Asarum kooyanum Makino var. nipponicum Kitam.

原著和名: カンアフヒ科名: ウマノスズクサ科 = Aristolochiaceae採集地: 千葉県 市原市 奈良 (上総 市原市 奈良)採集日: 1990/3/24採集者: 萩庭丈壽整理番号: JH038993国立科学博物館整理番号: TNS-VS-98899

Additional file 1: Table S1. of Stool microbiota composition is associated with the prospective risk of Plasmodium falciparum infection

Taxonomic composition of Dirichlet components DC1 and DC2. Table S2. Fit of DMM modeling for various values of K (the number of Dirichlet components). Best fit is highlighted in red. Table S3. Taxonomic composition of Dirichlet components CC1 through CC9. Table S4. Distribution of samples from the four cohorts (Mali, HMP, Malawi, and MSD) in the 9 Dirichlet components (CC1 through CC9). Table S5. Fit of DMM modeling for various values of K (the number of Dirichlet components) for P. falciparum infection status analysis. Best fit is highlighted in red. Table S6. Taxonomic composition of Dirichlet components PP1, PP2, PN1, and PN2. Table S7. Taxonomic composition of Dirichlet components FM1 and FM2. Table S8. Cox model of DMM Component: Time to Infection. Figure S1. Increase in microbial taxa diversity with age in the Malian cohort. For each stool microbiota sample, the alpha diversity on the y-axis was plotted against the individual’s age in years (x-axis). The blue lines are the linear model fits and all of them have positive slope (P < 10−9). Four different alpha diversity measures are reported (Sobs – the observed #OTUs, Chao estimate, Ace estimate, and Shannon diversity). Similar trends are observed when the datasets are analyzed separately by gender. Figure S2. Evaluation of model fit of Dirichlet mixtures to the Mali dataset. Model fit is evaluated using the Laplace approximation to the model evidence for varying values of K (the number of Dirichlet components). For these data, K = 2 results in the best fit. (ZIP 595 kb

Proposed model by which children remain asymptomatic and control parasitemia upon <i>P. falciparum</i> re-exposure.

<p>In children without prior or recent malaria exposure, <i>P. falciparum</i> infection induces a robust pro-inflammatory cytokine and chemokine response (e.g. IL-1β, IL-6, IL-8) whereas effector mechanisms that mediate parasite clearance (phagocytosis, phagolysosome activation, antigen presentation, T cell co-stimulation and IFN-<b>γ</b> production by CD4⁺ T cells) are not readily inducible, leaving children susceptible to fever and other systemic symptoms of malaria as well as poorly controlled parasite replication. In contrast, febrile malaria induces an exposure-dependent regulatory state (shown here) whereby re-exposure to <i>P. falciparum</i> results in reduced production of pro-inflammatory cytokines and chemokines and enhanced expression of regulatory cytokines (e.g. IL-10 production by CD4⁺ T cells) and pathways involved in phagocytosis-mediated clearance of infected red blood cells and activation of adaptive immunity, thus enabling children to remain asymptomatic and control parasite replication in the face of ongoing <i>P. falciparum</i> exposure. In addition, <i>P. falciparum</i>-specific IgG levels are low in children who have not been recently exposed to malaria, but transiently increase in response to <i>P. falciparum</i> infection <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004079#ppat.1004079-Weiss1" target="_blank">[44]</a>, <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004079#ppat.1004079-Crompton2" target="_blank">[45]</a>, further enhancing exposure-dependent parasite clearance through opsonization and phagocytosis of infected erythrocytes. Arrows indicate the direction of expression observed in this study of molecules at the mRNA and/or protein levels induced by <i>P. falciparum</i> re-exposure after febrile malaria relative to responses induced by <i>P. falciparum</i> exposure at the healthy baseline. Molecules are color-coded by biological function.</p

<i>P. falciparum</i>-inducible IL-10 is mainly produced by CD4⁺CD25⁺Foxp3⁻ T cells that co-produce IFNγ and TNF.

<p>(<b>A</b>) PBMCs from the healthy baseline (HB), 7 days after malaria (d7), and at the healthy baseline at the end of the subsequent dry-season (HB′) were stimulated for 18 h with iRBC lysate and assayed for the production of IL-10, IFNγ and TNF by intra-cellular FACS. Results are shown as the ratio of live CD3⁺ CD4⁺ antigen-experienced cells (CD45RO⁺ CD27⁺, CD45RO⁺ CD27⁻, and CD45RO⁻ CD27⁻) producing IL-10, IFN-γ or TNF in response to stimulation with iRBC lysate vs. uninfected RBC (uRBC) lysate (n = 16, 13 paired samples). (<b>B</b>) Overlay of IL-10-producing cells (red) among all live cells (gray) in a CD3 vs. CD4 dot plot (top) (n = 14), and IL-10-producing CD4⁺ T cells (red) with all CD4⁺ T cells (gray) in CD25 vs. FoxP3 dot plot (bottom) (n = 9; representative subject shown). (<b>C</b>) Using SPICE analysis, cytokine-producing CD4⁺ T cells were divided into 7 distinct subpopulations producing any combination of IL-10, IFNγ and TNF (n = 16). (<b>D</b>) Pie chart representation of the combination of cytokines produced by CD4⁺ T cells after iRBC stimulation for 3 representative donors 7 days after malaria (d7). The black arcs indicate the IL-10-producing CD4⁺ T cells. (<b>E</b>) Representative FACS plots of live CD3⁺ CD4⁺ antigen-experienced cells producing IL-10, IFNγ and TNF after iRBC stimulation of PBMCs collected at the healthy baseline (HB), 7 days after malaria (d7) and at the healthy baseline at the end of the subsequent dry-season (HB′). (<b>F</b>) CD4⁺ T cells were isolated from PBMCs which had been collected from children 7 days after malaria and were then stimulated for 18 h with iRBC or uRBC lysate in the absence (CD4⁺T d7) or presence of non-CD4⁺T cells isolated from PBMCs of the same individuals collected at either the healthy baseline (CD4⁺T d7 + nonCD4⁺T HB) or 7 days after malaria (CD4⁺T d7 + nonCD4⁺T d7) (n = 8 paired samples). (<b>G</b>) PBMCs collected from children 7 days after malaria were stimulated for 18 h with iRBC lysate and assayed for the production of IL-10 in the presence (αMHC-II) or absence (isotype) of antibodies specific for HLA-DR, -DQ and -DP (n = 8). ns, not significant (<i>P</i>≥0.05), <i>P</i> values determined by a linear mixed model for repeated measures ANOVA with Tukey HSD post hoc tests (A) and permutation re-sampling tests (F, G). Data are shown as the means ± s.d.</p

A molecular pattern of restrained inflammation and enhanced anti-parasite effector function upon <i>P. falciparum</i> re-exposure.

<p>(<b>A</b>) PBMCs were collected from 34 healthy children with blood smears negative for <i>P. falciparum</i> infection before the malaria season (HB) and 7 days after treatment of their first febrile malaria episode of the ensuing malaria season when malaria symptoms had resolved (d7). RNA was extracted from PBMCs immediately after thawing and hybridized onto Affymetrix GeneChip Human 1.0 ST arrays. RNA from all 68 PBMC samples was of sufficient quantity and quality for microarray analysis. Nine of 68 samples did not pass the microarray quality assessment and were removed from further analysis (see Supplemental <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004079#ppat-1004079-g001" target="_blank">Figure 1A</a>) such that 25 children with paired RNA samples at the healthy baseline and 7 days after malaria were analyzed. The heat map shows <i>ex vivo</i> RMA-normalized log₂ ratios (d7/HB) of differentially expressed genes (rows) for each child (columns). Genes are grouped and color-coded by function as indicated. (<b>B</b>) PBMCs analyzed by FACS for B cells (CD19⁺), T cells (CD3⁺), CD3⁺CD4⁺ T cells, CD3⁺CD8⁺ T cells, and monocytes (CD14⁺) at the healthy baseline and after malaria. (n = 34 children; except CD14⁺ monocytes, n = 30). (<b>C</b>) Ratio of monocyte percentage (d7/HB) versus the ratio of the expression level of monocyte-derived pro-inflammatory cytokines and chemokines (d7/HB). Each point represents an individual subject (n = 21 children with paired samples). (<b>D</b>) RNA was extracted from PBMCs of the same 34 children after 18 h of <i>in vitro</i> stimulation with <i>P. falciparum</i>-infected red blood cell (iRBC) lysate. After stimulation with iRBC lysate, 22 of the 34 children had RNA samples from both time points of sufficient quantity and quality for microarray analysis and also passed the microarray quality assessment. The heat map shows RMA-normalized log₂ ratios (d7/HB) of differentially expressed genes (rows) for each child (columns) in response to <i>in vitro</i> iRBC lysate stimulation. Genes are grouped and color-coded by function as indicated. (<b>E</b>) q-RT-PCR confirmation of the microarray data. The data represent the results of one experiment with 6 genes (<i>IL1B</i>, <i>IL6</i>, <i>IL10</i>, <i>TGFB1</i>, <i>TLR2</i>, <i>CXCL5</i>) from 17 subjects at two time points (d7 and HB) from both the <i>ex vivo</i> unstimulated and <i>in vitro</i> iRBC-stimulated datasets. Each symbol represents a single gene at a given time point. PCR expression computed as antilog₂ –dCT. <i>n</i> = 497 XY pairs. (<b>F</b>) q-RT-PCR expression of genes encoding the pro-inflammatory cytokines IL1-β and IL-6 and the anti-inflammatory cytokine TGF-β in PBMCs of children (n = 17) collected at the healthy baseline (HB) and after resolution of febrile malaria (d7), either directly <i>ex vivo</i> (unstimulated) or after <i>in vitro</i> stimulation with iRBCs for 18 h. ns, not significant (<i>P</i>≥0.05), <i>P</i> values determined by the paired <i>t</i>test (B), Pearson's (C), Spearman's (E) or paired Wilcoxon rank sum test (F). Data are shown as the means ± s.d. (B) or means ± s.e.m. (F).</p

Effect of baseline <i>Schistosoma haematobium</i> mono-infection, <i>Plasmodium falciparum</i> mono-infection, and co-infection on first or only malaria episode (with anemia interaction term)^a.

<p>Abbreviations: CL, confidence limit; HR, hazard ratio; HbAS, sickle cell trait.</p>a<p>Risk of first or only malaria episode was adjusted for age, distance from home to river, sickle cell trait, anemia status at baseline, residence in the cluster of high <i>S. haematobium</i> transmission, and roof type in the classic Cox proportional hazards model with inclusion of interaction terms between anemia status and the two covariates with <i>S. haematobium</i> infection (anemia*co-infection and anemia*<i>S. haematobium</i> mono-infection).</p><p>Effect of baseline <i>Schistosoma haematobium</i> mono-infection, <i>Plasmodium falciparum</i> mono-infection, and co-infection on first or only malaria episode (with anemia interaction term)^{<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003154#nt109" target="_blank">a</a>}.</p

Kaplan-Meier plots of risk of <i>P. falciparum</i> infection or febrile malaria.

<p>A) Time to first PCR-confirmed <i>P. falciparum</i> blood-stage infection by <i>S. haematobium</i> (Sh) infection status at enrollment. Data shown is only for individuals who were PCR-negative for <i>P. falciparum</i> at enrollment. B) Time to first febrile malaria episode (defined as fever of ≥37.5°C and asexual parasite density ≥2500 parasites/µl on blood smear) by <i>P. falciparum</i> (Pf) and <i>S. haematobium</i> (Sh) infection status at enrollment. C) Time to first febrile malaria episode by <i>S. haematobium</i> (Sh) infection status and anemia status at enrollment. (−) negative status; (+) positive status. <i>P</i> values for log-rank analyses (all groups) are shown. Blue shading indicates time period during which praziquantel was given to all individuals who were determined to be infected with <i>S. haematobium</i> at enrollment.</p

Multiple linear regression model of parasite density at the first febrile malaria episode by different parasite density thresholds^a.

<p>Abbreviations: CL, confidence limit; HbAS, sickle cell trait; NA = not assessed due to lack of individuals with heavy <i>S. haematobium</i> mono-infection in analysis.</p>a<p>Effect of infection status at enrollment on parasite density in log(parasites/µl) using a general linear model with adjustments for age, distance from home to clinic, sickle cell trait, baseline anemia status, and residence in the cluster of high <i>S. haematobium</i> transmission.</p>b<p>1–9 eggs/10 mL urine.</p>c<p>≥10 eggs/10 ml urine.</p><p>Multiple linear regression model of parasite density at the first febrile malaria episode by different parasite density thresholds^{<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003154#nt111" target="_blank">a</a>}.</p

Study participants and risk analysis flow chart.

<p>Study participants and risk analysis flow chart.</p

Spatial distribution of <i>S. haematobium</i> and <i>P. falciparum</i> infections in Kalifabougou, Mali at enrollment (May 2011).

<p>Shapes indicate infected and uninfected cases as noted. Large colored circles show significant, unadjusted clusters: green circle = cluster of co-infected cases in May 2011 (27 cases, n = 158, relative risk [RR] = 6.51, <i>P</i><0.0001, Bernoulli model); red circles = clusters of <i>P. falciparum</i> infections in May 2011 (cluster 1: 35 cases, n = 41, RR = 1.90, <i>P</i><0.001; cluster 2: 12 cases, n = 12, RR = 2.15, <i>P</i> = 0.04, Bernoulli model). Map data: Landsat image obtained from <a href="http://glovis.usgs.gov" target="_blank">glovis.usgs.gov</a> (latitude: 12.952, longitude: −8.173, imagery date: March 2011).</p