the two compartments with a fast rate, this would affect the relative abundance of the uninfected cells in the two compartments. As mentioned below in Section 5, the distribution of target cells among the two compartments has not been measured, and there is no significant change in conclusions if it is varied within reason. We further note that instead of explicitly tracking the free virus population, we assumed it to be in a quasi-steady state, proportional to the number of infected cells [These equations are an extension of the well-established theoretical framework to mathematically describe the dynamics of virus infections –19. The ed cells . While i0f = λfβf/da and R0e = λeβe/da. If R0f>1, the virus establishes an infection in the follicular compartment. If R0e>1, the virus establishes an infection in the extrafollicular compartment. If these conditions are fulfilled, the populations converge to the following equilibrium in the absence of immunity.Whether an infection can be established in the absence of immune responses is given by the basic reproductive ratio of the virus . This isad−fλfβ)(ad−eλeβ)+dη(2ad−fλfβ−eλeβ)>0. In this case, the system converges to an equilibrium, the expressions for which are lengthy and uninformative, and therefore not included here. For low values of η, however, the expressions converge to the ones derived for η = 0 above. When a CTL response is added to the system, it reduces virus load towards an equilibrium that is again too lengthy and uninformative to write down. In the mathematical formulation used here, the CTL response always becomes established if the infection persists in the absence of immunity [Returning to the biologically realistic scenario where infected cell migration occurs between the two compartments (η>0), the virus establishes an infection if the following condition is fulfilled: (immunity  (which iimmunity ).In computer simulations, parameter values need to be chosen. Several parameters are unknown , and they were chosen arbitrarily for the purpose of illustration. The presented simulation results are not dependent on this particular choice of parameter values unless otherwise stated (see section 5 for more in depth discussion of parameter effects). Known parameters are adopted from the literature. Hence, infected cells are assumed to have an average life-span of around 2.2 days , and othIn the mathematical model considered, the CTL responsiveness parameter, c, is one of the most important immune parameters that determines virus load at equilibrium . Thus, aThe rate at which CTL move from the extrafollicular to the follicular compartment (g) can also influence the distribution of virus in the two compartments in the model. It is unclear whether this parameter is biologically fixed or whether it can be influenced by the virus. Varying this parameter in the model, however, allows us to study how it can potentially affect infection outcome. At relatively low CTL F-homing rates, the virus is more abundant in the F compared to the EF compartment . If moreHere, the above analysis is repeated, assuming that CTL can also be stimulated and expand in the follicular compartment . The eque and cf, respectively. Since we currently do not have any information about the relative magnitude of these parameters, we will assume c = ce = cf for purposes of illustration. Results, however, do not depend on this particular choice (see section 5). Although CTL in model (The equations for the virus dynamics remain the same as in model . The CTLin model  can expae = cf). Similar to model e = cf). It is instructive to also plot the extrafollicular number of infected cells at equilibrium under the assumption that infected cells do not migrate between the two compartments , and in the absence of CTL  and kept the rate of back-migration from F to EF (parameter h) constant. The distribution of CTL can, however, also be influenced by the parameter h. In fact, if the parameter g is sufficiently large, an increase in g has an identical effect as an equivalent decrease in h, and it is the ratio of g/h that counts . For lowIn the simulations presented in the figures, parameter values were chosen such that the migration rates of infected cells were generally slower than those of CTL among the two compartments. As far as we are aware, there are currently no data available that would allow us to estimate the respective migration rates. The results presented in the figures, however, largely do not depend on those parameter choices see . If the e and λf. Results further remain robust if we assume asymmetrical migration rates of the target cells between the two compartments, and if CTL expansion occurs at different rates in the two compartments Click here for additional data file.