Potato virus Y (PVY) variants differing at most by two substitutions involved in pathogenicity properties. Model selection procedures were used to compare experimental results to six hypotheses regarding competitiveness and intensity of genetic drift experienced by viruses during host plant colonization. Results indicated that the frequencies of variants were well described using Lotka-Volterra models where the competition coefficients ijβ exerted by variant j on variant i are equal to their fitness ratio, jr/ir. Statistical inference allowed the estimation of the effect of each mutation on fitness, revealing slight (s = −0.45%) and high (s = −13.2%) fitness costs and a negative epistasis between them. Results also indicated that only 1 to 4 infectious units initiated the population of one apical leaf. The between-host variances of the variant frequencies were described using Dirichlet-multinomial distributions whose scale parameters, closely related to the fixation index FST, were shown to vary with time. The genetic differentiation of virus populations among plants increased from 0 to 10 days post-inoculation and then decreased until 35 days. Overall, this study showed that mathematical models can accurately describe both selection and genetic drift processes shaping the evolutionary dynamics of viruses within their hosts.Uncovering how natural selection and genetic drift shape the evolutionary dynamics of virus populations within their hosts can pave the way to a better understanding of virus emergence. Mathematical models already play a leading role in these studies and are intended to predict future emergences. Here, using high-throughput sequencing, we analyzed the within-host population dynamics of four  Potato virus Y variants differing at most by two substitutions involved in pathogenicity properties. The competitiveness costs induced by these mutations as well as the mathematical expressions of the competition coefficients of virus variants were derived from Lotka–Volterra equations. High genetic differentiation of virus populations between hosts was evidenced as well as its hump-shaped behaviour with time. The modelling framework proposed here was intended to help design control strategies aiming to prevent virus emergences.Natural selection and genetic drift drive the evolution of virus populations within their hosts and therefore influence strongly virus emergences. To help predict future virus emergences, we developed a model that estimates simultaneously genetic drift and selection intensities using high-throughput sequence data representing the within-host population dynamics of  Plant virus emergences represent near half of emerging plant infectious diseases Natural selection is a deterministic process by which the frequencies of the fittest variants in a given environment increase Potato virus Y (PVY) variants simultaneously submitted to genetic drift and natural selection. The four variants differ by one or two mutations that change their pathogenicity properties towards pepper genotypes carrying resistance alleles at a single locus While within-host genetic drift and selection act simultaneously, and thus jointly determine emergence, their intensities have rarely been estimated and modelled jointly from experimental data. Drift intensity was often measured using populations of pathogen variants with equal multiplicative fitness Capsicum annuum L.) genotype used in this study was Yolo Wonder, a bell pepper cultivar susceptible to all PVY isolates. The SON41p infectious cDNA clone 2pvr2 resistance gene (The pepper (nce gene  [20].Nicotiana clevelandii plants (four week old) N. clevelandii plants were calibrated using DAS-ELISA i.e. at two-leaf stage). The conformity of each variant was checked by direct sequencing of the RT-PCR product corresponding to the entire VPg cistron of the PVY populations present in the four plants used for the inoculum Inoculations were carried out under insect-proof greenhouse conditions. First, separate inoculations with the cDNA clones were realized by DNA-coated tungsten particle bombardments of juvenile Avian myeloblastosis virus reverse transcriptase (Promega), the high-fidelity Herculase II fusion DNA polymerase (Stratagene) and primers PYRO-FOR  and PYRO-REV . Emulsion-PCR and high-throughput 454 sequencing were realized by GATC-Biotech . The genome region sequenced encompasses notably codons 101 to 123 of the VPg cistron which has been demonstrated by reverse genetics to be the only region involved in breakdown of the pvr2 resistance genes in pepper Virus populations were separately sampled from eight plants at five successive dates: 6 days post-inoculation (dpi) corresponding to the 3–4 leaf stage, 10 dpi (5–6 leaf stage), 15 dpi (7–8 leaf stage), 24 dpi (11–12 leaf stage) and 35 dpi (22–23 leaf stage). Additionally, a sample of the mixed inoculum used for mechanical inoculations on pepper plants was also collected. At each date, all leaves of each plant were harvested, homogenized in a buffer (0.03 M phosphate buffer (pH 7.0) supplemented with 2% (w ∶ v) diethyldithiocarbamate; 4 mL of buffer per gram of leaves) and total RNAs were purified with the Tri Reagent kit  from a 150 µL aliquot of each sample. RNAs were used to amplify the central part of the VPg cistron by RT-PCR with In addition, in order to estimate the effective population size during leaf colonization, the eight plants sampled at 15 dpi were kept till 50 dpi and then a single newly grown leaf was sampled randomly on each plant . These lWe obtained between 209 and 930 correctly assigned sequences per virus population of each pepper plant, corresponding to a total of 24,166 sequences. Alignment was done using default parameters of the software SeqMan . Because indels are the most frequent 454 pyrosequencing errors i(t)V of virus variants i = 1,…,4 at time t, within a host plant behaved as a deterministic interacting system of four ordinary differential equations (ODE):To investigate the time course of competing virus populations within host plants, we merged deterministic and stochastic aspects into a single model. The deterministic aspect relied on the assumption that the mean numbers (or densities) K is the virus carrying capacity of a plant,ir is the intrinsic rate of increase of variant i,i,jβ is the coefficient that accounts for the competition strength exerted by genotype j on genotype i,i,jμ is the mutation rate from genotype j to genotype i.μ denotes the point mutation rate per replication cycle and per nucleotide, we get i and j are distant from one mutation and i and j are distant from two mutations.Equation 1 extends Lotka-Volterra competition equations to four competitors i(t)V due to the heterogeneity of virus populations between plants and to the nature of samples (counts of virus sequences). To be more specific, let p sampled at time t (dpi) corresponding to virus variants NN, DN, NH and DH. Our second main assumption states that, conditionally to the total number i.e.:(i)t over all plants t.N (discarding time and plant indices t and p) is N results from a two-step random procedure. First, a non-observed random vector totN and random frequencies Λ, N is drawn according to a multinomial p at time t gives rise to a non-observed random vector θ(t) and on overall theoretic means λi(t) of the variant frequencies. The numbers p at time t is a multinomial θ(t) decrease the genetic differentiation among host plants. Asymptotically, if i.e. Λ is deterministic and equals λ. Besides, θ(t) can be actually related to the so-called fixation index FSTFor clarity, we recall that an integer valued vector t were given via the ODE system as Finally, the coupling between deterministic and stochastic components consisted in asserting that the overall frequencies of variants at time via the forms of the competition coefficients used to derive the overall theoretical frequencies i(t)λ and (ii) the intensity and temporal variation of genetic drift experienced by viruses during host plant colonization, which could be investigated via the time dependence of the scale parameter θ(t).Our goal was to determine (i) the forms of selection processes occurring between competing viruses within a host plant, which could be handled Accordingly, six models allowing four to 14 parameters  were con1) (C2) (C3)  (D2) , i.e. the number of founder infectious units initiating the systemic infection of a single leaf, we used a method based on FST statistics described in FST value at 15 dpi (resp. 50 dpi). A 95% confidence interval was calculated for eN with a bootstrap method by resampling data 1,000 times over plants.In order to estimate the effective population size . The detailed proof is provided in −5 and 4.34×10−7, respectively.The long term behaviour of the model that is best supported by the data  and at 50 dpi  among the same plants. At 15 dpi, three variants were systematically detected in all plants, although with varying frequencies .The scale of our study was the set of leaves of infected plants. It represents the epidemiologically-relevant part of the virus population since it is readily accessible to vectors that ensure plant-to-plant horizontal transmission. It is possible that the narrow bottlenecks and intense genetic drift observed at larger scales (whole plant and plant organs) are direct consequences of those incurred by virus populations at the smallest scale . Supporting this hypothesis, the time dependence of nt level  parallelFST values observed at later infection times are related to the sink-source transition undergone by leaves during plant growth. Source-to-sink translocation of carbohydrates through the phloem corresponds to the direction of the systemic movement of viruses within plants FST values. In the context of our experiments, the timing of the sink-source transition in pepper and its comparison with FST variation remain to be determined. The two above hypotheses are not mutually exclusive, since the increasing number of source leaves during infection could also increase the MOI FST values.It is also possible that decreasing 121H and N119D amounted to −0.45% and −13.2%, respectively. These figures agree with the distribution of the mutational effect of single nucleotide substitutions. Indeed non-lethal mutations reduce virus fitness by 10–13% on average 2pvr2 (mutation N121H followed by mutation N119D) −7). In natural context, the RB variant would most likely appear initially by mutation at a very low frequency in a virus population largely dominated by the fittest variants NN and NH. Note also that, although multidrug-resistant variants can be generated by recombination  and final  virus populations are represented in blue and red, respectively.Protocol used to estimate the effective population size during the colonization of a pepper leaf by (PDF)Click here for additional data file.Table S1Number of well-assigned and cleaned sequences to each sample (eight plants by date and the mixed inoculum) and number and frequency of each virus variant  in each population.(PDF)Click here for additional data file.Table S2eN during plant colonization.Estimation of (PDF)Click here for additional data file.Text S1Note on model identifiability and on likelihood-based inference.(PDF)Click here for additional data file.Text S2Mathematical analysis of the Lotka-Volterra model with mutation.(PDF)Click here for additional data file.


Nitrobacter was the dominant NOB in acetate-fed aerobic granules. In the conventional system, both Nitrospira and Nitrobacter were present in similar amounts. Remarkably, the NOB/AOB ratio in aerobic granular sludge was elevated but not in the conventional treatment plant suggesting that the growth of Nitrobacter within aerobic granular sludge, in particular, was partly uncoupled from the lithotrophic nitrite supply from AOB. This was supported by activity measurements which showed an approximately threefold higher nitrite oxidizing capacity than ammonium oxidizing capacity. Based on these findings, two hypotheses were considered: either Nitrobacter grew mixotrophically by acetate-dependent dissimilatory nitrate reduction (ping-pong effect) or a nitrite oxidation/nitrate reduction loop (nitrite loop) occurred in which denitrifiers reduced nitrate to nitrite supplying additional nitrite for the NOB apart from the AOB.In this study, we analysed the nitrifying microbial community (ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB)) within three different aerobic granular sludge treatment systems as well as within one flocculent sludge system. Granular samples were taken from one pilot plant run on municipal wastewater as well as from two lab-scale reactors. Fluorescent in situ hybridization (FISH) and quantitative PCR (qPCR) showed that  Nitrobacter is known to be capable of utilizing organic compounds and can grow by dissimilatory nitrate reduction  and oxidation of nitrite to nitrate by nitrite-oxidizing bacteria (NOB). Both AOB and NOB are known to grow lithoautotrophically without the need for any organic compound. AOB belong to four genera in the Betaproteobacteria and Gammaproteobacteria and use oxygen as electron acceptor to oxidize ammonium in two steps by using AMO and HAO enzymes  within different biofilm and flocculent sludge systems.The microbial diversity of nitrifying bacteria has been extensively described for conventional activated sludge-based wastewater treatment systems. In these processes, the most common AOB found belong to the genus 2/L by using two mass flow controllers (one for air and other for nitrogen gas). The volume exchange ratio and the hydraulic retention time (HRT) were 57 % and 5.2 h, respectively. Sludge retention time (SRT) was maintained around 30 days by periodically removing sludge from the reactor. The SRT calculation can be found elsewhere  NH4Cl 35.4 mM, K2HPO4 4.2 mM, KH2PO4 2.1 mM and 10 mL/L trace element solution  of 2.6 L was operated at 30 °C. Temperature was held constant by means of a thermostat, and the reactor was protected against cooling with a thermal isolation placed around the reactor. The operational cycle lasted 3 h and was divided into the following phases: 60-min anaerobic feeding from bottom of the reactor in a plug flow regimen; 112-min aeration period; 3-min settling and 5-min effluent withdrawal. Aeration and mixing were achieved through an air diffuser placed in the bottom of the reactors (airflow rate of 4 L/min). pH was kept at 7.0 ± 0.2 pH units by dosing 1 M NaOH or 1 M HCl. Dissolved oxygen (DO) concentration was controlled at 2.0 ± 3 mg O2/L in order to suppress the growth of NOB  reactor was operated as described in previous research  was operated in a similar way as the lab-scale reactor. pH values were kept at around 7. The influent chemical oxygen demand (COD) and influent ammonium corresponded to approximately 600 mg/L and 50–100 mg N/L, respectively.The pilot-scale aerobic granular sludge reactor and the activated sludge reactor, treating the same wastewater, were operated in parallel in a domestic wastewater treatment plant . The pilot-scale granular sludge reactor (1.5 mt = 180 min) and was pre-aerated for 2 h to assure that all ammonium was completely oxidized. Subsequently, the granules were washed with tap water whose temperature was adjusted to 30 °C (operating temperature of the reactor), sieved and gently crushed to prevent the occurrence of denitrification in the anoxic zones of the granules, which would interfere in the nitrite oxidation rate measurements. The crushed granules were distributed equally (based on the wet weight) to 250-mL flasks. Air was supplied to the batch flasks, which were filled with 50 mM Tris–HCl buffer (pH 7.0) and placed in a water bath kept at 30 °C. A pulse of either ammonium or nitrite solution was added in the beginning of the experiment in order to achieve initial concentrations of 50 mg N/L and 20 mg N/L, respectively. Samples were collected every 5–20 min and measured for ammonium, nitrite and nitrate. Biomass specific rates were obtained by linear regression of either ammonium or nitrite concentrations in time divided by the constant concentration of volatile suspended solids (g VSS/L) in the batch flask. The experiment was repeated several times over a period of 2 months.In order to compare the maximum ammonium and nitrite oxidation rates, batch tests were performed under fully aerated condition (DO kept at 100 % air saturation) with granular sludge from the lab-scale reactor. Representative biomass was taken at the end of the operational cycle  by polyphosphate-accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs). Denitrifying PAOs and GAOs were actually the main active denitrifiers in the reactor, since no external organic carbon source was available during aeration period to be used as electron donor by other heterotrophic bacteria to accomplish denitrification in the anoxic zones of the granules. Granules were sieved and washed with tap water at 30 °C. Equal amounts of granules (based on the wet weight) were introduced in different 250-mL flasks filled with a Tris–HCl buffer (pH 7.0) containing the same minerals of the synthetic media fed to the reactor (except for acetate and phosphate). Nitrogen gas was supplied to each flask through porous diffusers in order to keep anaerobic conditions. A pulse of nitrate was given to obtain a final concentration of 30 mg N/L. From this point, samples were taken regularly every 10–20 min for determination of nitrate concentrations. Specific nitrate reduction rates could then be obtained by linear regression of nitrate concentration over time divided by the constant amount of VSS in the batch flask.2/L). Specific nitrate reduction rates were obtained by linear regression of the nitrate uptake in time divided by the amount of VSS in the reactor.Anoxic cycle tests were also performed in the lab-scale reactor under fully anoxic conditions. In these tests, no air was supplied to the reactor, and anoxic conditions were achieved by supplying nitrogen gas instead of air through the porous diffuser. Nitrate was gradually added according to the denitrification rate, which was estimated based on the difference between the ammonium uptake rate and the nitrite/nitrate production rate obtained in the cycle tests performed under normal operation conditions (DO: 1.8 mg O4-N), nitrate-nitrogen (NO3-N) and nitrite nitrogen (NO2-N) were measured by means of a flow injection analyzer . Phosphate (PO4-P) was quantified by Hach Lange cuvette tests (LCK 350). Biomass concentration, in terms of volatile suspended solids (VSS), was determined as described in previous research  reactor . ΔCT was calculated by the following equation: ΔCT = CT(ref) – CT(target) , hardened by freezing −20 °C) and cut in the frozen state with a microtome-cryostat (Leica CM1900-Cryostat) into 25-μm thin slices. Dried slices were kept on a microscopic glass slide, and FISH was performed for determination of PAOs, GAOs, AOB and NOB (Fluos) populations in the same manner as reported by Winkler et al. . Sequenc0 °C and YX/N). For mixotrophic growth of NOB on acetate, a biomass yield from heterotrophs was assumed (YX/HAC) (Table The estimated autotrophic community composition was based on the biomass yields on ammonium (AOB) or nitrite (NOB) (C) Table . The theC) Table .Table 3Bt = 62 min) to allow sufficient mixing. During the anaerobic feeding period (data not shown), all acetate is converted to intracellular polymers (e.g. polyhydroxybutyrate—PHB) by PAOs or GAOs leaving no dissolved organic carbon for the subsequent aerobic period. During anaerobic feeding, phosphate is released by PAOs and is subsequently taken up by the same microorganisms during the aerobic period. After the feeding period, PAOs and GAOs degrade internally stored PHB and use the generated energy for growth  than the ammonium uptake rate (2.3 mg NH4-N/gVSS/h). Since denitrification was prevented by using crushed granules (therefore eliminating the anoxic zones within the granules), all nitrite consumption was due to nitrite-oxidizing activity. Repeated experiments showed a good reproducibility. The results shown in Fig. Batch experiments with crushed granules (to eliminate oxygen diffusion limitation) under fully aerobic conditions (DO kept at 100 % air saturation) were performed to compare the maximum ammonium- and nitrite-oxidizing activities. The ammonium, nitrite and nitrate profiles of the aerobic tests with ammonium and nitrite dosage are illustrated in Fig. During normal reactor operation, nitrification and denitrification processes occur simultaneously. Therefore, it is difficult to distinguish the amount of nitrite oxidized by NOB and the amount of nitrite reduced by denitrifiers. In order to have a better insight into the denitrification potential in the granular sludge reactor, two types of experiments were carried out under anoxic conditions: anoxic batch test in the aerobic granular sludge reactor with a continuous supply of nitrate instead of oxygen during the aeration (mixing) phase Fig.  and a baNitrobacter was the main NOB present in aerobic granular sludge. In the conventional treatment plant, both Nitrospira and Nitrobacter coexisted in roughly equal amounts.To study the nitrifying population within the aerobic granular sludge, a comparative study between the amount of AOB and NOB was performed by means of qPCR. Ratios between NOB and AOB were constructed for samples collected from an autotrophic CANON/Anammox reactor, a conventional treatment plant, an aerobic granular sludge pilot plant and a lab-scale aerobic granular sludge reactor Fig. . Both asIn wastewater treatment systems, nitrifiers are expected to account for 1–3 % of the total community composition due to their low growth yield. Therefore, FISH was also conducted with PAOs and GAOs to have a reference for the heterotrophic community Fig. . The FISIn order to calculate how much COD is needed to increase the NOB/AOB ratio to 3, we assumed that NOB grew mixotrophically on organic acids with nitrate as electron acceptor and we considered a biomass yield similar to general heterotrophs. Calculations showed that a theoretical amount of 37 mg COD/L is needed to elevate the expected autotrophic NOB/AOB ratio of 0.5 by a factor 6  in heterotrophic aerobic granular sludge from a pilot plant and a lab-scale reactor using FISH, qPCR analysis and activity batch tests. In contrast, qPCR measurements on samples from the conventional treatment plant operated in parallel with the aerobic granular sludge pilot reactor did not show elevated NOB levels. Moreover, the negative control samples collected from a CANON reactor revealed expectedly low NOB/AOB ratios (i.e. ca. 100-fold lower than AOB). A qPCR on ammonium-oxidizing archaea was conducted, but no signal could be detected (data not shown). Nitrobacter using acetate as electron donor and carbon source, and therefore the growth of Nitrobacter is uncoupled from the direct nitrite supply of the AOB. The second theory is referred to as the ‘nitrite loop’, in which a nitrite oxidation/nitrate reduction loop takes place in the granules  to store intracellular polymers to balance their growth  has also all enzymes of the tricarboxylic acid (TCA) cycle but does not synthesize PHB as storage products, and there is also no experimental evidence that Nitrosomonas can generate PHB from organic acids  has been experimentally proven in pure nts Bock . Additio3), nitrite (NO2), nitric oxide (NO) and nitrous oxide (N2O) are reduced to nitrogen gas (N2) (Philippot 2− to gaseous NO by nitrite reductases (NirK or NirS) can be the rate limiting step in denitrification in certain types of bacteria  were used to investigate and understand the unexpected elevated NOB/AOB ratio in aerobic granular sludge systems. We observed that the NOB population in the granular systems was dominated by Nitrobacter have grown mixotrophically by acetate-dependent dissimilatory nitrate reduction (ping-pong effect) or a nitrite oxidation/nitrate reduction loop (nitrite loop) have happened in which denitrifying bacteria reduced nitrate to nitrite providing additional nitrite for the NOB apart from the AOB. The disproportion of the amount of AOB and NOB in granular sludge should be investigated further to confirm the hypothesis made in this work.Two hypotheses were proposed: either


Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) on the surface of parasitized red blood cells (RBCs), thereby weakening their cytoadherence to microvascular endothelial cells (MVECs) and impairing their activation of MVECs to produce pathological responses. Therefore, we hypothesized that parasites causing malaria in HbAS or HbAC heterozygotes have overcome this protective mechanism by expressing PfEMP1 variants which mediate relatively strong binding to MVECs. To test this hypothesis, we performed 31 cytoadherence comparisons between parasites from HbAA and HbAS (or HbAC) Malian children with malaria. Ring-stage parasites from HbAA and HbAS (or HbAC) children were cultivated to trophozoites, purified, and then inoculated in parallel into the same wildtype uninfected RBCs. After one cycle of invasion and maturation to the trophozoite stage expressing PfEMP1, parasite strains were compared for binding to MVECs. In this assay, there were no significant differences in the binding of parasites from HbAS and HbAC children to MVECs compared to those from HbAA children . These data suggest that in-vitro reductions in cytoadherence by HbS and HbC may not be selecting for expression of high-avidity PfEMP1 variants in vivo. Future studies that identify PfEMP1 domains or amino-acid motifs which are selectively expressed in parasites from HbAS children may provide further insights into the mechanism of malaria protection by the sickle-cell trait.Sickle hemoglobin (Hb) S and HbC may protect against malaria by reducing the expression of  Plasmodium falciparum malaria has selected for red blood cell (RBC) polymorphisms, including sickle hemoglobin (Hb) S, HbC, α-thalassemia, and G6PD deficiency 6 glu->val) is a balanced polymorphism in which HbAS heterozygotes are protected against both uncomplicated and severe malaria 6 glu->lys) generally affords protection against severe, but not uncomplicated, malaria + T cells and upregulation of heme-oxygenase 1; accelerated acquisition of immunity; and altered host pathogenic mechanisms , the parasite's variant surface antigen and cytoadherence ligand, on ‘knobs’ on the surface of parasitized HbAS and HbAC RBCs For millennia, the significant morbidity and mortality of Abnormal PfEMP1 display is characterized by (i) reduced PfEMP1 levels, (ii) reduced knob densities, (iii) heterogeneous distributions of PfEMP1 and knobs, and (iv) aberrant – wider and more protuberant – knob morphologies var genes, which encode PfEMP1 var genes Var genes share a two-exon structure, which encodes for a semi-conserved intracellular domain (exon 2) and an extracellular domain (exon 1) comprised of Duffy binding-like domains (DBLs) and cysteine-rich interdomain regions (CIDRs) The expression of PfEMP1 on parasitized RBCs also leaves parasites vulnerable to detection by the immune system. To avoid this, individual parasites undergo antigenic variation by switching from one clonally-expressed PfEMP1 variant to another Differential affinity of individual DBLs and CIDRs for specific host endothelial receptors  enables the organ-specific sequestration of parasitized RBCs and influences the clinical presentation and severity of malaria in-vivo studies to validate in-vitro findings. In considering ways to investigate these potential mechanisms, we hypothesized that parasites causing clinical malaria in HbAS and HbAC children must have somehow overcome the malaria protective effects of abnormal PfEMP1 display. One potential mechanism is that parasite populations in HbAS and HbAC children are selected to express particular PfEMP1 variants, which mediate stronger binding to MVECs in vivo than those expressed in HbAA children. This process could enable parasites to circumvent the protective effects of abnormal PfEMP1 display and cause malaria symptoms in HbAS and HbAC children. To explore this possibility, we tested whether parasites from HbAS and HbAC children with malaria show increased binding to MVECs in vitro than those from HbAA children in Mali.One challenge in defining the mechanisms underlying malaria protection in HbS and HbC children is the difficulty of conducting human P. falciparum-infected RBCs and uninfected RBCs were obtained from an ongoing cohort study conducted in three villages  located 75 km southwest of Bamako, Mali. From these villages, 1514 children aged 0.5–17 years were enrolled over three transmission seasons . All children were typed for Hb polymorphisms , ABO blood group (agglutination assay), α-thalassemia (nested PCR), and presence of the G6PD deficiency allele, G6PD*A- (G202A) (nested PCR), as described G6PD*(A-) allele] from healthy volunteers were similarly collected, washed, resuspended at 50% hematocrit, and stored at 4°C for up to 3 days before use. Ring-stage parasites from HbAA, HbAS, and HbAC children with malaria  and inoculated into wildtype RBCs at 2.5% hematocrit. After invasion of uninfected RBCs was confirmed by the appearance of new ring-stage parasites, the hematocrit was decreased to 0.8%. Once parasites matured to trophozoites, they were assayed for cytoadherence to MVECs in parallel with one or more other parasite isolates that were simultaneously cultivated, purified, and inoculated into the same wildtype RBCs.Venous blood samples from children with malaria were collected in sodium heparin Vacutainers , and the RBCs washed three times in RPMI 1640 . Uninfected ‘wildtype’ donor RBCs [i.e., HbAA, normal αα/αα genotype, and no  malaria Table 1 Human dermal MVECs  were grown in the manufacturer's EGM-2MV media for up to 5 passages and seeded into 8-well LabTak CC2-coated chamber slides  to achieve ∼30% confluency. Trophozoite-infected RBCs were magnetically purified and adjusted to 3–5% parasitemia  and 0.5% hematocrit using uninfected RBCs in binding medium . Parasitized RBC suspensions were added to MVEC-coated chamber slides (200 μl/well) and incubated on an orbital shaker (100 rpm) for 1 h at room temperature. Whenever possible, each parasite isolate was tested for binding in duplicate wells on the same slide. After the parasitized RBC suspensions were removed from each well, the gasket was detached from the slide. The slide was then washed by dipping horizontally in BM four times, fixed in 2% glutaraldehyde overnight at room temperature, and stained in 10% Giemsa for 30 min. The number of parasitized RBCs bound to ∼350 MVECs in each well was counted, and data expressed as number of parasitized RBCs per MVEC. Duplicate comparisons were made whenever sufficient numbers of parasites were available. Seventy-six percent (25/33) of comparisons were performed in duplicate, 50% of which had a ratio of replicate 1∶2 between 0.80 and 1.3 (range 0.5–2.5).An overdispersed Poisson regression was used to model the effect of Hb type (HbAS and HbAC) and age (≤5 and >5 years) on the binding of parasitized RBCs to MVECs, controlling for any ‘slide’ and ‘location within slide’ effects in our data set and for any multiple comparisons done with an individual parasite isolate. Analyses were done in Proc GLMMIX in SAS Version 9.2.ex vivo to the trophozoite stage, magnetically purified, and inoculated into the same wildtype donor RBCs  in an area of intense seasonal transmission for 3 years, we were able to make only 16 comparisons between HbAS and HbAA samples, and only 15 comparisons between HbAC and HbAA samples. The number of comparisons was limited by several factors. First, high numbers of parasites were required to conduct the ex-vivo cytoadherence assay before parasites switched PfEMP1 variants . Second, the assay required that parasites from HbAS (or HbAC) children mature synchronously in culture with those from HbAA children, which did not always occur. Third, HbAS conferred significant protection against malaria in our cohort (unpublished data) and so fewer parasite isolates were available from HbAS children. Additional factors limited data analysis. For example, more comparisons would have enabled us to include age as a continuous variable, providing finer resolution of age effects on cytoadherence. Also, 42% of comparisons between HbAS (or HbAC) and HbAA samples may have been confounded by co-inherited RBC polymorphisms  (We hypothesized that iciency) Table 1,in vivo to modulate the expressed var gene repertoire of parasite populations. Second, if a subset of high-avidity PfEMP1 variants are, indeed, being selected in HbAS children, they might offer an opportunity to identify “virulent” PfEMP1 variants and thus aid the discovery of putative “pathogenicity motifs”  that confer high-avidity binding phenotypes. While such motifs may only cause uncomplicated malaria in older children with HbAS, for example, they may be responsible for causing severe malaria in younger HbAA children who lack both immune- and hemoglobinopathy-mediated resistance to this disease. Such an approach would complement efforts to characterize PfEMP1 variants expressed in children with severe malaria. Since parasites from these children show increased binding to CD36 and ICAM-1, the PfEMP1 variants causing uncomplicated malaria in HbAS children might share features with those causing severe malaria in other children.It remains unclear whether our results reflect the limitations described above or to an actual lack of difference in binding phenotypes for parasites from HbAA and HbAS children – especially since parasites from HbAS children trended towards increased binding to MVECs, but failed to reach significance. However, the lack of statistical significance in both sets of comparisons suggests that any cytoadherence-dependent mechanism is likely working in concert with other factors  to prevent the development of uncomplicated and severe malaria syndromes. Additional studies that are powered to address some of these limitations are therefore warranted since the results from such studies would have two significant implications. First, they would provide insight into whether abnormal PfEMP1 display is working in vivo. Testing the binding of parasites from HbAS, HbAC, and HbAA children with malaria to individual receptors  as well as to MVECs derived from brain or lung may help to further clarify the binding phenotypes of these parasites. Furthermore, identification of “virulent” PfEMP1 domains associated with increased binding to MVECs may inform the rational design of PfEMP1-based vaccines against severe malaria.The results of our study suggest that our particular binding assay detected no clear differences between the cytoadherence of parasites from HbAA, HbAS, and HbAC children to MVECs. Although further studies that are adequately powered to account for age, severity of malaria episode, and co-inherited RBC polymorphisms are needed, our initial findings provide useful insights into the relationship between Hb types and PfEMP1 variants


To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat.Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining.Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining.Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease. Diffusion Tensor Imaging (DTI), developed more than a decade ago The diffusivity from traditional DTI is derived from a symmetric rank-2, positive tensorDespite its popular application, conventional DTI has shortcomings resulting from its two underlying assumptions. First, the use of a ‘single’ diffusion tensor for characterizing a pixel volume, which may contain thousands of tissue components, results in a diffusion tensor representing only an average of these multiple tissue components (compartments). Examples of DTI model failure in analyzing areas of fiber crossing in white matter have been documented To overcome these limitations of DTI, Q-space diffusion tensor imaging (Q-DTI), such as high angular resolution diffusion imaging (HARDI)Shannon's entropy is a measure of uncertainty or randomness based on information theory H) is evaluated via the equation:i)ppp(x log i)p with no history of neurological or psychological disorders participated in this study. Ten subjects were enrolled for the comparison between entropy and FA and the remaining three for the investigation of the effects of numbers of gradient directions on entropy. In our case study, a rat with MSC treatment after TBI was also studied MR images were obtained with a GE 3T MRI scanner utilizing an eight-channel head coil. The subject's head was comfortably secured in the head coil using foam padding. Disposable earplugs were provided to minimize the subject's exposure to instrument noise during scanning. T2 and DTI MRI measurements were obtained using the following parameters.2 was obtained using a fast spin-echo sequence. A TR value of 2.5 seconds was utilized with effective echo times of 14 and 120 milliseconds. Images were produced with a 24 cm field of view, 4 mm slice thickness, 32 slices, and a 512×512 matrix.T2, 15–90 directions uniformly distributed in space depending on the experiments, and 1 average and 6 b = 0 T2 weighted images.DTI was acquired using a pulsed gradient spin-echo echo-planar sequence with a TE/TR ratio of 92/10 ms, a 24 cm field of view, 96×96 imaging matrix, 2.6 mm slice thickness, b-value of 1500 s/mmvia controlled cortical impact 6 human bone marrow stromal cells (hMSCs) was implanted into the core of the lesion 2O:O2 (2∶1).Traumatic brain injury (TBI) ex vivo DTI was performed one day after death.MRI measurements were performed using a Varian 7 Tesla MRI scanner . A 12 cm bore actively shielded gradient coil set, capable of producing magnetic field gradients up to 20 gauss/cm was used. A saddle radio-frequency (RF) coil was used as the transmitter and a surface coil as the receiver. The animal was sacrificed at 6 weeks after TBI and 2 in each slice Q-ball based DTI was performed using a pulsed gradient spin-echo sequence. The FOV was 32 mm; four average, 128×128 imaging matrix, 1 mm slice thickness with 16 slices, TR = 1.5 s, TE = 38 ms, δ = 12 ms, Δ = 20 ms, 128 diffusion attenuated directions with b = 1500 s/mmHuman brain autopsy tissue samples (n = 30) and animal brain (n = 1) were studied for axonal analysis. To identify cerebral white matter properties, immunohistochemistry was performed on formalin-fixed, paraffin-embedded coronal brain sections (6 µm). Axonal density and orientation were examined using a combined Nissl/silver-staining method (Bielschowsky staining) Entropy was calculated on a voxel-by-voxel basis using To perform comparisons between histological axonal density with corresponding MRI entropy and FA, five randomly chosen fields of view in each ROI of cortical gray matter, corpus callosum (CC), putamen, thalamus, and frontal white matter (FW) of histological sections were digitized using a 40× objective (Olympus BX40) via the MCID imaging system . Captured images were digitally level-adjusted using the public domain NIH Image analysis program version 1.42 . Each black and white 8-bit image was binarized with the intensity threshold set at a pixel value of 170. The number of black pixels divided by the total number of pixels in the selected area was measured to represent axonal density. The average value from five fields of view in each ROI of histological sections was used in the correlation data analysis. The MRI entropy and FA were measured to correlate the histological axonal density from the same anatomic ROI. MRI analysis and histological analysis were performed by blind analysis of two persons.ANCOVA was used to test the differences between entropy and FA (as outcome of interest) among the regions (as correlated dependent covariate) to test overall region  effect on the difference. The paired t-test was performed at the region level if there was an overall region effect. For evaluating the correlation between entropy, FA, and histological axonal density, we correlated the means of entropy, FA, and histological axonal density in each ROI, as exploratory analysis, since we could not get the histological data from patients alive and the MRI and histological data were from different samples. Spearman correlation coefficient was calculated to measure the correlation of entropy and FA with histological evaluation, respectively. For evaluating effects of number of gradient directions  on entropy, entropy was measured at four regions of interest . The doubly repeated measure analysis of variance (ANCOVA) was used to test the direction and region effects (as correlated covariates) on entropy measurements (outcome of interest). The analysis started with testing for the number of directions by region interaction, followed by the subgroup analysis with focus on the direction effect at each specific region, if the interaction was significant at 0.05 level. A significant interaction indicated that the direction effects varied among the regions. The optimal number of directions was selected if entropy values with minimum directions approached that measured in 90 directions.In the human study, the signal intensities in the entropy and FA maps showed similar patterns of intensity changes, from the highest in CC, intermediate in gray matter, and the lowest in CSF. However, entropy maps exhibited a significantly enhanced dynamic range of contrast, especially in gray matter, compared with FA maps as demonstrated in To investigate the effects of number of directions of gradients on entropy in the human study, fifteen to ninety directions of diffusion gradients were performed. The corresponding entropy values measured from the same ROIs in CC, Cortex gray matter, FW, and CSF ROIs in Entropy in gray matter increased as number of directions increase from 15 to 90 and there were significant differences between 15 and 25 vs 90 and 70 as well as 15 vs 55. The entropy in FW exhibited a trend independent of the number of directions. However, a significant difference was detected only between 15 and 25 directions.To quantitatively compare the differences between entropy and FA, entropy and FA values from each ROI were measured and are listed in To better compare the differences between entropy and FA, percentages of normalized values for entropy and FA in different regions with respect to corpus callosum were calculated as listed in the In ex vivo FA (A), entropy (B), and q-ball fiber orientation direction (FD) maps , and Bielshowsky and Luxol fast blue images (E-H) from the fixed animal brain 6 weeks after TBI. White matter reorganization after MSC treatment, confirmed by an increase in axons  and myelination E-H, blue), coincided with increases in FA  in the extended region of the corpus callosum surrounding the lesion. The entropy map revealed increased diffusion entropy not only at the boundary of the lesion as shown on the FA map but also at the base of the lesion (yellow arrow), where fiber crossings of axons were confirmed by the q-ball fiber orientation map  and the Bielshowsky and Luxol fast blue images .In this study, diffusion entropy is investigated to detect axonal remodeling after injury. Our data demonstrated that diffusion entropy extracts more accurate structural details from brain tissues with crossing axonal bundles than does the conventional Gaussian model of DTI. The entropy method exhibits better dynamic range and distinction between different gray matter structures and CSF, without making any assumptions or modeling during the diffusion process. Our data also demonstrates that entropy strongly correlates with axonal density measured in human autopsy brain (r = 0.91), and is an important and sensitive method for detecting axonal remodeling during neurological recovery from animal model of TBI.Brain injury, such as TBI, remains a leading cause of mortality and disability among children and young adults. Current research in brain injury has been restricted to acute neuroprotection treatment with a short treatment window Entropy measurement can overcome the limitations of the conventional Gaussian model of DTI in detecting structural changes in gray matter and white matter containing crossing axons. Although conventional DTI based on the Gaussian model has become an important clinical measurement in detecting WM changes, it can not detect structural changes in gray matter due to its associated very small dynamic range, and can also produce large errors in detecting WM with crossing axons The number of diffusion directions affects entropy values. Although entropy values could be more stable and accurate with increased number of directions, it is more time consuming and less tolerable for patients. The optimum number of directions is determined by obtaining stable and reliable entropy values close to that measured with a large number of directions, such as 90, with minimum scan time or minimum number of directions. The entropy in CSF decreases with the increase in number of directions. CSF should have an entropy value close to 0 due to evident lack of structure. The measured entropy values in CSF are most likely due to image noise. The increased number of directions will increase the signal and decrease noise to derive decreased entropy. The CC has more dense unidirectional brain structure and therefore higher entropy values. The entropy value should be increased and then be stabilized after number of directions could provide proper information content and signal to noise ratio. Our data indicate that 55 directions may be an optimum number for diffusion directions to have relatively stable entropy in white matter and CSF. Also, there is no significant difference in entropy values between 55 and 90 directions in all the ROIs.Distribution of diffusion attenuation reflects amplitude of entropy. Mobility of water molecules along different gradient directions in brain can be evaluated using the attenuation of the MRI signal Entropy is superior to FA in detecting white matter reorganization with prominent crossing axons. The entropy is sensitive to the early stage of white matter reorganization with more crossing fibers, where the entropy significantly increases compared with the relatively low FA. However, the entropy shows a similar pattern as FA if the white matter is well organized to a single direction. The combination of entropy and FA may provide information about the stage of white matter reorganization in the injured brain, with increased entropy alone (without FA elevation) representing an early recovery stage of white matter reorganization with crossing fiber, while the increased FA identifies more mature linear fibers.This study investigated diffusion entropy in evaluating different brain tissues and its ability in detecting axonal remodeling after injury. Diffusion entropy resolves crossing fibers induced error without making any model assumption on the diffusion process, and detects axonal remodeling with crossing axonal bundles. Our results show high agreement (r = 0.91) between entropy and axonal density and superior image contrast in entropy compared with that in FA. Compared with FA, entropy may provide improved quantitative biomarkers of diseases that affect brain structures involving gray matter and white matter with crossing axons.


Systemic thrombolysis in acute ischemic stroke is restricted to the 4.5 h time window. Many patients are excluded from this treatment because symptom onset is unknown. Magnetic resonance imaging (MRI) studies have shown that stroke patients presenting with acute supra-tentorial diffusion-weighted imaging (DWI) lesions that do not have matching lesions on fluid attenuated inversion recovery (FLAIR) are likely to be within a 4.5 hour time window. This study examines the DWI-FLAIR mismatch in infra-tentorial stroke.http://clinicaltrials.gov; NCT00715533). Fifty-six patients with infra-tentorial stroke confirmed by MRI and known symptom onset who underwent the scan within 24 h after symptom onset were analysed. Two neurologists blinded to clinical information separately rated the DWI lesion visibility on FLAIR. Lesion volume, relative signal intensities of DWI and relative apparent diffusion coefficient values were determined.This was a retrospectively conducted substudy of the “1000+” study; a prospective, single-center observational study , and showed no significant correlation to lesion volume (p = 0.145).In our study the DWI-FLAIR-Mismatch does not help to reliably identify patients within 4.5 h of symptom onset in acute ischemic infra-tentorial stroke. Thus therapeutical decisions based on the DWI-FLAIR mismatch estimation of time from onset cannot be recommended in patients with infra-tentorial stroke. Systemic thrombolysis in acute ischemic stroke is restricted to the 4.5 h time window http://clinicaltrials.gov; NCT00715533). Written informed consent was obtained from all patients. This study and the consent procedure were approved by the ethics committees .This was a retrospectively conducted substudy of the “1000+” study; a prospective, single-center observational study  or the symptoms had occurred more than 24 h prior to the examination (3 patients). Only patients with symptomatic infra-tentorial lesions with clear onset were chosen. MRI studies were performed on a 3-T MRI scanner . The MRI sequence parameters were as follows: for DWI  and for FLAIR .DWI and FLAIR images were evaluated separately by two experienced raters  blinded to clinical information in terms of time from stroke onset to imaging, NIHSS and symptoms. FLAIR and DWI images were both made available. Raters judged only infra-tentorial lesions as FLAIR positive (DWI lesion visible on FLAIR) or FLAIR negative (DWI lesion not visible on FLAIR). Additional supra-tentorial lesions were ignored the same as subacute or older FLAIR lesions which did not overlap with acute DWI lesions. Finally, in cases of discrepancy, a consensus rating was performed.The volume of DWI lesions was calculated using a free available software package . Considering the small DWI lesion size the delineation of regions of interest was made manually. For patients with disseminated infra-tentorial lesions more than one region of interest was drawn.Accordingly the region of interest for the unaffected side was defined by mirroring the DWI lesion manually and possibly corrected to avoid areas of leukoaraiosis, contralateral stroke or cerebrospinal fluid.Absolute and relative signal intensity (rSI) was calculated for all lesions on DWI and apparent diffusion coefficient (ADC). The rSI was calculated by dividing the SI in the pathological side by that in the normal side and designated as rDWI and rADC.Statistical analyses were performed with SPSS 20 (IBM) and Clinical Calculator 1 . Medians and interquartile ranges describe the results. The Mann-Whitney-U test was used to assess differences between patient groups. To assess the correlation between time from stroke onset and rDWI, rADC and age we used a linear regression model.Fifty-six data sets were included of which 26 patients had a brainstem stroke (46.4%), 28 patients had a cerebellar stroke (50%) and two patients had both (3.6%). All of our patients exhibited a positive DWI at time of arrival. For baseline characteristics see FLAIR was rated as negative in 11 out of 20 (55%) patients <4.5 hours and in 14 of 36 (38.9%) patients >4.5 hours after onset. A negative FLAIR correctly identified patients within 4.5 hours of symptom onset with a specificity of 61% (95% CI 44–76%), a sensitivity of 55% (95% CI 32–76%), a positive predictive value (PPV) of 44% (95% CI 25–65%) and a negative predictive value (NPV) of 71% (95% CI 52–85%); see FLAIR negative patients had a lower rDWI and higher rADC value than FLAIR positive patients (p<0.05). In a linear regression model we could only show a weak correlation between delay from stroke onset and rDWI values  and no correlation between delay and rADC values .Our study demonstrates the difficulty of estimating lesion age in infra-tentorial stroke. In this population, the DWI-FLAIR-Mismatch does not seem to reliably identify patients within 4.5 hours of symptom onset . Twelve rDWI and rADC seem to evolve parallel to FLAIR, however the time dependency of rDWI was too weak for clinical use within a 24 h period. Corresponding to the observations of Ebinger et al. rADC values in our study did not chronometer stroke onset in a useful manner although it has been shown that ADC values decrease in the first three days of stroke Finally FLAIR-positive patients were younger than FLAIR-negative patients. This observation was already made by Thomalla et al. for supra-tentorial stroke and shows that there are other factors influencing the development of FLAIR changes than time alone This study has several limitations such as the low number of patients in general and the limited number of patients per time window . On average the patients had mild neurological deficits (median NIHSS 3) and small lesions (median 0.26 ml). Therefore this cohort was not representative of patients eligible for thrombolysis and may also explain lower predictive values of FLAIR compared to the cited studies. Furthermore the small DWI lesion volume might limit the accuracy of the quantification of diffusion parameters in some patients.In our study the DWI-FLAIR-Mismatch did not help to reliably identify patients within 4.5 h of symptom onset in acute ischemic infra-tentorial stroke. The importance of this study is in showing that the DWI-FLAIR mismatch in acute ischemic infra-tentorial stroke does not seem to be as helpful in identify patients within 4.5 h of symptom onset as it is in cases of supra-tentorial stroke. Thus, therapeutical decisions based on the DWI-FLAIR mismatch estimation of time cannot be readily recommended in patients with infra-tentorial stroke. This is of special relevance considering currently ongoing MRI based clinical studies examining the effect of thrombolysis in patients with unknown time of stroke onset.On the other hand, and assuming that FLAIR may be a tissue clock, our study could further support the hypothesis that infra-tentorial ischemic stroke may benefit from late endovascular therapy independently from a rigid time window


Characterizing biodiversity in a habitat or in targeted taxonomically or socioeconomically important groups remains a challenge. Standard DNA-based biodiversity identification tools such as DNA barcoding coupled with high-throughput Next-Generation Sequencing (NGS) technologies are rapidly changing the landscape of biodiversity analysis by targeting various habitats and a wide array of organisms. However, effective use of these technological advances requires optimized protocols and benchmarking against traditional tools. Here we investigate the use of commonly used preservative ethanol as a non-destructive and inexpensive source of DNA for NGS biodiversity analysis of benthic macroinvertebrates. We used the preservative ethanol added to field collected organisms (live sorted bulk benthic samples) as a source of community DNA for NGS environmental barcoding. We directly compare this approach with a DNA barcode library generated using Sanger sequencing of all individuals separated from abenthic sample as well as with NGS environmental barcoding of DNA extracted from mixed/homogenized tissue specimens of the same benthic sample. We also evaluate a multiplex PCR strategy, as compared to commonly used single amplicon workflow, using three newly designed primer sets targeting a wide array of benthic macroinvertebrate taxa.Our results indicate the effectiveness of ethanol-based DNA in providing sequence information from 87% of taxa identified individually from mixture as compared to 89% in conventional tissue extracted DNA. Missing taxa in both DNA sources were from species with the lowest abundance  in the benthic mixture. Interestingly, we achieved 100% detection for taxa represented with more than 1% individuals in the mixture in both sources of DNA. Our multiplex amplification regime increased the detection as compared to any single primer set indicating the usefulness of using multiple primer sets in initial amplification of target genes.Although NGS approaches have significantly increased the potential of using DNA information in biodiversity analysis, robust methods are needed to provide reliable data and alleviate sample-processing bottlenecks. Here we coupled non-destructive DNA access and a multiplex PCR approach in NGS environmental barcoding for effective data generation from benthic live-sorted samples collected in bulk and preserved in ethanol. Our study provides a possible solution to sampling and vouchering challenges in using benthic samples through next-generation environmental barcoding and facilitates wider utility of DNA information, especially species-specific DNA barcodes, in ecological and environmental studies and real-world applications such as biomonitoring programs. Next-generation sequencing (NGS) technologies are rapidly increasing the applicability of genomics approaches in biological sciences. Aside from the sheer volume of sequence information obtained from NGS devices, the massively parallelized capacity of these machines is a significant advantage for the analysis of mixtures of DNA fragments. In PCR-based applications of NGS technologies amplicons are generated from target genes, often from multiple template genomes, and are sequenced in parallel without the need for separating target organisms or their DNA through sample sorting or cloning. For exaEnvironmental barcoding seeks toAn important concern in the analysis of environmental samples is obtaining DNA templates from all target organisms in the mixed sample. Methods have been developed to extract and purify DNA from environmental samples such as soil or water. However, for bulk material such as benthos--obtained using kick nets--orpassively sampled arthropods collected in a Malaise trap, DNA extraction often requires homogenizing the biomass from all organisms and then performing a standard DNA extraction protocol on this homogenized slurry. Although this approach has been effective in gaining DNA from organisms in the mixture, it results in loss of all individual specimens, thereby rendering any subsequent analysis on these individuals impossible. Recently, we demonstrated that ethanol, commonly used as a preservative medium for storing specimens, contains DNA of stored organism and that this “free DNA” can be directly used for downstream amplification and sequencing without the need for conventional DNA extraction approaches. AlthougAnother important concern in the use of NGS for analysis of environmental samples is the issue of bias in multi-template PCR amplification. CurrentHere we introduce an enhanced approach for environmental barcoding, which will aid sampling, DNA extraction and PCR steps in biodiversity analysis of benthic macroinvertebrate taxa commonly used for biomonitoring applications. We firstly incorporate a non-destructive sample preparation approach by using preservative media (ethanol) as the source of target DNA (hereafter referred to as ethanol-based DNA) and compare it with a conventional tissue-based DNA extraction (hereafter referred to as tissue-DNA). Secondly, to increase the recovery of species’ DNA barcode sequences in bulk environmental samples and to offset specific primer-binding biases, we introduce a multiplex PCR approach targeting multiple amplicons within the standard cytochrome c oxidase 1 (COI) DNA barcode region. We develop and test three wide-range primer sets for NGS analysis. To show the utility of this approach, we test it in parallel with Sanger sequencing individual specimens from a typical biomonitoring benthic sample containing several groups of macroinvertebrates.Our first analysis aimed at assembling a DNA barcode sequence library from all individuals present in our benthic sample. Using a small (i.e. 2 mm) tissue sample , from each larvae, we were able to obtain a standard COI DNA barcode sequence from 98.7% 148/150) of individuals present in the benthic sample. These Sanger sequenced individuals formed 46 OTUs in a neighbor-joining tree analysis of COI barcodes. When these taxa were identified to lowest annotated taxonomic unit 36.9% (17 OTUs) of them matched DNA barcode sequences of known species and another 50% (23 OTUs) matched a DNA barcode identified at genus level. The remaining 13.1% matched a sequence at family or order levels  from genus Paraleptophlebia representing 8.78% of individuals. All other species had lower than 5% abundance in Sanger sequencing analysis  identified to genus Cricotopus bicinctus, was only detected by one primer set and was represented by a small percentage of 454 sequence reads (see below) in the tissue-DNA analysis. This species had two OTUs in the Sanger sequence library. One of these was missed in both ethanol-based DNA and tissue-DNA analysis  in the environmental sample tested , detection of taxa increased substantially for all two-amplicon combinations Table. FinallyWe combined data obtained from ethanol-based DNA and tissue-DNA to see the effect of using both sources of DNA in detection capability Table. Using DWe also compared different primer sets for their efficiency in detecting species quantitatively. In other words, we simply calculated the percentage of taxa with more than 1% abundance in our benthic mixture that were detected by each primer set Table and in tFurther to our investigation to evaluate taxonomic detection (see above), we performed a series of correlation analyses to understand primer behavior as well as uniformity of results among different comparisons in ethanol-based DNA and tissue-DNA reactions. We used the proportion of reads obtained for each OTU for calculating correlations Figure. Each prA small number of NGS reads (Min 5 and Max 95 in different primer sets and DNA sources) matched sequences of 16 OTUs that were not originally in our assembled Sanger library .Our results from both tissue extracted DNA and ethanol-based DNA suggest the presence of taxa not originally sequenced in our Sanger-based DNA barcode analysis. While two individual larval samples did not produce Sanger DNA barcodes in our analysis, 14 benthic taxa were detected that were not present as individuals in our mixture. Since our analysis was based on a single sampling event using all precautions to avoid possible contamination we can potentially link the presence of residual DNA to carry over through the organisms present in the larval community we sampled. This is in line with earlier observations[Our study only included live field-sorted larval mixtures (a common sampling approach used for aquatic biomonitoring) and needs to be verified in other types of mixed samples such as Malaise traps , pitfall traps (used for soil arthropods) and different types of light traps (used for insects). A somewhat comparable approach for accessing extracellular DNA has been advocated for soil analysis, although it uses a phosphate buffer followed by a DNA extraction protocol.Oligonucleotide primers are an integral factor in PCR-based NGS analysis, yet there has not been much attention to empirical optimization and testing of primers for specific genes commonly used in NGS analysis. Conversely, genes have mainly been selected based on availability of conserved binding sites. It is, The difficulty in large-scale spatiotemporal analysis of biodiversity has resulted in bottlenecks in executing biomonitoring programs and several other types of ecological and environmental investigations. Next geApproaches such as environmental barcoding are relatively new and require additional scrutiny to make them suitable for large-scale studies and real-world applications. Here we show the utility of ethanol-based DNA in simplifying sample preparation and alleviating destructive analysis of ethanol-preserved organisms. This procedure also allows preservation of specimens for further scrutiny. We also introduced a new multiplex PCR approach to neutralize specific primer-binding biases, thereby allowing the recovery of more taxa. We recognize that multiple samplings are required for comprehensive analysis of biota in an ecosystem through NGS. The availability of NGS devices with higher throughput and lower costs per analysis will facilitate generating sample sizes required for sound statistical analysis of NGS results. We note′12.88″N, 79º42′35.61″W). The sample was collected by kick netting for ten transects across the river, 10 m between transects. The sample was live sorted on site and preserved in 95% ethanol at 4°C until processing (approximately 3 months).A larval benthic sample was collected from the Humber River  was then subjected to routine DNA barcoding following standard COI DNA barcoding protocols. We amplWe performed two DNA preparations for NGS analysis. One method involved using ethanol originally used for collecting and preserving benthic sample (see above). For this ethanol-based DNA analysis, 10 ml of the preserved ethanol was transferred to ten 1.5 ml Eppendorf tubes and evaporated at 56°C for 5–6 hours. The dried residue was dissolved in 30 μl of molecular biology grade water and was used as the source of template DNA for PCR (see below).The other approach involved using tissue mixtures from the original benthic sample. A tissue sample from each individual  was pooled in a single tube containing ethanol and the resultant mixed tissue sample was incubated at 56°C for approximately two hours to evaporate residual ethanol. The dried mixture was divided into 10 lysing matrix tubes “A” (about 100 mg each) and homogenized using an MP FastPrep-24 Instrument  at speed 6 for 40 sec. Total DNA of this homogenized slurry was extracted using the Nucleospin tissue kit (Macherey-Nagel Inc.) following the manufacturer’s instructions and eluted in 50 μl of molecular biology grade water.2 (50 mM), 0.5 μl dNTPs mix (10 mM), 0.5 μl forward primer (10 mM), 0.5 μl reverse primer (10 mM), and 0.5 μl Invitrogen’s Platinum Taq polymerase (5 U/μl). The PCR conditions were initiated with heated lid at 95°C for 5 min, followed by a total of 15 cycles of 94°C for 40 sec, 46°C for 1 min, and 72°C for 30 sec, and a final extension at 72°C for 5 min, and hold at 4°C. Amplicons from each sample were pooled and purified using Qiagen’s MiniElute PCR purification columns and eluted in 30 μl molecular biology grade water. The purified amplicons from the first PCR were used as templates in a second PCR with the same amplification condition used in the first PCR with the exception of using 454 fusion-tailed primers in a 30-cycle amplification regime. Eppendorf Mastercycler ep gradient S thermalcyclers were used for all PCRs. A negative control reaction (no DNA template) was included in all experiments. PCR success was checked by agarose gel electrophoresis.Three fragments within the standard COI DNA barcode region were amplified with three newly designed primer sets Table in a twoAmplicons were quantified by flourometer and normalized to the same concentration (100 ng/μl). The amplicon libraries were sequenced on a 454 Genome Sequencer FLX System (Roche Diagnostics GmbH) following the amplicon sequencing protocol and using GS Titanium chemistry. Amplicons of each sample were bi-directionally sequenced in 1/16 of a full sequencing run (70 × 75 picotiter plate). Details of the 454 pyrosequencing run are available by request from the corresponding author. All sequences have been submitted to GenBank (Accession Numbers KC263198 - KC282326).Pyrosequencing reads were first filtered by quality using ‘Filter FASTQ’ on Galaxy-18 ensurA total of 21932 sequences were generated in one lane, and 23483 in the other using DNA templates from ethanol-based DNA and tissue-DNA, respectively. After quality filtering, there were 17308 (~79%) reads and 20240 (~86%) for each lane, respectively. The Sanger reference library contained a total of 148 sequences, but after clustering with USEARCH[The authors declare that they have no competing interests.MH conceived the idea, designed the experiments, participated in data analysis and visualization, and wrote the manuscript. JLS collected the benthic sample, performed molecular biology analysis, participated in data analysis and edited the manuscript. SS participated in experimental design, performed NGS DNA sequencing, participated in data analysis, and edited the manuscript. SVK performed bioinformatics analyses of DNA sequence data. All authors read and approved the final manuscript.Table S1. Taxa identified from sequences obtained in environmental barcoding analysis but absent in Sanger sequenced DNA barcode library constructed from individuals in the benthic sample analysed.Click here for file


E. coli for use as antigens in enzyme-linked immunoassay (ELISA). Human serum/plasma samples from both Côte d'Ivoire and Germany showed frequent seropositivity for the four viruses. Antibody pre-adsorption-based ELISA excluded the possibility that reactivities resulted from binding to known human polyomaviruses. Together, these results support the existence of additional polyomaviruses circulating within the human population that are genetically and serologically related to existing chimpanzee polyomaviruses.Polyomaviruses are a family of small non-enveloped DNA viruses that encode oncogenes and have been associated, to greater or lesser extent, with human disease and cancer. Currently, twelve polyomaviruses are known to circulate within the human population. To further examine the diversity of human polyomaviruses, we have utilized a combinatorial approach comprised of initial degenerate primer-based PCR identification and phylogenetic analysis of nonhuman primate (NHP) polyomavirus species, followed by polyomavirus-specific serological analysis of human sera. Using this approach we identified twenty novel NHP polyomaviruses: nine in great apes , five in Old World monkeys and six in New World monkeys. Phylogenetic analysis indicated that only four of the nine chimpanzee polyomaviruses (six novel and three previously identified) had known close human counterparts. To determine whether the remaining chimpanzee polyomaviruses had potential human counterparts, the major viral capsid proteins (VP1) of four chimpanzee polyomaviruses were expressed in  Polyomaviruses are able to cause severe disease in immunocompromised individuals. The discovery of Merkel cell polyomavirus and its association with Merkel cell carcinoma has increased interest in these viruses, resulting in the identification of several novel human polyomaviruses in recent years. The existence of one of these recently identified viruses, human polyomavirus 9 (HPyV9), had been predicted nearly 30 years prior due to the ability of human sera to neutralize infection of an African green monkey polyomavirus . HPyV9 and LPyV are now known to be antigenically and phylogenetically closely related. We hypothesized that nonhuman primate (NHP) polyomaviruses, in particular those of the closely related chimpanzee, may serve as genetic and immunological predictors for the existence of yet unknown human polyomaviruses. In the present study, we discovered 20 novel NHP polyomaviruses, six of which were isolated from chimpanzees. Of the 9 chimpanzee polyomaviruses now known, 5 do not presently have a closely related human counterpart. Serologic reactivity against these novel chimpanzee viruses was observed in humans from European and African populations. From these data we predict that additional human polyomaviruses exist which are genetically and serologically related to the novel chimpanzee polyomaviruses. Over recent years the rate of identification of new viruses within human and animal populations has increased exponentially. Since 2007, more than 20 novel animal polyomaviruses have been discovered, and 12 genetically distinct human polyomaviruses are currently known. Polyomaviruses are non-enveloped viruses with a circular double-stranded DNA genome of approximately 5,000 base-pairs. All polyomaviruses encode proteins  that have potential oncogenic capacity. However, transformation by these viruses is influenced by the individual virus type, as well as by the animal species undergoing infection Trichodysplasia spinulosa, and has been designated Trichodysplasia spinulosa-associated polyomavirus (TSPyV) Infection with human polyomaviruses usually occurs in childhood or during adolescence without severe acute symptoms and results in lifelong persistence with no apparent disease. However, polyomavirus reactivation can cause serious disease in immunocompromised patients Human sera have been observed to serologically cross-react with polyomaviruses of nonhuman primates (NHPs) that have closely related human counterparts. For example, human sera reactive against BKPyV and JCPyV are cross-reactive with the closely related Old World monkey (OWM) polyomavirus simian virus 40 (SV40), and sera reactive against human polyomavirus 9 (HPyV9) have been shown to cross-react with the closely related OWM lymphotropic polyomavirus (LPyV) In the present study, we have performed a comprehensive search for unknown NHP polyomaviruses by using degenerate primer-based PCR. Identified novel polyomaviruses were then sequenced to determine phylogenetic position within the polyomavirus family, followed by the use of serological assays of human sera to assess for the presence of reactivity against these newly identified NHP polyomaviruses. Our main focus was placed on chimpanzees, since they are our closest phylogenetic relatives and might therefore harbor polyomaviruses closely related to those found in humans Degenerate primer PCR-based analysis was performed to ascertain the diversity of polyomaviruses in wild NHPs. For this analysis, blood, tissue and fecal samples (n = 792) collected from live or deceased great apes, OWMs, NWMs and prosimians  co-infection was observed. Prosimian (strepsirrhine) polyomaviruses were not detected, which may be a reflection of the small (n = 20) sample size.We discovered 9 polyomaviruses in great ape species . These viruses were further characterized in the present study and are listed in Pan troglodytes verus) and Eastern chimpanzee (Pan troglodytes schweinfurthii)], three from OWMs  and three from NWMs . Repeated amplification attempts from the remaining ten polyomaviruses were unsuccessful, most likely due to low genome copy numbers. The sequence information of these ten complete genomes and ten partial VP1 sequences has been deposited in the GenBank database. The accession numbers are listed in To characterize the complete genomes of the nine great ape and 11 monkey polyomaviruses, specific nested primers in an inverse orientation were used to target the partial VP1 sequences obtained from the initial degenerate primer PCR for long-distance PCR amplification of the remaining virus genome. Complete genome sequences of ten polyomaviruses were amplified and sequenced: four from chimpanzees  and two novel viruses from cercopithecids  which were associated to HPyV9 and LPyV.Clade (b) consisted of three novel chimpanzee viruses [PtrovPyV5 and 6 from Western chimpanzees (Ateles paniscus)] and the human-infecting TSPyV.Clade (c) included two orangutan viruses (PpygPyV1 and OraPyV1), a NWM polyomavirus [ApanPyV1 from red-faced spider monkey (Pan troglodytes troglodytes) and CeryPyV1 from red-eared guenon (Cercopithecus erythrotis)] which formed a cluster with JCPyV, BKPyV, SV40 (from rhesus monkey) and SA12 (from baboon).Clade (d) comprised a chimpanzee and a monkey polyomavirus  and the chimpanzee virus ChPyV.Clade (f) included two colobus viruses , as well as to some bat polyomaviruses.In clade (g) finally, GbergPyV1 from Eastern lowland gorilla (Budgerigar fledgling disease virus (BFDV)] E. coli are known to form pentameric capsomer structures 450 values were plotted against each other, and correlation analysis was performed to check for statistical evidence of cross-reaction. Rank correlation showed only slight to moderate correlations (0.178 to 0.62), and for none of the antigen pairs was a correlation >0.5 measured for any serum/plasma panel  with no close counterparts in humans were selected for use in indirect ELISA [clades (b), (e) and (f) in ma panel , indicatTo assess possible antigenic cross-reactivity between the four chimpanzee polyomaviruses and known human polyomaviruses, competitive inhibition of seroreactivity was tested. Serum and plasma samples (n = 5–7) reactive against VP1 of a particular chimpanzee polyomavirus  were tested by ELISA using the respective chimpanzee polyomavirus VP1 as the antigen. Prior to use in the assay, all sera were pre-adsorbed with soluble VP1 antigen from BKPyV, HPyV9, JCPyV, MCPyV or TSPyV. Incubation with the soluble homologous chimpanzee polyomavirus VP1, and soluble APyV VP1 served as positive and negative controls, respectively. Pre-adsorption with the homologous chimpanzee polyomavirus antigens reduced the ELISA reactivity by approximately 80% or more in all cases , and preIn the present study, multiple, hitherto unknown, highly diverse polyomaviruses were detected in great apes and monkeys. These viruses were localized mainly to lymphoid organs, lungs and intestinal tissue . In phylIvorian plasma samples consistently showed higher levels of VP1 reactivity compared to samples from German individuals . One posUsing degenerate PyV PCR in NHPs, we found a high prevalence of polyomaviruses in spleen, lymph node and intestine samples. This observation led us to test comparable human tissue samples for the presence of human counterparts of ChPyV, PtrovPyV3, PtrovPyV4 and PtrosPyV2. Surprisingly, human spleen and lymph node samples were largely PCR negative. However, we did identify a novel human polyomavirus in liver and intestine samples that showed no close genetic relationship to any of the known polyomaviruses  Identifying the human polyomaviruses predicted in this study will likely be no easy task. Their lack of detection in the face of the massive screening effort performed by the scientific community over recent years already testifies that these viruses are not easy targets. The underlying reason could be technical. For example, although efficient generic PCR methods are available, there is no guarantee that the systems in use can amplify these elusive human polyomaviruses. Another explanation may also lie in the biology of these polyomaviruses. For example, their tissue tropism may hamper detection if the corresponding tissue type is not commonly used for polyomavirus detection and/or is difficult to obtain. Therefore, the gain of molecular information about these human polyomaviruses may require the use of alternative detection methods, e.g. PCR systems specifically designed to target meaningful subsets of polyomaviruses, and/or targeting of body compartments that have not commonly been analyzed. Importantly, the results from the present study can be used to develop targeted nucleic-acid based detection methods for their identification in the future. Clearly, the limitation of the serological approach is the inability to discern single from multiple polyomaviruses within a phylogenetically related group. However, this strategy does indicate the presence of at least one, if not multiple, human polyomaviruses closely related to ChPyV, PtrovPyV3 and PtrovPyV4 (and possibly PtrosPyV2), circulating at substantial levels within the human population. The specific identity of the human correlate polyomaviruses and the disease implications associated with infection by these viruses remain to be determined.General permission for sample collection from deceased wild primates was obtained from the authorities of national parks of each country. Deceased animals were found during the course of a long term project focused on the behavior and infectious disease in wild-living nonhuman primates, mainly in Côte d'Ivoire. Most animals included in this study had died due to anthrax and respiratory diseases http://www.panafricanprimates.org/.All samples from sanctuary-living wild-born great apes were collected during routine health checks by the sanctuary on-site veterinarian. No animal was sampled specifically for this study, and diagnostics were performed at RKI at request by the respective sanctuary. Therefore, no approval from our institutional committee was needed. All samples were collected according to the guidelines: PASA 2004. Pan African Sanctuary Alliance Veterinary Manual. Available at For animals living in zoological gardens and primate facilities, samples were obtained during routine health checks by the zoo and facility veterinarians. No animal was sampled specifically for the present study. Therefore, no approval from our institutional committee was needed. All samples were collected according to the guidelines laid down by Fowler and Miller For all samples, importations occurred according to German veterinary regulations for import of organic materials. Tissue and blood samples were exported with the appropriate CITES permissions from the respective country and Germany.Plasma samples of human volunteers in Côte d'Ivoire were sampled under the permission of the ministry of health of Côte d'Ivoire and the Institute Pasteur Côte d'Ivoire. Written informed consent was obtained from all participants of the study. The study was performed in cooperation with local health professionals. The aim of the study  was explained to the local population during various educational campaigns. German serum samples were anonymously collected ‘residual materials’, and the collection was approved by the ethics committee of the Charité - Universitätsmedizin Berlin. All samples were collected according to the declaration of Helsinki.Plasma samples (n = 115) from Côte d'Ivoire were collected from 57 women and 58 men,  participating in a broad study to investigate zoonotic diseases at the human – wildlife interface in Côte d'Ivoire. Serum samples (n = 111) were collected from healthy German adults  at the Charité University Hospital, Berlin, Germany.A total of 792 blood, fecal and tissue samples were collected from live or deceased individuals of 44 primate species  Two generic PCRs for polyomavirus identification Complete/partial VP1, VP2 and LTag protein coding sequences generated for this study were translated into amino acids using SeaView The three sets of sequences were aligned with SeaView using Muscle Best-fit models of amino acid evolution were determined using ProtTest v3 Phylogenetic analyses were then performed under the given models of amino acid evolution in ML and Bayesian frameworks. ML analyses were performed with PhyML v3.0 http://tree.bio.ed.ac.uk/software/tracer/). Visual confirmation that the stationary distribution had effectively been reached was obtained for both runs (a plateau was observed). In addition, model parameters apparently converged to undistinguishable distributions for both runs. Finally, combined effective sample sizes (ESS) were above 200 for all parameters. Trees sampled after a visually conservative burn-in of 1,000,000 generations were assembled into a single file using LogCombiner v1.7.1 before the information that this tree sample  contained was summarized onto the maximum clade credibility (MCC) tree with TreeAnnotator v1.7.4. Posterior probabilities (pp) were taken as branch support values.Bayesian analyses were performed using BEAST v1.7.4 and the associated suite of softwares http://tree.bio.ed.ac.uk/software/figtree/).All trees presented in this article were made up with FigTree v1.3.1  and expressed in IgG ELISAs, including use of APyV VP1 as a negative control to exclude non-specific seroreactivity (due to binding of antibodies to conserved VP1 epitopes or due to unspecific binding), estimation of cut-off values, calculation of the correlation of antibody reactivity using the Spearman rank correlation test, and adsorption assays with soluble VP1 capsomers were performed essentially as described The database was established in Excel for Windows before being transferred into Stata  for statistical analyses. Absorbance values and prevalence of the individual viruses and the effect of age and gender on absorbance values were analyzed using regression models and Fischer exact test.Pan troglodytes verus polyomavirus, PtrovPyV) and listed in Pan troglodytes verus, Pan troglodytes schweinfurthii and Gorilla gorilla gorilla, published in our earlier study For the purpose of this paper, tentative names and abbreviations for the novel NHP polyomaviruses were derived from species and subspecies name of the host in which the virus was detected Click here for additional data file.Figure S2Sequence homology between NCCRs. The NCCRs of (a) MfasPyV1 and PtrovPyV5 and (b) PtrosPyV2 and PtrovPyV5 were aligned. Identical nucleic acids are marked by vertical lines, gaps by hyphens.(TIF)Click here for additional data file.Figure S3Alignment of the primary sequence of large T antigens and their functional motifs from novel NHP polyomaviruses. The LTag proteins of all novel NHP polyomaviruses (with complete genomes amplified and sequenced) were aligned with the LTAg of SV40. Functional motifs are highlighted with different colors. The color code is shown below the alignment.(TIF)Click here for additional data file.Figure S4Location of functional motifs in large T antigen. LTag is represented by an open bar.(TIF)Click here for additional data file.Figure S5Amino acid sequence identity between the host range domain of SV40 large T antigen and the C-terminal region of CeryPyV1 large T antigen. Identical amino acids are highlighted in yellow.(TIF)Click here for additional data file.Figure S6Bayesian chronogram deduced from the analysis of a 90 amino acid alignment of VP2 sequences. Polyomaviruses were identified in humans (red), apes (blue), other primates (green), and other mammals and birds (black). Novel polyomaviruses identified in this study are marked with a star. Viruses from which VP1 was used in serological assays are highlighted by colored rectangles. Clades ‘a’ and ‘g’ (highlighted in (TIF)Click here for additional data file.Figure S7Bayesian chronogram deduced from the analysis of a 443 amino acid alignment of large T sequences. Polyomaviruses were identified in humans (red), apes (blue), other primates (green), and other mammals and birds (black). Novel polyomaviruses identified in this study are marked with a star. Viruses from which VP1 was used in serological assays are highlighted by colored rectangles. Clade ‘g’ (highlighted in (TIF)Click here for additional data file.Figure S8Multiple seroreactivities against chimpanzee polyomaviruses in humans. German sera (A) and Ivorian plasma samples (B) were tested for seroreactivity against ChPyV, PtrovPyV3, PtrovPyV4 and PtrovPyV10. The graph displays percentages of single and multiple reactivities.(TIF)Click here for additional data file.Figure S9Age-stratified reactivity of human sera to VP1 proteins of chimpanzees and human polyomaviruses. Antibody reactivity against 2 human polyomaviruses (HPyV9 and JCPyV) and 4 chimpanzee polyomaviruses  of sera from German (n = 111) and of plasma samples from Ivorian subjects (n = 115). Samples were analysed for seroreactivity with a capsomer-based IgG ELISA using the VP1 major capsid protein of the above polyomaviruses as antigens. Absorbance spread measurements are shown as blue dots, representing the German (left) and Ivorian panels (right), respectively. The COV is shown as dashed line Click here for additional data file.Table S1Primate species and tissues tested with generic polyomavirus PCR.(DOC)Click here for additional data file.Table S2Primers used for amplification of nonhuman primate polyomaviruses.(DOC)Click here for additional data file.Table S3Known and novel polyomaviruses used in phylogenetic analysis.(DOC)Click here for additional data file.Table S4Genomes and encoded proteins of the novel nonhuman primate polyomaviruses.(DOC)Click here for additional data file.Table S5Putative functional motifs in the large T-antigens of the novel NHP polyomaviruses.(DOCX)Click here for additional data file.Table S6Correlation of seroreactivities against VP1 antigens of polyomaviruses.(DOC)Click here for additional data file.Text S1LT-ag binding motifs in NCCR of novel NHP polyomaviruses.(DOCX)Click here for additional data file.Text S2Motifs in large T antigens of novel NHP polyomaviruse.(DOCX)Click here for additional data file.