A consistent determinant of the establishment success of alien species appears to be the number of individuals that are introduced to found a population (propagule pressure), yet variation in the form of this relationship has been largely unexplored. Here, we present the first quantitative systematic review of this form, using Bayesian meta-analytical methods. The relationship between propagule pressure and establishment success has been evaluated for a broad range of taxa and life histories, including invertebrates, herbaceous plants and long-lived trees, and terrestrial and aquatic vertebrates. We found a positive mean effect of propagule pressure on establishment success to be a feature of every hypothesis we tested. However, establishment success most critically depended on propagule pressures in the range of 10–100 individuals. Heterogeneity in effect size was associated primarily with different analytical approaches, with some evidence of larger effect sizes in animal rather than plant introductions. Conversely, no variation was accounted for in any analysis by the scale of study  or methodology  used. Our analyses reveal remarkable consistency in the form of the relationship between propagule pressure and alien population establishment success. Alien species are a major contributor to human-induced global environmental change. The probability of whether or not an alien species will successfully establish in a novel environment is often related to the number of times a species is introduced and the number of individuals that are introduced each time, collectively termed ‘propagule pressure’. Despite this evidence, we don’t yet know whether this is a universal characteristic of species invasions, and the role of propagule pressure continues to be questioned. Here, we present a quantitative meta-analysis of the relationship between propagule pressure and establishment success across a broad range of species and geographies. We found that propagule pressure was consistently and positively associated with the establishment success of alien species. We conclude that propagule pressure is indeed the most consistent and strongest determinant of alien species establishment. No other factors suggested to explain establishment success can claim such universal support. Our results underpin a clear policy and management target for slowing invasion rates by reducing propagule pressure—ideally to single figures or zero—regardless of any other feature of the invasion. Alien species constitute a major threat to global biodiversity –4, and sDespite all the attention paid to the effect of propagule pressure on alien population establishment success, there are still substantial and surprising gaps in our knowledge of this relationship. Most notably, there has been no quantitative assessment of evidence for the strength, shape, or variation in the statistical effect of propagule pressure. Given that propagule pressure underpins our basic understanding of the ecological and evolutionary dynamics of small founding populations , as wellIncreases in propagule pressure can be achieved through the release of large numbers of individuals (i) in any single introduction event (propagule size), (ii) through many independent introduction events (propagule number), or (iii) through a combination of the two (propagule pressure) . PositivReported relationships between propagule pressure and establishment success range from strongly positive  through This variety of study designs, taxonomic diversity, and spatial scales has required variation in the statistical methodologies adopted. These methods range from simple univariate models to complicated multivariate structures that seek to disentangle the often complex intercorrelations between propagule pressure, species traits, and environmental conditions –38. AlthPropagule pressure can be difficult to measure in the natural experiments that represent real-world introductions of alien species and impossible to estimate retrospectively. To deal with this challenge, proxies for components of propagule pressure are analysed instead of direct estimates of propagule pressure itself. Proxies are variables that are not measures of the number of individuals released to found different populations but that are thought to correlate with that number . For thiThe observed variability in the strength of the relationship between propagule pressure and establishment success has led some authors to suggest that the proposed ‘null model for biological invasions’  is actuan = 11) that provided raw data on the binary outcome of establishment success , we directly evaluated the specific variation in the shape  of the effect of propagule pressure on establishment probability.Here, we have performed the first systematic and quantitative review of the relationship between propagule pressure and establishment success for alien species introductions. We used quantitative meta-analytical methods to estimate the overall effect of propagule pressure on establishment success and to test for heterogeneity in this relationship. We then assessed the extent to which heterogeneity can be explained by the set of a priori hypotheses concerning factors that vary across studies. Specifically, we tested whether the relationship between propagule pressure and establishment success differs among (i) taxonomic groups, (ii) studies performed at different spatial scales, and (iii) relationships analysed using proxies for propagule pressure compared with those studies using direct measures . We alsZr) across all 56 studies was positive (0.47), with 95% Credible Intervals (CI) that did not overlap zero (95% CI = 0.34–0.59). However, these studies showed substantial heterogeneity among effect sizes , we found no evidence for any variables explaining heterogeneity among effect sizes (Table B in n = 56), there was evidence (ΔLOO-IC > 2.0 from the Intercept-only model) that effect size varied according to how propagule size was treated for analysis  and the range over which ‘Propagule size’ was measured  increases in propagule pressure (95% CI = 7.0–18.5). Establishment success responded most strongly to propagule pressures between 10 and 100 individuals  compared with an Intercept-only model. Variation was not accounted for, in any analysis, by the spatial scale of study , and there was no evidence for an effect of the source of evidence . The effect of propagule pressure on establishment success manifests equally, as positive, within local experimental tests  and globHeterogeneity in effect sizes was most apparent when taking account of the variety of ways analyses were performed across studies. The moderator variable that most consistently explained variation in effect size was whether analysis was univariate or multivariate , then the positive relationship between propagule pressure and establishment success is strongest when large step changes across ranges of propagule pressures are discretised, compared with continuous (either linear or log-transformed) measures . Bins caEffect sizes also weakened as the range of release sizes  increases . Effect Finally, we explicitly accounted for the nonindependent analysis of overlapping datasets by grouping studies and effect sizes which relied on the same (or similar) data. Although we found some evidence that vertebrate and invertebrate studies have larger effect sizes than plant studies  of this relationship will vary according to a variety of biological and methodological factors. There is heterogeneity in effect sizes, but this is primarily associated with different analytical approaches. Our analyses dispel suggestions that the effect of propagule pressure on establishment success is an artefact of the analyses of only certain data , conducted in only certain ways , on certain metrics of propagule pressure , or when the analysis focuses only on certain species  or certain locations . There was no evidence for publication bias, and the propagule pressure effect is remarkably consistent in both size and shape. There are very few, if any, other factors purported to explain establishment success that can claim such universal support . In a fiWe searched Web of Science, Biosis, and EbscoHost using the following search terms: propagule AND pressure AND ecolog*, ‘introduction effort’ AND (ecolog* OR invas*), propagule AND pressure AND invas*, propagule AND (size OR number) AND (ecolog* OR invas*), pressure AND invas* AND ecolog*, ‘establishment success’ AND propagule. We varied this search string and included all generally used synonyms of ‘alien’ including ‘exotic’, ‘non-native’, ‘non-indigenous’, and ‘naturalized’ . In addin = 8 studies). We grouped these studies, which were based on a common underlying dataset, so that the 96 relationships were analysed across 43 study/dataset groups , invertebrate (n = 25), or vertebrate (n = 61).Taxon: We classified taxon as either plant (n = 5), state (n = 13), country (n = 31), continental (n = 20), and global (n = 27). State indicates any spatial unit nested within a country , and local refers to field and mesocosm studies.Spatial scale: We classified analyses on the basis of the spatial extent over which data were observed; local (n = 70) or a ‘proxy’ variable (n = 26). For ‘direct’ measures of propagule pressure, we scored the type of scientific methodology as either experimental (n = 11) or observational (n = 59). Observational studies mainly related to data on the success or failure of historical introductions. Examples of proxies included the number of 19th century plant catalogues selling a species [Methodology: We distinguished whether the analysis used a ‘direct’ measure of propagule pressure   or multivariate models (n = 34).Number of predictors: We scored effect sizes according to whether they were taken from a model that included other explanatory variables, i.e., univariate (n = 35), log transformed , or binned into a small number of ordinal categories of varying size (n = 21).Transform: We classified analyses according to how they treated the form of the propagule pressure data in its measured relationship with establishment success, i.e., linear  (n = 40n = 70): We distinguished whether the analysis used an estimate of propagule size  or propagule number . Note, this applies only to the ‘direct’ subset of the Proxy variable.Propagule pressure (n = 56): For studies of propagule size, we recorded the range  across which establishment success was measured, i.e., tens (n = 12), hundreds (n = 19), or thousands (n = 25).Propagule size (Zr [r) following the algebraic recalculations and detailed conversions provided in Box 13.3 by Lajeunesse and colleagues [The majority of studies (41 out of 56) conducted a logistic- or probit-type regression analysis between establishment success and propagule pressure, in which individual success was depicted as a binary outcome ; additional test statistics are detailed in the Supporting Information . We calcZr . We convlleagues .2 statistics [We conducted a Bayesian multilevel meta-analysis to estimate the overall statistical population-level effect size. This approach allowed us to estimate the heterogeneity in effect size for the random effects: among studies and among relationships within a study . Heterogatistics , 65. We n = 70). The second evaluated the extent to which effect size was influenced by the range across which propagule size was measured .There were two additional moderator variables that we had reason to believe would account for heterogeneity in population-level effect size—moderator variables ‘Propagule pressure’ and ‘Propagule size’. In order to evaluate the influence of these variables, we subset the reported relationships into groups, with each subset containing only relationships that had information on the focal moderator variable of interest . The first subgroup considered whether the component of propagule pressure  explained heterogeneity in effect sizes  at all cross-classification levels of the pairs of moderator variables. We imposed these constraints to avoid overfitting due to limited overall number of effect size measures available. We used a LOO-IC to estimate the predictive accuracy of the Bayesian hierarchical meta-regression models [LOO-IC > 2.0).For all models, regardless of subset or analytical underpinning, we included either single moderator variables or the additive effects of pairs of moderators, provided that there was sufficient replication  software environment for statistical and graphical computing . We usedSelective reporting of results can lead to ‘publication bias’ . We inveEgger’s regression provides an inferential test to examine evidence against the hypothesis of no publication bias, but this test requires independent observed effect sizes. Nakagawa and Santos  present Some studies have used an experimental approach to evaluate how incrementally increasing propagule size served to alter establishment probability. Each experiment consisted of a series of populations held in either constant or systematically altered environments. The treatment applied is the varying of founding numbers of individuals across replicate populations, with the range of founder sizes determined by the researchers. Establishment probability in this context is the number of experimental populations that remained extant (successful) after a predefined time frame (>1 generation) out of the total number of experimental populations initially constructed. Eleven of these studies provided sufficient raw data for us to extract and combine 14 relationships into a single analysis that evaluates the specific variation in the shape of the propagule pressure effect.10 transformed and centred for this analysis. We found no evidence for overdispersion in the binomial proportions after accounting for the random effects.We used a Bayesian generalised linear mixed model with a logit link and binomial variance function to evaluate the slope of the effect of propagule pressure on establishment probability, accounting for average differences in establishment success between experiments (a random effect). We also examined evidence for random differences in the slope of the relationship across experiments. Propagule pressure was logS1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.S1 Data(CSV)Click here for additional data file.


Vaccines constitute a unique selective pressure, different from natural selection, drives the evolution of influenza virus. In this study, A/Chicken/Shanghai/F/1998 (H9N2) was continually passaged in specific pathogen-free embryonated chicken eggs with or without selective pressures from antibodies induced by homologous maternal antibodies. Genetic mutations, antigenic drift, replication, and pathogenicity of the passaged virus were evaluated.Antigenic drift of the passaged viruses occurred in the 47th generation (vF47) under selective pressure on antibodies and in the 52nd generation (nF52) without selective pressure from antibodies. Seven mutations were observed in the vF47 virus, with three in PB2 and four in HA, whereas 12 mutations occurred in the nF52 virus, with three in PB2, two in PB1, four in HA, one in NP, one in NA, and one in NS. Remarkably, the sequences of the HA segment from vF47 were 100% homologous with those of the nF52 virus. Both the vF47 and nF52 viruses showed enhanced replication compared to the parental virus F/98, but higher levels of replication and pathogenicity were displayed by nF52 than by vF47. An inactive vaccine derived from the parental virus F/98 did not confer protection against challenges by either the vF47 or nF52 virus, but inactive vaccines derived from the vF47 or nF52 virus were able to provide protection against a challenge using F/98.Taken together, the passage of H9N2 viruses with or without selective pressure of the antibodies induced by homologous maternal antibodies showed genetic variation, enhanced replication, and variant antigenicity. Selective pressure of the antibody does not seem to play a key role in antigenic drift in the egg model but may impact the genetic variation and replication ability of H9N2 viruses. These results improve understanding of the evolution of the H9N2 influenza virus and may aid in selecting appropriate vaccine seeds. The H9N2 influenza virus has spread rapidly in chickens throughout Asia since the 1990s . To contThere are two scenarios under which the transmission of H9N2 avian influenza virus occurs. The first is a sporadic outbreak of H9N2 avian influenza virus in chicken farms occurring despite chicken vaccination, and can even occur in animals with a high antibody titer against H9N2 influenza , 8. ThisThe immune selective pressure of host drives influenza virus evolution . During Sun et al. reported that, in China, the prevalent H9N2 avian influenza virus prior to 2000 was the BJ/94-lineage, and after 2004 the F/98-lineage became dominant. Currently, the F/98-lineage is still the prevalent genotype in China , 23. In Ten-day-old of incubation SPF embryonated chicken eggs, SPF hens and cocks were purchased from the Shandong Poultry and Breeding Farms, China, and housed under SPF conditions. All animal experiments were approved by the Jiangsu Administrative Committee for Laboratory Animals (permission number SYXK-SU-2007-0005) and complied with the Jiangsu Laboratory Animal Welfare and Ethics guidelines of the Jiangsu Administrative Committee of Laboratory Animals .A/Chicken/Shanghai/F/98  influenza virus was isolated in Shanghai in 1998, purified and stocked by the Animal Infectious Disease Laboratory, School of Veterinary Medicine, and Yangzhou University . The H9N2, 37 °C.Madin-Darby canine kidney (MDCK) cells were grown in DMEM media (Invitrogen) containing 10% fetal bovine serum (FBS) (Invitrogen), and cultured in an incubator with 5% COv/v) for 24 h at 37 °C. Inactivation was confirmed by the absence of detectable infectivity after two blind passages of formalin-treated allantoic fluid in embryonated eggs. The inactive allantoic fluid was emulsified in two parts of paraffin oil (v/v), which is currently used commercially as an adjuvant for veterinary vaccine production [The F/98 strain was inactive by adding 0.2% formalin .Hemagglutination (HA) and hemagglutination inhibition (HI) assays, the antisera preparation of F/98 virus, routine HA and HI tests were used as outlined in the OIE Three, four-week-old SPF chickens were immunized by intramuscular injection of 0.3 ml oil-emulsion of inactive whole virus vaccine of the indicated viruses. Sera were taken in chickens at 3 weeks after immunization and treated with receptor-destroying enzyme  to remove non-specific haemagglutination inhibitors, as above described an HI test was performed. Samples were regarded positive for inhibition of haemagglutination at a dilution ≥1:16.Manual of Diagnostic Tests and Vaccines for Terrestrial Animals. Briefly, the yolk samples were treated with a receptor-destroying enzyme (RDE)  at 37 °C for 20 h to eliminate non-specific inhibitors of hemagglutination. HI titers obtained from a purified yolk and RDE mixture (25 ml egg yolk + 75 ml RDE provided a starting dilution of 1:1) were defined as the reciprocal of the highest dilution of yolk, which completely inhibited hemagglutination of 4 hemagglutination units of the virus with a 1% solution of chicken red blood cells. Samples with HI titers under 16 were considered negative.Three ten-day-old of incubation SPF embryonated chicken eggs either directly from SPF hen, or from the vaccinated SPF hens inseminated with SPF cocks. For yolk immunoglobulin extraction using a simplified chloroform polyethylene-glycol procedure, 2 ml of egg yolk was mixed with an equal volume of phosphate-buffered saline, and then added to 4 ml of chloroform. After mixing well, the yolk was centrifuged at 3500 rpm for 10 min. The supernatant was collected and used for antibody tests. The HI test was performed according to the standard procedures recommended by the OIE 6 the 50% egg infectious dose (EID50) of the F/98 virus. The allantoic fluid of each generation pooled from 3 eggs with or without SPA was collected after 72 h incubation. Part of allantoic fluid was saved at the − 70 °C, part of allantoic fluid were combined and used for the next passage in another three eggs with or the SPF embryonated chicken eggs, respectively, until 80 passages  assay. When HI titers of the passaged virus were up to 8-fold difference from that of the parental virus F/98, antigenicity of this passaged virus was believed to be drift . These pViral RNA was extracted from allantoic fluid of the indicated passaged viruses using the High Pure RNA isolation kit (Roche). RNA was subjected to reverse transcription-PCR (RT-PCR) using 18 primer sets that cover the entire viral genome. These primer sets were designed according to the genome sequences of the F/98 virus and by using Primer Premier 5.0 software. The fragments, approximately 600 to 800 nucleotides in length, were sequenced using the Illumina HiSeq2000 sequencing platform in the Chinese National Human Genome Center, Shanghai. Briefly, a library was constructed with TruSeq DNA sample prep kit set A. The DNA library was diluted and hybridized to the paired-end sequencing flow cells. DNA clusters were generated on a cBot cluster generation system with the TruSeq PE cluster generation kit v2, followed by sequencing on a HiSeq 2000 system with the TruSeq SBS kit v2. The threshold for the detection of single-nucleotide polymorphisms (SNP) was set manually at 10% of the population.Genome RNAs of viral clones were extracted from culture supernatants using the QIAamp viral RNA kit (Qiagen). Genes were reverse transcribed and amplified using a OneStep RT-PCR kit (Qiagen). Primers were the same as those used in the deep sequencing assay. The amplified cDNA products were excised from agarose gels and purified using a QIAquick gel extraction kit (Qiagen). Full-genome DNAs were Sanger sequenced by TAKARA BIOTECHNOLOGY (DALIAN) CO., LTD., and the sequence data were analyzed using GenScan software.The positions of amino acid substitutions on the HA molecule were analyzed on the 3-dimensional structure obtained from the Protein Databank  with the RasMol 2.7.3 program.6 EID50 of the parental virus F/98, the passaged viruses or phosphate buffer solution (PBS) control. Tissue samples (trachea and lung) from the inoculated chickens were collected at 3 days and 5 days post-inoculation (dpi) . Briefly, three SPF chickens were euthanatized using CO2 asphyxiation at designated times and half of the tissues were harvested, washed and ground into 20% (w/v) suspension in 1 ml PBS. Virus titers in the trachea and lung were determined in 10-day-old SPF embryonated chicken eggs accordingly (43). Another half part of the tissues were fixed with 10% neutral buffered formalin, embedded in paraffin, sectioned at 5 mm and routinely processed for staining with hematoxylin and eosin for histopathological examination (47). These experiments were repeated three times.For studying the viral replication and pathogenicity in chicken, groups of six 4-week-old SPF chickens were oral, intranasally, or intratracheally inoculated with 0.2 ml of 106 EID50 of indicated virus. The airborne contact group was placed in a cage directly adjacent to the infected group with a distance of 50 cm between cages. At day 3, 5, 7 and 9 post-inoculation, tracheal and cloacal swabs from chickens were collected in 1 ml of PBS containing antibiotics, following freeze/thaws once, and were centrifuged at 3000 rpm for 10 min. Of the resulting supernatant, 0.2 ml were taken and the EID50 titers of tracheal and cloacal swabs collected from the indicated passaged virus were determined by serial titration of viruses in SPF embryonated chicken eggs using the Reed and Muench method [For studying the viral transmission, twelve 4-week-old SPF chickens for each virus were divided into: (i) inoculated group (three chickens), (ii) direct contact group (three chickens), (iii) airborne contact group (three chickens), (iv) PBS control group (three chickens) . The infected group was inoculated oral, intranasally and intratracheally with 10h method . Sera coh method . The expTo study the cross - immunogenicity of the passaged virus, 135 4 - week - old SPF chickens were divided into 5 groups, A, B, C, D and E  was used to evaluate the replication ability of strains and the tissue lesion in chickens challenged with different viruses. A To explore the role of SPA on the evolution of H9N2 avian influenza virus, the F/98 virus was serially passaged in SPF embryonated eggs in the presence or absence of SPA, and the allantoic fluid of each generation was collected and stocked Fig. . HI titeThe passaged viruses vF47, nF47 and nF52 in the allantoic fluid were further deeply sequenced. We did not determine any viral quasispecies. Simultaneously, the passaged viruses vF47, vF60, vF70, vF80, nF47, nF52, nF60, nF70, and nF80 in the allantoic fluid were twice purified by plaque purification in MDCK cells (10 plaques of each indicated virus were picked up and sequenced to determine the purity of the passage viruses). Those viruses were then passaged once in the allantoic cavities of 10-day-old chicken eggs. A sequence analysis of these viruses confirmed that serial passage in allantoic cavities of the egg model did not lead to the formation of viral quasispecies.50) of nF47, vF47, and nF52 was significantly higher than that of their parental virus F/98 by 9.3-fold, 12.5-fold, and 117.5-fold, respectively (Table p < 0.01). Notably, vF47 and nF47 shared similar EID50 titers. However, after five more passages, the EID50 of the nF52 virus was significantly increased compared to nF47 and vF47 (Table p < 0.01).The F/98, nF47, vF47, and nF52 viruses passaged in the allantoic fluid of eggs were selected for further research. We found that the embryo means death time (EMDT) of nF47, vF47, and nF52 in SPF embryonated chicken eggs was reduced by 7 h, 11 h, and 17.5 h, respectively, compared to the 86 h EMDT of the parental F/98 virus. The 50% egg infectious dose  and one in the HA gene (K131R). Conversely, vF47 has seven amino acid mutations, three in the PB2 gene  and four in the HA gene . Additionally, nF52 has 12 amino acid mutations, three in the PB2 gene , two in the PB1 gene , four in the HA gene , one in the NP gene (R99K), one in the NA gene (A459T), and one in the NS1 gene (A143T) (Table http://www.fludb.org) between 1994 and 2015 (from 1 January 1994 to 20 December 2015) were analyzed. Most H9N2 wild-type isolates shared common mutations with vF47 or nF52. Over the past 20 years, the mutations C228Y and K375R of the PB2 gene that we observed in the passaged viruses displayed high mutation frequencies of 92–100% in wild-type viruses. Additionally, the mutation frequencies of K131R, S145 N, G181E, and A198V in the HA gene that we observed in the vF47 and nF52 viruses were 96.3–99.4%, 3.7–18.1%, 0–72%, and 30.2–42.4% in wild-type viruses, respectively. In comparison, the A143T mutation in the NS1 gene that we observed in the nF52 virus had a mutation frequency of 18.8–43.2% in wild-type viruses. Notably, the mutations S145 N and G181E in HA were significantly increased in wild-type isolates, with 18.1% and 54% over recent years.To determine whether the amino acid changes observed in vF47 or nF52 occur in H9N2 wild-type isolates, sequences from the National Institute of Allergy and Infectious Diseases database , S145 N (green), G181E (apricot yellow), and A198V (blue) in the HA gene. The locations of the amino acid substitution in the HA of H9 are illustrated on the three-dimensional map of F/98 HA  at 3 and 5 days post-infection (dpi). The titers of vF47 in the trachea were significantly lower than those of nF47 at 3 and 5 dpi , and they were also lower than that of nF52 at 5 dpi . Additionally, the titers of nF47 and nF52 at 5 dpi were not only higher than their corresponding titers at 3 dpi , but they were also higher than those of their parental virus F/98 and of vF47 . The titer of vF47 decreased in the lung  to a level similar to that of the parental virus F/98.We further examined the replication and pathogenicity of the viruses passaged with or without SPA by comparing the virus titers and pathology parameters in chickens. The results show that the viral load of the passaged viruses in the trachea were 100–10,000-fold higher than that of their parental virus F/98 , whereas the passaged viruses nF47 and nF52 showed enhanced pathogenicity levels in both the trachea and lung .The histopathological lesions of the trachea and lung in chickens infected with one of the passaged viruses, or with the wildtype virus F/98, had similar levels of severity at 3 dpi Fig.  - k. At We set up transmission experiments with the passaged viruses nF47, vF47, nF52 and their parental virus F/98 to further explore the effect of SPA on the transmission route of the H9N2 influenza virus . The resThe immunization and challenge procedure used here is described in Table Previous work studying the evolution of influenza focused on performing sequence analyses of field isolates , 25, 32.Group one, containing mutants S145 N, G181E, and A198V in HA, was found in both the vF47 and nF52 virus. The antigenicity of the vF47 and nF52 viruses were changed with 32-fold HI titers lower than the parental virus F/98. Those changes resulted in low levels of protection against the passaged viruses vF47 and nF52 in chickens that were immunized with the vaccine based on the parental virus F/98  was significantly higher than that of the parental virus F/98 (Table Group two included K131R in HA, C228Y and K375R in PB2, which appeared in three viruses: nF47, nF52, and vF47. The EID98 Table . This im50 (Table Interestingly, group three, consisting of A459T in NA, T156A and R189K in PB1, R99K in NP, and A143T in NS1, only appeared in the nF52 virus. Compared to the vF47 virus, the nF52 has a 9.3-fold higher incidence of EID50 Table , and speIn summary, our findings suggest that the antigenic drift of H9N2 influenza virus occurs during serial passaging with SPA or SPF embryonated chicken eggs. The virus produced by passaging in the presence of SPA has fewer amino acid substitutions and displays earlier antigenic drift than the virus produced by passaging in SPF embryonated chicken eggs. In contrast, the virus passaged in SPF embryonated chicken eggs developed more genetic changes. These mutations lead to the virus having enhanced replication and pathogenicity in SPF chickens and changed the feature of airborne spread compared to the SPA-passaged virus. The vaccine prepared from the parental virus did not provide protection against the passaged viruses, but the vaccines produced from the passaged viruses conferred complete protection against the parental virus. Our findings broaden the understanding of antigenic drift and the selection of vaccine seeds for H9N2 influenza viruses.


Plant-made biopharmaceuticals have long been considered a promising technology for providing inexpensive and efficacious medicines for developing countries, as well as for combating pandemic infectious diseases and for use in personalized medicine. Plant virus expression vectors produce high levels of pharmaceutical proteins within a very short time period. Recently, plant viruses have been employed as nanoparticles for novel forms of cancer treatment. This review provides a glimpse into the development of plant virus expression systems both for pharmaceutical production as well as for immunotherapy. Plant-derived biopharmaceuticals, including vaccines, monoclonal antibodies, and other therapeutic proteins, are rapidly emerging into the marketplace. Today, commercialized plant-made pharmaceutical products are offered by Protalix Bio Therapeutics, Inc. , Planet Biotechnology, Inc. , and Icon Genetics, GmbH . Biologics derived from plants have been demonstrated to be effective, safe, and inexpensive. They are easy to generate en masse and can be stored at ambient temperatures . These aThe first plant-derived pharmaceuticals were generated from transgenic plants, with length of generation time and protein expression levels being two of the principal caveats of this technological approach. In response, transient expression through the use of plant virus expression vectors became an attractive venue by which biopharmaceuticals could also be generated . Virus vWith this history, the development of plant virus expression vectors for biopharmaceutical development has become a powerful tool. This review aims to describe some of the virus expression systems currently in use and explore some of their most recent applications, both as production systems and as nanoparticles for cancer immunotherapy.Plant viruses have been engineered to express vaccines, monoclonal antibodies, and other therapeutic proteins. Plant virus expression vectors have been designed from the genomes of both positive-sense RNA viruses or single-stranded DNA viruses ,7,8. FirSecond generation virus expression vectors, on the other hand, have no size limitation of foreign genes, have improved production levels, and overcome both host plant species and tissue restrictions. These new ‘deconstructed vectors’ are composed solely of the foreign gene of interest and the minimum virus components that are required for replication ,10,11. AA third plant virus strategy using viruses as nanoparticles has arisen as a means by which, among other things, cancer can be addressed. Immunotherapy using plant virus nanoparticles has been demonstrated to elicit a localized immune response against cancer cells that is also stable, nontoxic, and biodegradable . The extAgrobacterium tumefaciens binary vector has also been developed by Musiychuk et al. in 2007 to generate vaccines against cholera, the influenza virus, and the plague [Rigid rod-shaped tobamoviruses include the Tobacco mosaic virus (TMV). TMV has 2130 copies of the capsid protein (CP), and was the first virus that has been engineered as a deconstructed vector system ,11. Thise plague ,23,24,25Nicotiana benthamiana leaves [Foreign protein expression in TMV infected plants can also be enhanced significantly through the coexpression of the RNA silencing suppressor gene P19 of the Tomato bushy stunt virus . Other Ta leaves . The auta leaves .Liu and Kearney have developed a tobamovirus that infects legumes, based on Sun Hemp Mosaic Virus (SHMV) that incorporates some of the attributes of the strategies developed by Icon and TRBO vectors . Their “Francisella tularensis that did not elicit adverse reactions when administered to mice, yet protected them against respiratory challenges with very high doses of F. tularensis Live Vaccine Strain LVS [Plasmodium falciparum development. TBV proteins, such as the Pfs25 protein, could be a potential target to reduce the transmission of malaria [The recent discovery of adjuvant properties of TMV has sparked a renewed interest in the use of this virus as a delivery vehicle for immunotherapy. TMV particles have been demonstrated to be taken up by dendritic cells and to exhibit activation properties, resulting in robust CD8+ T cell responses ,37. Banirain LVS . Similar malaria . The TMV malaria ,41.The MagnICON deconstructed vector is perhaps most well-known for its use in efforts to develop personalized medicine against non-Hodgkin’s lymphoma (NHL) . NHL is The tobacco mosaic virus has been engineered to be tumor-specific using the tumor homing peptide cRGD, which has been functionalized to the surface of the virus. TMV particles that display cRGD can become rapidly internalized into tumor cells. Doxorubicin and other anti-cancer drugs can also be conjugated to TMV so that they can be taken up by cancer cells and released during endocytosis .Potato Virus X (PVX), a flexuous, rod-shaped virus containing a plus-sense RNA molecule, has also been engineered extensively as an expression vector for biopharmaceuticals. The genome of PVX consists of replicase and capsid protein genes, as well as a triple gene block, whose products are responsible for virus movement. PVX has been used to express full-length proteins, fusion proteins, epitopes that are displayed on the outer surface of the assembled virus particle, and more recently, PVX nanoparticles have been demonstrated to block tumor progression in animal models . For exaN. benthamiana plants infected with a PVX vector expressing this fusion protein were able to produce 1 mg/g fresh leaf tissue or 30% total soluble protein, and inoculated mice were protected from influenza infection.PVX has been employed for the development of a universal influenza vaccine consisting of an epitope derived from the extracellular domain of H1N1 virus matrix protein 2 (M2e). The researchers fused M2e to bacterial flagellin, a strong mucosal adjuvant, in order to improve M2e immunogenicity . N. bentPVX has produced other antigens as well. For example, Uhde-Holzem et al. (2010) used PVX to express the epitope HVR1 from the Hepatitis C virus (HCV) as a fusion protein . Mice imRecently, PVX has been designed to act as a nanoparticle for tumor immunotherapy. PVX nanofilaments carrying monoclonal antibodies of herceptin (Trastuzumab) for breast cancer patients  could inPapMV also has immunostimulatory properties, and can act as a nanoparticle. PapMV nanoparticles can elicit an α-IFN-dependent response, and when administered intra-tumorally can slow down melanoma progression and prolong survival in animal models ,60,61,62The Comovirus Cowpea mosaic virus (CPMV) has undergone extensive development as an expression vector. CPMV is an icosahedral virus of 30 nm in diameter, comprised of 60 large (L) and 60 small (S) capsid proteins. The genome of CPMV is bipartite, with RNA-2 being the principal component of expression vector development. CPMV has been utilized extensively in antigenic presentation and full-length protein expression as part of a fusion protein that can undergo proteolytic cleavage to release the therapeutic protein, as well as in material science research, such as the formation of magnetic clusters and biosensors ,64,65,66The CPMV deconstructed vector system pEAQ involves the expression of foreign proteins without the need for viral replication ,69, thusA new vector, known as pCPMV-HT (Cowpea Mosaic Virus Hyper-Trans expression system) has been engineered that also provides high translational efficiency ,71. ThesCPMV particles have also been found to bind to vimentin displayed on the surface of HeLa cells, and are able to be taken up by endocytosis ,75,76. TThe Cowpea mosaic virus expression vector pEAG-HT has also been used to express the extracellular domain of the rat ErbB2 in tobacco plants . ErbB2 iOne possible direction of vector development may include the merging of genetic elements from two vastly different virus expression systems. This next section describes two such systems.In the first example, Mardanova et al. utilized an expression vector construct based on PVX, along with a translational enhancer from RNA 4 of the alfalfa mosaic virus (AMV), and combined it with the CPMV-based pEAQ-HT vector backbone driving a suppressor of gene silencing to create a new vector expression system (pEff) . pEff isIn the second example, TMV has been used to express the genome of the Alphavirus Flock house virus (FHV), a small insect virus that can replicate to high levels in plants without inducing apoptosis. By including origins of assembly (ori) from TMV into the Flock house virus genome, a pseudovirus consisting of the FHV genome encapsidated by TMV coat protein was generated. Since TMV behaves like an adjuvant and can stimulate an immune response, this pseudovirus approach can be used to produce novel vaccines from plants .Geminiviruses, with their twinned capsid morphology, are single-stranded circular DNA viruses, and are capable of undergoing replication in a broad range of host plants at a high copy number. As a result, geminiviruses are suitable to develop as expression vectors . The gemA geminivirus vector based on the Beet Curly top virus (BCTV) has been used to generate a vaccine against hepatitis A . As anotFundamental difficulties remain for populations of remote, impoverished regions to access vaccines and other biopharmaceutical protein, including high cost and limited accessibility. This prevents many from achieving better health, and as a result better livelihoods for themselves and their families. Plant-made vaccines could slow the spread of infectious diseases that are major killers, such as HIV, HBV, and malaria. Plants possess other advantages as expression systems; they do not harbor mammalian pathogens and in certain instances can undergo similar post-translational modifications to their mammalian counterparts. Pharmaceuticals derived from plants can easily be purified, or in specific cases merely partially purified prior to oral administration.Plant-made biopharmaceuticals to fight cancer are increasing in number. Plant-made vaccines which combat oncogenic viruses that are of concern to resource poor countries, such as Hepatitis B, Hepatitis C, and Human papillomavirus, are under development and could make a huge impact on the quality of life for hundreds of millions of people. The generation of monoclonal antibodies to combat cancer in a variety of plants could also assist developing countries. The recent discovery of plant virus nanoparticles to target and penetrate solid tumors is particularly interesting ,89,90,91Plant virus particles can also be a platform technology for developing nations to utilize for growing their own pharmaceutical industries. By equipping poor countries with virus constructs and freedom to operate, a plant-made pharmaceutical industry could become a reality. Improvements in manufacturing infrastructure, financial support, and the maturation of a regulatory framework surrounding plant-derived pharmaceuticals are all essential for their commercialization in the developing world. If these obstacles are overcome, it would seem that many of the examples presented in this review could play a significant role in improving the lives of many.


Genome‐wide patterns of genetic divergence reveal mechanisms of adaptation under gene flow. Empirical data show that divergence is mostly concentrated in narrow genomic regions. This pattern may arise because differentiated loci protect nearby mutations from gene flow, but recent theory suggests this mechanism is insufficient to explain the emergence of concentrated differentiation during biologically realistic timescales. Critically, earlier theory neglects an inevitable consequence of genetic drift: stochastic loss of local genomic divergence. Here, we demonstrate that the rate of stochastic loss of weak local differentiation increases with recombination distance to a strongly diverged locus and, above a critical recombination distance, local loss is faster than local “gain” of new differentiation. Under high migration and weak selection, this critical recombination distance is much smaller than the total recombination distance of the genomic region under selection. Consequently, divergence between populations increases by net gain of new differentiation within the critical recombination distance, resulting in tightly linked clusters of divergence. The mechanism responsible is the balance between stochastic loss and gain of weak local differentiation, a mechanism acting universally throughout the genome. Our results will help to explain empirical observations and lead to novel predictions regarding changes in genomic architectures during adaptive divergence. In spite of substantial gene flow, populations under differential selection in a heterogeneous environment may diverge as partial barriers to gene exchange establish along the genome at loci involved in local adaptation (Barton and Bengtsson the establishment bias). For an illustration of this effect, see Figure genome hitchhiking by Feder et al.  there is an optimal value θ(k) for the phenotype. For simplicity, the two optima are assumed to be constant during time and symmetric around zero, so that θ(1)=−θ(2).We simulate a multilocus model of divergence between two diploid populations. The model is similar to that used in Yeaman and Whitlock . In the model each allele is attributed an allele‐effect size by which it contributes additively to the phenotype of an individual. In other words, the phenotype zi of individual i equals the sum of allele‐effect sizes at the L loci. We assume that the fitness wi(k) of individual i in population k  depends on the phenotype zi of this individual as:N surviving to maturity in a given deme is constant over time, and we assume that it is equal in the two populations. Generations are assumed to be discrete and nonoverlapping. The lifecycle of individuals is modelled as follows. Virgin adults migrate to the opposite deme at a per generation per individual rate m. Migration is followed by random mating locally within each population, recombination, and selection. Recombination is assumed to occur at a rate r between adjacent loci, per gamete, per generation. Finally, mutations accumulate at a rate μ per allele, individual, generation. Each mutation is given a mutation‐effect size by which it additively contributes to the effect size of the allele it lands on. Mutation‐effect sizes are drawn randomly from a Gaussian distribution with a standard deviation σμ, and a mean zero. To check whether the results are robust against the model for mutation‐effect sizes, we also perform simulations in which mutation‐effect sizes are drawn from an exponential distribution mirrored around zero, so that the mean mutation‐effect size is zero. In these simulations the parameter of the exponential distribution is set to 2/σμ so that the variance of mutation‐effect sizes is equal to σμ2. Finally, we note that the analysis in Martin and Lenormand =−θ(2)=2 . The parameter σ is chosen to account for weaker (σ=4) or stronger selection (σ=2.5). For further details on selection parameters, see Supporting Information S1. To assess how the patterns are influenced by the local population size N, we contrast results obtained with N=1000 and 200. The migration rate m is set to a high value (m=0.1) that allows us to capture the signatures of migration under the chosen values of other model parameters. The recombination rate r between a pair of adjacent loci is set to r=0.0005 or 0.001 so that the first and the last locus in the genomic region simulated (with L=100 loci) are at a recombination distance of about 0.05 or 0.1, respectively (but the distance is larger for L=2000). Note that r=0.0005 corresponds to about 5×104 base pairs assuming that recombination rate between two nearby base pairs is 10−8. The mutation rate μ per generation, allele, locus, individual is chosen so that mutations that influence an individual's phenotype occur infrequently (μ=2×10−5). Finally, the variance of mutation‐effect sizes σμ2 is set to a small value (σμ=0.05) so that the square root of the total variance over all adaptive loci (Lσμ) is smaller than the distance between the optimal trait values θ(1)−θ(2). For the parameters set here and assuming that the whole genome region simulated acts as a single locus , this means that it requires, on average, about four adaptive steps for the populations to reach their optimal traits (taking into account diploidy). Otherwise, if the distance between the optima is equal to or lower than Lσμ, perfect adaptation in both populations can, by chance, be attained in a single adaptive step, which we consider to be an unlikely scenario in natural populations.At the start of a simulation, all individuals at all loci are assumed to have alleles of effect size zero. We set arbitrarily θ=−θ(2)=2 5) to allow the populations to come close to their local optima and stabilize. At intervals of 50 generations, we measure the extents of local and total genomic divergence as follows. The extent of local genomic divergence Dl at locus l is estimated as twice the difference between the allele‐effect size of the most frequent alleles at this locus in the two populations. The factor 2 is used because the population is diploid. Our measure of local genomic divergence divided by 2 corresponds to the measure d used by Yeaman and Whitlock −θ(2)=4. As an alternative to the measure Dl of the extent of local genomic divergence at locus l, one can use twice the average allele‐effect size at this locus . We note that the two measures of divergence  give rise to qualitatively the same patterns of divergence (see below). However, because the measure D is directly comparable to the measure d used by Yeaman and Whitlock .To understand the mechanisms at work in the multilocus model presented above, we analyze a two‐locus model. In particular, we use two versions of a two‐locus model. One is an a successful establishment of a mutation means that the mutant allele is most common (frequency >50%) in the deme where it is advantageous  determines whether divergence established in a genomic region at a given divergence stage will make a lasting contribution to overall differentiation. The balance between stochastic loss and gain at a given locus depends on the distance of this locus from other diverged loci in the genome, as well as the strength of local and total genomic divergence. To understand this dependence, we use the two‐locus gain–loss model.As noted in the introduction, earlier theory of divergence‐with‐migration focuses on evaluating the importance of the establishment bias for the evolution of genetic architectures during divergence‐with‐migration . The second locus is assumed to have stronger divergence Ds (>Dw) with allele‐effect sizes Ys (>Yw), and −Ys (and so Ds=4Ys). We vary the value of Ys in the simulations to mimic different stages of divergence . Using this model, we estimate the rate of local gain , and the rate of local loss at the two differentiated loci. When the rate of loss at a locus is larger than the rate of gain at this locus in a given stage of divergence, this locus is unlikely to make a sustained contribution to overall divergence. Otherwise, the opposite is true. In what follows, we explain our method for estimating the rates of gain and loss using this model.In this model, both loci are assumed to have established divergence. One locus is assumed to be weakly differentiated with the extent of divergence 2μN≪1) and when the two loci are at a recombination distance rj=jr , the rate of local gain λG,w(rj) at the weakly diverged locus is equal to the product of the probability that a locally beneficial mutation lands at this locus (2μN), and the probability pG,w(rj) that it establishes at this locus :w in equation s, we obtain the corresponding expression for the rate of local gain at the more strongly diverged locus. In the limit of λG,w(rj)≪1, the time to local gain at the weakly diverged locus is approximately exponentially distributed with mean λG,w−1(rj) (and similarly for the more strongly diverged locus).In the limit of rare mutations , lands at the weakly diverged locus immediately after the initialization of the system . In the other set of simulations, we assume that the mutation lands on the more strongly diverged locus . Further mutations are thereafter neglected. We further assume that in the former case the mutation lands in the first population  on an allele of effect size Yw (and similarly on Ys in the latter case). For these settings, the mutant allele is advantageous over both alleles at the locus prior to the mutation, and hence it will promote the local extent of divergence upon a successful establishment. We use a similar method to that explained in the establishment model (see above) to estimate the establishment probabilities pG,w(rj), and pG,s(rj)at the weakly and at the more strongly diverged locus, respectively. Finally, we use equation We estimate the rates of gain at the two loci using two separate sets of simulations. In one set, we assume that a mutation of a fixed mutation‐effect size, Tm) expires. As explained above, loss of divergence means that a locus becomes monomorphic due to fixation of one allele in both populations. Using simulations, we first estimate the probabilities pL,s(rj|Tm) and pL,w(rj|Tm) that the first loss event occurs at the more strongly or at the weakly diverged locus, respectively, conditional on it occurring before Tm. Here, rj denotes the recombination distance between the two loci (see above). Second, we estimate the average time ⟨tL(rj|Tm)⟩ until the first loss event based on simulations in which a loss has occurred by the maximum time Tm. Using these data, we estimate the rates of loss λL,s(rj) and λL,w(rj) at the more strongly and at the weakly diverged locus, respectively, based on the following considerations. In the limit of λL,s(rj)≪1, the time to loss at the more strongly differentiated locus is approximately exponentially distributed with mean λL,s−1(rj) (and similarly for the weakly diverged locus). Furthermore, in the limit of λL,s(rj)≪1, λL,w(rj)≪1, the time until the first loss event (either at the first or at the second locus) is approximately exponentially distributed with mean +λL,w(rj))−1. Therefore, the probability pL(rj|Tm)=pL,s(rj|Tm)+pL,w(rj|Tm) that the first loss event occurs either at the more strongly or at the weakly diverged locus by the time Tm is given by:In addition to the rates of gain, we estimate the rates of local loss at the two loci starting from the same initial condition as in the simulations described above, but now neglecting mutations. Each simulation is run under drift, selection, migration, and recombination until one or the other locus experiences loss of divergence or until a predetermined maximum time (⟨tL(rj|Tm)⟩ to the first loss event, conditional on the loss occurring by the time Tm, can be expressed in terms of λL,s(rj), λL,w(rj), pL(rj|Tm), and Tm as follows:Finally, we find that the average time BecauseλL,w(rj) given the probabilities pL,s(rj|Tm) and pL,w(rj|Tm), and the average time ⟨tL(rj|Tm)⟩ that we obtain using simulations. The rate of local loss at the more strongly diverged locus is obtained by combining equations We use equation ⟨tL(rj|Tm)⟩ is not defined if no loss occurs by the maximum time Tm set in the simulations. To avoid such cases, Tm has to be long enough +λL,w(rj))−1) to assure that loss occurs by this time with a high enough probability. Because we do not know the rates λL,s(rj) and λL,w(rj) in advance, Tm has to be chosen. Here, we set it to a large value Tm=105, because this allows us to compare the timescales of local loss and gain for other parameter values used in this study. Indeed, when the mutation rate is μ=2×10−5 . Importantly, in situations when no loss occurs by this time, we immediately deduce that the rate of local loss is much smaller than the sum of rates of gain at the weakly and at the more strongly diverged locus according to eq. Note that D≈2), the cluster of diverged loci attains a maximum size , with an average of around 15 loci , divergence starts to concentrate, resulting in formation of a cluster of divergence. Note that, comparing to weak selection, a cluster under strong selection starts forming in a much later stage of divergence in terms of the value of D, but sooner in terms of the number of generations after the start of divergence  than the other (Dw=0.2). First, analyzing the rate of gain at the two loci in an initial stage of the divergence process , we find that the rate is marginally larger at the more strongly diverged locus , the critical distance starts to decrease. Consequently, under weak selection and as Ds increases up to Ds≈2, the cluster grows reaching the size of about 20 loci , the clusters compete with each other for gaining new differentiation (or against losing the differentiation they have established). The dynamics of such a competition can be investigated by a gain–loss model similar to that analyzed here, but with more than two loci included and focusing on gain and loss of differentiation at individual clusters, each of which contains multiple loci.per se that matters but, as shown here, a balance between loss and gain processes, which operates differently in different stages of divergence. In a recent study, Aeschbacher and Bürger .Figure S5. Effect of drift.Figure S6. Same as in Figure 3 in the main text but for the selection parameter σ = 3.5 .Figure S7. Patterns of divergence under the parameter values similar to those in Figure 1C in the main text, but with 20 times more adaptive loci (L = 2000), and 20 times smaller variance σμ2 of mutation‐effect sizes.Figure S8. Same as in Figure 3 in the main text, but for the parameters corresponding to those in Figure S7.Figure S9. Patterns of divergence for the parameter values corresponding to those in Figure 1 in the main text, but here mutation‐effect sizes are drawn from an exponential distribution mirrored around zero .Figure S10. A comparison between patterns of divergence in a single stochastic realization of the model, but shown using two different measures for the extent of divergence at locus l, that is, in (A) we use the measure lD introduced in the main text , and in (B) we use instead twice the difference between average allele‐effect sizes at locus l in the two populations .Click here for additional data file.


Though elegant, this process is time-consuming (>30 min), subjects cells to high levels of stress (>350 g) and relies on user skill to enable fractionation of cells that layer as a narrow band between the density-gradient medium and platelet-rich plasma. We hypothesized that microfluidic adaptation of this technique could transform this process into a rapid fractionation approach where samples are separated in a continuous fashion while being exposed to lower levels of stress (<100 g) for shorter durations of time (<3 min). To demonstrate proof-of-concept, we designed a microfluidic density-gradient centrifugation device and constructed a setup to introduce samples and medium like Ficoll in a continuous, pump-less fashion where cells and particles can be exposed to centrifugal force and separated via different outlets. Proof-of-concept studies using binary mixtures of low-density polystyrene beads (1.02 g/cm Cells in the body are either organized as complex multi-cellular tissue or as heterogeneous mixtures in fluids such as blood. Separation of cells into different sub-populations is an essential step for various applications such as immune-phenotyping, tissue engineering and evaluation of systemic inflammation ,4,5,6,7.Leukocytes or white blood cells are responsible for maintenance of immune homeostasis and for protecting the body from injury and infections. Therefore, sampling leukocytes from a patient provides valuable information regarding the immediate immune and inflammatory status of the patient ,8,9. CelDensity-gradient centrifugation is one of the most commonly used separation methods for fractionation of leukocyte subpopulations from the perspective of efficiency, purity and cost. By exploiting density difference among leukocyte subpopulations and erythrocytes, less dense peripheral blood mononuclear cells (PBMCs) are enriched in a suspended buffy layer following >350 g centrifugation for 30 min. User skills are critical for extraction to ensure efficient fractionation via removal of the thin band of PBMCs layered in between the Ficoll–Paque layer and platelet-rich plasma. However, this approach imposes stress on the cells leading to activation of leukocytes .Microfluidics provides a powerful platform for analysis of small biological samples via precise manipulation of the fluids. Several microfluidics-based approaches have been developed to isolate and analyze leukocyte populations. The most common microfluidic approaches for isolation of mononuclear leukocytes or peripheral blood mononuclear cells (PBMCs) have exploited size difference to achieve separation of target cells via either filtration or inertial focusing-based platforms ,16,17. H+ cells, a centrifugally driven immunoassay where antibody-coated beads are transported via centrifugal forces and an ELISA-like readout is used to facilitate accurate dosing of VEGF [There have been several prior efforts that have utilized centrifugal force to drive fluids or achieve cellular separations using microfluidic approaches. However, their approaches do not accomplish high-fidelity miniaturization of conventional density-gradient centrifugation where red blood cells and polymorphonuclear cells (PMNs) are isolated from PBMCs in unique fractions. Al-Faqheri et al. present an excellent review summarizing centrifugal force-based microfluidic efforts for cell separations . Other w of VEGF , Schaff  of VEGF  develope of VEGF  where a  of VEGF  develope of VEGF . Rather  of VEGF  describe of VEGF  developeThe major design challenge in miniaturizing conventional density-gradient centrifugation is to account for scaling effects that distinguish microscale fluid behavior from conventional macroscale effects. Fluid flow in microfluidic channels is primarily laminar. However, in low aspect ratio channels, at higher Reynolds number flows, when cells and particles are comparable to the size of the channel, the parabolic flow profile that develops in these channels results in a velocity gradient across the cross-section of the channel resulting in inertial lift forces that cause migration of cells and particles to the outer walls. The wall lift forces push back on the cells/particles and equilibrium is achieved, resulting in focusing close to the walls with larger particles closer to the wall and smaller particles further away. When rectangular channels are arranged in a curved/spiral fashion, secondary Deans forces also develop resulting in rotational effects on the flowing fluid. This results in a single focusing position close to the inner wall.For our setup to work conceptually, we require the centrifugal forces to be much greater than the inertial lift forces rendering the focusing effects due to fluid flow in the channels irrelevant with minimal generation of secondary Deans forces, which can cause mixing of the two phases (sample and Ficoll-Paque) flowing side by side. This is achieved by achieving specific geometries for a given spinning speed to ensure that the Reynolds number, which dictates the magnitude of the inertial lift forces, and Deans number, which dictates the magnitude of forces that cause fluid rotation within the channels, are small enough to not affect the flow and separation within the microfluidic channels.3) and high-density silicon dioxide (SD) beads (2.2 g/cm3) with Ficoll–Paque (1.06 g/cm3).This paper details an approach that has great potential to be adapted for separation of PBMCs in the clinical setting. Conventional density-gradient centrifugation with Ficoll–Paque was miniaturized as a pump-free, continuous, label-free microfluidic system that, when mounted onto a custom built rotary platform, can enable separation of cells based on differences in density. While conceptually simple and straightforward, without minimization of inertial lift forces and Deans forces laminar flow of samples and Ficoll-Paque side-by-side will not be possible. This was accomplished via careful manipulation of channel dimensions, fluidic resistances, orientation of inlets and outlets and direction of rotation. To demonstrate successful proof of concept of this technique to separate cells/particles of different densities, we utilized low-density polystyrene beads (PS)  and a custom-designed rotary platform that can be mounted on the motor to hold the microfluidic device . The rot3)  and high-density silicon dioxide beads (2.2 g/cm3)  with Ficoll–Paque (1.06 g/cm3) . The particles were suspended as a 2% solution in 1X phosphate buffered saline (PBS) with 1% bovine serum albumin (BSA) to prevent aggregation. The solutions were vigorously shaken prior to use, loaded in beads reservoir along with Ficoll–Paque and accelerated rapidly for 5 min and then gradually decelerated until the system came to rest.To demonstrate proof-of-concept, we used 2 different particles with different densities and a Ficoll–Paque solution with an intermediate density. Specifically, we used low-density fluorescently labeled polystyrene beads (1.02 g/cmn = 3). After spinning stops, the inlet reservoirs and outlet collection tubes were removed and the quantity of liquids in each was measured to estimate the collective and relative flow rates. 1X (PBS)  and Ficoll–Paque Plus  were loaded in each reservoir and the centrifugation system was operated between 400-1600 rpm for 5 min . For evaluation of beads within the channels, PDMS devices bonded to glass were directly imaged at different locations. Samples collected in the reservoirs were analyzed using a hemocytometer. Fluorescently labeled polystyrene beads were distinguished from silicon dioxide beads via fluorescence imaging.Various designs were evaluated for establishment of optimal laminar flow and layering of the sample stream over the Ficoll–Paque stream. The design that produced the optimal results without inducing mixing due to inertial forces and Deans forces was 3 mm wide with a pitch of 45 mm . The totn = 3) and the standard deviations negligible.To estimate the total and relative flow rates of particle samples and Ficoll–Paque, we measured the quantity of liquid in the inlet reservoirs and in the outlet collection tubes following spinning at different speeds ranging from 400 to 1600 rpm . The rat3) suspended in a 1X PBS solution was flowed into the system and layered over either 1X PBS (1.00 g/cm3) or Ficoll–Paque (1.06 g/cm3) and the device was spun at a speed of 875 rpm, which generates centrifugal force of ~40 g. As expected when layered over 1X PBS, the centrifugal force pushes the PS beads through the lower-density 1X PBS resulting in >99% of PS beads being collected via the distal outlet .SD beads with a density of 2.2 g/cml outlet C. Resultn = 5). Bright-field and fluorescence images of PS and SD beads at different locations  during this process are shown in Finally, the ability of this device to achieve separation of particles of low- and high-density particles with a medium of intermediate density was accomplished. A 1X PBS solution containing a 4% solution of equal amounts of PS and SD beads was layered over Ficoll–Paque and the device was spun at 875 rpm (40 g). Results confirm that high-efficiency separation of PS and SD beads can indeed be accomplished using this approach with >99% PS beads collected via the proximal outlet and >99% of SD beads fractionated via the distal outlet . ResultsDensity-gradient centrifugation is an elegant technique that exploits differences in cell mass densities to achieve separation of PBMCs from erythrocytes and polymorphonuclear cells (PMNs). While this technique has been extensively used for over 50 years, shortcomings associated with high levels of stress imposed on cells, extended processing times and need for skilled technicians to cleanly isolate the fractionated samples have not been addressed. Microfluidics systems have great potential to miniaturize conventional macroscale separation approaches where samples confined in micrometer sized channels can be manipulated to enable faster, more precise and highly effective separations. To overcome the high levels of stress on cellular samples and minimize separation time, we sought to develop a microfluidic adaptation of conventional density-gradient separation process focused on minimizing duration and magnitude of centrifugation-induced stress on cells.To accomplish this, we designed a system that could house a microfluidic device that was bonded to a 4’’ silicon wafer and subject it to rotary motion to induce centrifugal force for cell and particle separation. The microfluidic device itself consists of a channel where cell/particle samples can be layered as a laminar stream over medium like Ficoll–Paque. Within microfluidic devices, low Reynolds number flows ensure that viscous forces are dominant and laminar flow is achieved. In order to minimize inertial effects and potential Deans forces that can induce rotational mixing of the sample stream with the Ficoll–Paque, the width of the channel (3 mm) was significantly larger than the height of the channels (50 μm) resulting in an aspect ratio of 60:1 (w:h) and ensuring large interfacial contact area between the fluids and the device. This ensured that introduction of two streams of fluids with different viscosity and density can be maintained as laminar streams and the layering is maintained during rotational motion of the device. It is also critical that the samples flow direction is in the same direction of the rotary motion to avoid disruption of the layering process. Further, it is important to position and orient the inlet reservoirs and inlets correctly to ensure proper flow of samples and Ficoll–Paque into the device. In our pump-less system, centrifugal force was used to induce fluid flow by ensuring that the outlets were placed further from the center of the wafer than the inlets. The ratio of fluids was adjusted by controlling the fluidic resistances (tubing and inlet channel length and diameter). To achieve proper fractionation, the fluidic resistance of the two outlets was adjusted to ensure separation of low- and high-density particles. Finally, to avoid trapping and retention of the high-density particles within the channels, the spin speed  needs to be controlled to ensure that the high-density particles travel into the Ficoll–Paque layer but do not travel all the way to the outer wall.Prior to optimizing this system for separation of cells, we sought to demonstrate proof-of-concept using particles. Polystyrene (PS) particles have a lower mass density than Ficoll–Paque, whereas silicon dioxide (SD) particles have a higher mass density and provide ideal particles for feasibility demonstrations. Initially, to confirm that beads introduced within the system experienced centrifugal force and moved across the channel we tested PS beads in solution with PBS. Our results confirm that higher-density PS particles move through the lower density PBS and are collected via the distal outlet. When the same PS beads were layered over Ficoll–Paque, the higher-density Ficoll–Paque retarded the motion of the PS beads and the PS beads were collected via the proximal outlet. When SD beads were layered over Ficoll–Paque, the higher-density SD beads easily transited through the Ficoll–Paque and were collected via the distal outlet. Finally, when a binary mixture of PS and SD beads were layered over Ficoll–Paque, the low-density PS beads remained at the interface of the Ficoll–Paque layer and were collected via the proximal outlet, whereas the high-density SD beads transited through the Ficoll–Paque and were collected at the distal outlet. The separation efficiencies for all separations were >99% confirming that the conventional Density-Gradient Centrifugation can be effectively miniaturized.3) which have a significantly higher density than Ficoll–Paque (1.07 g/cm3) close to the outer wall. Increased spinning speeds resulted in pinching of SD beads against the walls due to higher centrifugal force, which prevents collection of SD beads out of the channels. For blood cells, we anticipate that based on the smaller density difference between red blood cells (1.08 g/cm3), granulocytes (1.077 g/cm3) and Ficoll–Paque, a higher spin speed (~2500 rpm) and longer residence time (42s) will be necessary to accomplish depletion of red blood cells and granulocytes. These calculations were made using a modified Stokes settling velocity equation.We believe that this technique is directly translatable to separation of blood cells. We utilized a maximum spinning speed of 875 rpm which translates to a residence time of 16 seconds within the device. This speed was sufficient to generate enough centrifugal force to move SD beads (2.2 g/cmIn summary, we demonstrate successful microfluidic adaptation of conventional density-gradient centrifugation. Proof-of-concept studies demonstrate high-efficiency separation of low-density PS beads from high-density SD beads when separated using a medium like Ficoll–Paque. These results suggest that this approach can potentially be adapted for separation of PBMCs from whole blood.


Heterogeneity of infectiousness is an important feature of the spread of many infections, with implications for disease dynamics and control, but its relevance to human influenza virus is still unclear. For a transmission event to occur, an infected individual needs to release infectious particles via respiratory symptoms. Key factors to take into account are virus dynamics, particle release in relation to respiratory symptoms, the amount of virus shed and, importantly, how these vary between infected individuals. A quantitative understanding of the process of influenza transmission is relevant to designing effective mitigation measures. Here we develop an influenza infection dynamics model fitted to virological, systemic and respiratory symptoms to investigate how within-host dynamics relates to infectiousness. We show that influenza virus shedding is highly heterogeneous between subjects. From analysis of data on experimental infections, we find that a small proportion (<20%) of influenza infected individuals are responsible for the production of 95% of infectious particles. Our work supports targeting mitigation measures at most infectious subjects to efficiently reduce transmission. The effectiveness of public health interventions targeted at highly infectious individuals would depend on accurate identification of these subjects and on how quickly control measures can be applied. E. coli O157, paratuberculosis or salmonella and has been shown to have implications for disease dynamics and controlet al. showed evidence of heterogeneity in viral shedding in symptomatic patients naturally infected by influenza A virusHeterogeneity of infectiousness is an important feature of the spread of many infections, such as For a transmission event to occur, an influenza infected individual needs to release infectious particles via respiratory symptoms. Key factors to take into account are virus dynamics, virus spreading in relation to respiratory symptoms, the amount of virus shed and, importantly, how these vary between infected individuals3Influenza within-host dynamics modelling allows a quantitative description of the infection and/or symptoms dynamics and has received increasing attention over the past decade678910111213Using a mathematical modelling approach, we aim to link viral shedding to influenza within-host dynamics and to identify parameters associated with heterogeneity of infectiousness.We used data from the control arm of five studies conducted between 1993 and 1997 comprising 56 healthy volunteers experimentally infected with influenza virus. These studies were randomized, double-blind, placebo-controlled registration studies of zanamivir treatment of H1N1 influenza virus . All were approved by ethics committees, and the volunteers gave their written informed consent. Volunteers were eligible for these studies if they were Caucasian men or women aged from 18 to 40 years, with serum hemagglutinin antibody titres of <1:8 to the relevant virus strains. They were non-smokers or smoked an average of less than 10 cigarettes per day and agreed not to smoke for the duration of the isolation period. They were judged to be healthy based on medical records, physical examination and laboratory investigations5 median tissue culture infective doses (TCID50) of influenza A/Texas/91/36 (H1N1) virus intranasally and were monitored daily for the following 7 or 8 days. A sample for viral shedding kinetics analysis was taken from each volunteer 8 or 9 times. In four studies (48 subjects), sample collection took place at 08:00 on day 0 (D0) before the challenge, and then on D1, D2, D3, D4, D5, D6, D7, and D8; no D8 sample was collected in the fifth study (8 subjects). The following symptoms were noted: earache, runny nose, sore throat, coughing, sneezing, breathing difficulties, muscle ache, fatigue, headache, feverish feeling, hoarseness, and chest discomfort. The intensity of each symptom was scored by the patient from 0 (none) to 3 (severe). Symptoms data were collected twice a day, at 08:00 and 20:00 on the same days as the viral titre samplesThe volunteers under placebo were challenged at 08:00 with 10We used the systemic symptoms score constructed in a previous study We adapted the within-host dynamic model previously developed by Canini and CarratV, infect target cells, T, at rate β and are cleared at rate c. The infected cells, I, produce virus at rate p and are lost at rate δ. The infected cells induce the production of local pro-inflammatory cytokines, FL, at rate γ. The local pro-inflammatory cytokines decrease the virus production rate, p, with an effect ψ, are cleared at rate αL and induce the production of systemic pro-inflammatory cytokines, FS, at rate ρ. As the cytokines levels were not measured, we set their dimension to F. Systemic pro-inflammatory cytokines are cleared at rate αS and induce the activation of the cytotoxic activity, N. Cytotoxic activity, whose dimension was set to cell−1.d−1, is induced at rate k by systemic pro-inflammatory cytokines and removes infected cells at rate η. We set k to 1 F−1. cell−1, d−2, without loss of generality, as this changes only the units in which cytotoxic activity is measured. A conversion factor σ is needed for the conversion from infectious virus, V in our model, to TCID50/mL as measured by the experimental dataσ = 0.69 TCID50/mL. cell−1 which is consistent with 1 mL virus stock having half the number of plaque forming units (PFUs) as the TCID50. The detailed dimension analysis is shown in In this model as represented in T0 = 4×108 cellsI0 = FL,0 = FS,0 = N0 = 0 as we assumed that there were no infected cells and the innate immune response  was not activated. T0 was determined by Baccam et al. as the number of epithelial cells lining the nasal turbinates of the respiratory tract0 was estimated as a parameter. We did not assume that V0 was the inoculated dose as we have no information concerning the quantity of virus remaining in the nose.The initial values for the different compartments were: α and IL-6 correlate with respiratory and systemic symptom dynamics17181920Local and systemic pro-inflammatory cytokines levels, particularly IFN-R(t) represents the respiratory symptom score at time t and Rmax = 12 is the upper limit of the respiratory symptom score scale. We computed the systemic symptom score in a similar fashion, as a function of the level of systemic cytokines FS(t) and the upper limit of the systemic symptom score scale, Smax = 12.http://www.lixoft.eu/). Individual parameters are computed as empirical Bayes estimates. We simultaneously fitted the viral titre data, the systemic symptom score data and the respiratory symptom score data.Nonlinear mixed-effect models were used in order to take into account the inter-individual variability (IIV) and to compute individual parameters see . Each paet al.When testing different models, we chose the model providing the smallest Bayesian information criteria (BIC)We computed the population and individual infectiousness and other epidemiological parameters (incubation period and duration of symptomatic phase) to predict how these parameters would vary within a large population. We used the estimated population VK/SD parameters to compute the population epidemiological parameters. We simulated 1,000 subjects by drawing 1,000 sets of individual VK/SD parameters from the distributions estimated above, taking into account the correlation between the different distributions. We then simulated the individual viral kinetics, systemic and respiratory symptoms dynamics. We used these simulations to predict how individual infectiousness varies in time. We present the median and inter-quartile range (Q1-Q3) for the parameters computed from the simulations.et al.’sJ(t) = V(t)(b+sR(t)), where b is the baseline infectiousness in the absence of respiratory symptoms and s the slope factor. Indeed, infectious particles can also be produced during normal breathingR(t) and V(t) are the individual respiratory symptom score and viral titre at time t predicted by the within-host model.We assumed that infectiousness is a function of viral titre and respiratory symptoms. We adapted Chen For symptomatic subjects, we computed the incubation period as the time from inoculation to reach a total symptom score (i.e. the sum of both respiratory and systemic symptom score) of 1, 2, 3 or 4 and the duration of the symptomatic phase as the time during which the total symptom score is above 1, 2, 3 or 4.56 volunteers were included in the control arm of the 5 studies of antiviral drug trial and received only placebo treatment. 12 of these subjects did not have a virus-positive sample on any occasion after the challenge and were therefore excluded from the analysis as uninfected. Of the 44 subjects shedding influenza virus, 9 did not report systemic symptoms on any occasion after the challenge and 4 of these did not report respiratory symptoms either; these 4 subjects were therefore considered as asymptomatic. The peak for total symptom (i.e. the sum of systemic and respiratory symptoms scores) had a median score of 6 and ranged between 0 and 20, for a scale ranging between 0 and 24.10 TCID50/mL (Q1-Q3: 1.24–2.14) whereas for subjects with maximal total symptom score above 2, the median AUCV is 4.76 log10 TCID50/mL (Q1-Q3: 4.09–5.52).Time courses of virus titres and symptoms scores are summarized in V0, δ and c  and the area under the total symptom curve (AUCS) are positively correlated  and the maximal total symptom score and the maximal viral titre are also positively correlated . This shows that viral titre and total symptom score are correlated.β, is 2.3-fold higher; virus production rate, p, 2.1-fold higher, effect of pro-inflammatory cytokines on virus production, ψ, 2.9-fold higher, cytotoxicity, η, 5.5-fold smaller, local cytokine production rate, ρ, 2.4-fold higher, local cytokine clearance, αL, 3.3-fold smaller, systemic cytokines production, γ, 2.5-fold smaller and systemic cytokine clearance, αS, 3.1-fold higher in symptomatic than in asymptomatic. The increased cytotoxicity induces a rapid halt in the virus life-cycle, which reduces the subsequent inflammation responsible for symptoms.From the simulations of 1000 subjects, we predict that 30.1 to 67.4% of subjects are asymptomatic or paucisymptomatic, when we set the maximal symptom score threshold between 1 and 4. For the symptomatic subjects, the incubation period lasts on average 1.9 to 2.4 days and subjects exhibit symptoms for an average of 1.5 to 2.4 days, depending on the threshold . SymptomThe peak of infectiousness occurs 1.5 to 2.2 days later in asymptomatic subjects than in symptomatic subjects.b and s. These subjects were the most infectious with the different values of b and s ): the virus production rate, p, the cytotoxic activity, η, local cytokine clearance rate, αL, and local cytokine production rate, γ.Four parameters are significantly  correlated with infectiousness .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.