EMBO/SourceData huggingface dataset:
Figure 2 Total IgG ELISA titers expressed as area under the curve (AUC) against homologous Cal/7/9 virus of pre-immune and pre-challenge sera of individual animals of the indicated vaccine groups (AAV-HA, -cHA, -GFP, WIV n = 18, AAV-NP n = 11). Background reactivity of pooled AAV-GFP pre-challenge serum is shown as dashed line. ELISAs were performed in technical duplicates.  IgA ELISA titers in post-challenge lung homogenates against Cal/7/9 of individual mice of the indicated vaccine groups (AAV-HA, -cHA, -GFP, -NP, WIV n = 11). of the Cal/7/9 (blue symbols) and PR8 low dose (red symbols) challenge groups. ELISAs were performed in technical duplicates.
Figure 3 A Immunoblot analysis of purified H1N1 viruses A/California/7/2009 (Cal/7/9), A/Brevig Mission/1/1918 (BM/1/1918), A/Puerto Rico/8/1934 (PR8) or A/Brisbane/59/2007 (Bris/59/7) separated under reducing and denaturing conditions. Uncleaved HA0 and cleavage products HA1 and HA2 were detected with pooled pre-challenge sera (AAV-HA, -cHA, -GFP , WIV n = 18, AAV-NP n = 11) as indicated (n = 3). C to F Binding of C179 (C), or antibodies present in AAV-HA (D), AAV-cHA (E) or WIV (F) pooled pre-challenge sera (n = 18 mice per group) to Cal/7/9 or PR8 virus after incubation of the virions at pH = 7.2, 5.8, 5.4, 5.0, 4.4 or 4.4+DTT to induce conformational changes in HA or remove the HA1 subdomain. Mean ± SD (n = 3, in technical triplicates). Statistical significance between pH = 7.2 and other conditions was determined using Kruskal-Wallis test with Dunn's multiple comparison testing (*p<0.05, **p<0.01).
Figure 4 A and B Influenza virus specific activation of the murine FcγRI, FcγRII, FcγRIII and FcγRIV by antibodies in pooled pre-challenge sera (AAV-HA, -cHA, -GFP, WIV n = 18, AAV-NP n = 11 mice per group). MDCKII cells were infected with Cal/7/9 (A) or PR8 (B) before mouse serum and FcγR-expressing reporter cells were added. Influenza specific Fc-FcγR interaction induces the production of IL-2 in the FcγR-expressing reporter cell, which was measured by anti-IL2 ELISA (n = 3, technical duplicates). Mean ± SE.  C HA-specific activation of FcγR by AAV-HA, AAV-cHA or WIV pooled pre-challenge sera (n = 18 mice per group). MDCKII cells were transfected with wildtype HA (pAAV-HA) or a stalk-only HA (pAAV-mHL1) before mouse serum and FcγR-I-expressing reporter cells were added (n = 2, technical duplicates). Mean ± SE.
Figure 5 A to F Mice were vaccinated three times with AAV-vectors or two times with WIV and then challenged with a lethal dose of homologous influenza virus (Cal/7/9) (A, B; n = 5) or two different lethal doses of the heterologous PR8 strain (C, D; n = 6 and E, F; n = 7). Survival was monitored over a 14-day period and is depicted as Kaplan-Meier plot (A, C, E). Weight loss was determined during the 14-day period, which is shown in relation to the weight at day 0 (B, D, F). Mean ± SE. Statistical significance between negative control group (AAV-GFP) or WIV group (E) and each vaccine group was determined using Log-Rank (Mantel-Cox) test (*p<0.05, **p<0.01).
Figure 6 B Cal/7/9-specific serum antibody titers in individual sera at indicated time points. Black lines: individual animals, red lines: mean titer. Statistical significance between pre-immune and immune sera was determined using Friedman test with Dunn's multiple comparison testing (*p<0.05, **p<0.01). The lower table indicates Cal/7/9-specific MN50 and HAI mean titers. Assays were performed in technical duplicates.  C to E Clinical score (C), body temperature (D), and relative weight (E) during challenge period. Statistical significance between pre-immune and immune sera was determined using Friedman test with Dunn's multiple comparison testing (AAV-HA ##p<0.01; AAV-cHA §§p<0.01; AAV-GFP $p<0.05; $$p<0.01; QIV *p<0.05;). Mean ± SD  F Virus titers in nasal turbinates (NT), trachea or lung homogenates. Statistical significance between AAV-GFP and vaccine groups was determined using Kruskal-Wallis test with Dunn's multiple comparison testing (*p<0.05). Lines indicate the GMT. Assays were performed in technical duplicates.  G and H IHC staining of submucosal glands (SMG) (G) or bronchi (H) with an anti-H1N1 polyclonal antibody (bar: 100 µm; red: influenza antigen (neufuchsin); blue: nuclei (haematoxylin)).  I and J H&E stained histological sections of bronchi (I) and lung parenchyma with alveolar epithelial cells (AEC, J). Arrowheads: areas of suppurative bronchitis/bronchiolitis; arrows: interstitial pneumonia, necrosis of AEC (bar: (I) 100 µm; (J) 50 µm).
Figure 1(B) The concentration-effect relationships of PARP1 inhibition by thioparib, talazoparib, and olaparib, as assayed by histone-based ELISA. Data are obtained from three biological replicates and depicted as mean ± SEM. (C) Concentration-dependent increase in PARP1-DNA binding by three PARP inhibitors using DSB FA assays. FA was measured 60 min after adding NAD+, and the ΔFA values represent the changes in PARP1-DNA binding. Data from four biological replicates are presented as mean ± SEM. ((F) and (G) Effects of thioparib on BRCA1-deficient MDA-MB-436 (F) and BRCA2-deficient Capan-1 (G) xenografts. Mice bearing MDA-MB-436 tumors were dosed orally with 10 mg/kg thioparib, 100 mg/kg olaparib, or vehicle (Veh) once daily for 3 weeks; and mice bearing Capan-1 tumors were dosed orally with 5 or 25 mg/kg thioparib, 0.3 mg/kg talazoparib, or vehicle (Veh) once daily for 3 weeks (n = 6). Data are shown as mean ± SEM. Statistical analysis was performed by two-way ANOVA. ***P < 0.0001. Representative images of xenograft tumors are shown, and mice tails represent complete regression of tumors.
Figure 2(C) The IC50 values of thioparib in six acquired PARPi-resistant cell lines. Numbers 1-6 represent the PARPi-resistant Capan-1/OP, Capan-1/TP, MDA-MB-436/OP, MDA-MB-436/TP, U251/OP, and U251/TP cells, respectively. Cells were treated with the indicated PARP inhibitors for 7 days and then subjected to SRB assay. The IC50 values are expressed as the mean ± SD from three separate experiments.(E) Efficacy of thioparib in the PDX model BR-05-0028 (BRCA1-deficient). Mice bearing BR-05-0028 tumors derived from a patient with breast cancer (n = 6) were treated with 10 or 30 mg/kg thioparib or 100 mg/kg olaparib for 6 weeks. Data are depicted as mean ± SEM. ***P < 0.0001.
Figure 3(B) Concentration-dependent effects of thioparib on the viability of malignant hematologic cells. Cells were treated with thioparib or other PARP inhibitors for 72 h and then subjected to CCK8 assay. Data from three independent experiments were presented as mean ± SEM.(D) Kaplan-Meier survival curve of M-NSG mice transplanted with JeKo-1 cells treated with 10 mg/kg thioparib, 0.3 mg/kg talazoparib, or vehicle (n = 10). Statistical analysis was performed by log-rank (Mantel-Cox) test. ***P < 0.0001, ns: P = 0.3526.
Figure 4(B) Western blotting of γH2AX and phosphor-RPA32 in cells exposed to thioparib, talazoparib, or olaparib for 12 h.(E) and (F). Thioparib caused changes in apoptosis-related proteins in JeKo-1 or THP-1 cells, as determined by western blotting. Cells were exposed to thioparib, talazoparib, olaparib, or Cpd 391 for 24 h and then subjected to western blotting.(G) and (H). Depletion of PARP1 in HT-29 and Capan-1/TP cells resulted in a decrease in DNA damage and thioparib resistance. The upper panel shows the changes in γH2AX and phospho-RPA32 in HT-29 PARP1 knockout (KO) clones (G) or Capan-1/TP PARP1 KO clones (H) and their parental cells after exposure to thioparib for 24 h. The lower panel shows the IC50 values of thioparib in these PARP1 KO clones and parental cells. Cells were treated with thioparib for 5 or 7 d and the IC50 values were determined by SRB assay from three separate experiments. Data are presented as the mean ± SD. ThP: Thioparib, OP: Olaparib, TP: Talazoparib, 391: Cpd 391.
Figure 5(A) HR repair assays in U2OS-DR-GFP cells treated with increasing concentrations of thioparib. Cells were incubated with the indicated drugs at the time of I-SceI introduction for 48 h. GFP-positive cells were analyzed after I-SceI transfection for 72 h by flow cytometry. The ATR inhibitor VE-821 was used as a positive control. Three independent experiments were performed and data are expressed as mean ± SD. Statistical analysis was performed by one-way ANOVA, and all groups were compared with control. ***P < 0.0001, *P = 0.0205, 0.0101 (from left to right).(C) Representative images of RAD51 foci in U2OS-DR-GFP cells with or without radiation. Graphs (right panel) show quantification of cells with ≥ 5 RAD51 foci in vehicle- and drug-treated cells. Scale bar: 5 μm. Data are obtained from three biological replicates and presented as mean ± SD. Statistical analysis was performed by one-way ANOVA. Left to right: P < 0.0001, = 0.0033, < 0.0001, = 0.0006, = 0.0031, = 0.0015.(H) HR repair assay. U2OS-DR-GFP (WT) and PARP1 KO cells (KO1 and KO2) were treated with the indicated drugs for 48 h and collected after 72 h of I-SceI transfection as in (A). VE-821 served as a positive control. PARP1 knockout efficiency was evaluated by western blotting. Data from three biological replicates are presented as mean ± SD. Statistical analysis was performed by one-way ANOVA, and each group was compared with the control. ***P < 0.0001, *P = 0.0143, 0.0483, ns: P = 0.3061, 0.8269, 0.9997, 0.3906 (from left to right).
Figure 6(C) Effects of thioparib on CXCL9, CXCL10, and IL15 mRNA in JeKo-1 cells. Data from three independent experiments are shown as the mean ± SD. Statistical analysis was performed by two-way ANOVA. Left panel: *P = 0.0367, **P = 0.0011; median panel: ***P = 0.0002, < 0.0001, < 0.0001; right panel: ***P = 0.0005, 0.0009, 0.0001 (from left to right).(D) The protein levels of p-STAT1, p-TBK1, γH2AX, and phospho-RPA32 in HT-29 parent, PARP1−/− (#KO1), and PARP7−/− cell lines after 24 or 48 h thioparib treatment.(F) Western blot analysis of p-STAT1, p-TBK1, and γH2AX in HT-29 parent, STING−/−, and TBK1−/−cells after 24 or 48 h thioparib treatment.(H) Immunohistochemistry staining of CD4, CD8, and CD45 expression in MC38 tumor tissue sections. Quantification of cells positive of CD4, CD8, CD45 were shown. Scale bar: 25 μm. Data from ten technical replicates from each of the two mice are presented as mean ± SD. Statistical analysis was performed by unpaired t-test. ***P < 0.0001, ns: P = 0.1958.
Figure 1Western blot analysis of soluble and insoluble fractions (Red- and yellow rectangles, highlights CTF-35 and CTF-25 respectively in the insoluble fraction).
Figure 2Immunofluorescent analysis showing fluorescence intensity of phosphorylated TDP-43 (pTDP-43). Scale bar: 20µm. Presented immunofluorescent images of control (C2) and mutant TDP-43 (P2). I represents its corresponding profile intensity plot of the selected (square) region. Scale bar: 10µm, J quantification pooled control (C0=10, C1=10 and C2=10) n=30 and pooled mutant TDP-43 (P1=10, P2=10 and P3=10) n=30 cells from each differentiation. Unpaired Mann-Whitney-test.
Figure 3Western blots showing nucleo-cytoplasmic fractionation of WT-mCherry and MUT-mCherry iPSC-derived motor neurons with F (left panel) quantification of total mCherry and total untagged TDP-43 on α-tubulin and (right panel) relative cytoplasmic mCherry and untagged TDP-43 on total mCherry and total untagged TDP-43 respectively
Figure 4Representative kymographs from control and mutant TDP-43 iPSC-derived motor neurons. The x-axis represent distance in µm while on the y-axis time in seconds is revealed. Stationary mitochondria are visible as straight vertical lines, while moving mitochondria are depicted as skewed lines. B Quantification of percentage of moving mitochondria.
Figure 6Immunofluorescent analysis showing fluorescence intensity of pTDP-43 in motor neurons. Scale bar: 10µm and its perspective intensity plot in F. G Quantification of E, each dot represents one analysed cell, unpaired Mann-Whitney-test.axonal transport analysis. Quantification of percentage of moving mitochondria (J), number of moving mitochondria (K) and number of stationary mitochondria (L) normalized to neurite length 100µm.
Figure 7Total cell lysates were fractionated into soluble and insoluble fractions and analysed by Western blot, representative Western blots of soluble and insoluble fraction without C and with D HDAC6 inhibitor treatment.
Figure 8Immunofluorescent analysis of TDP-43 in control, mutant TDP-43 and mutant TDP-43+HDAC6 inhibitor after 12 h treatment. Presented immunofluorescent images of control (C2) and mutant TDP-43 (P2). Scale bar: 25µm. B Profile intensity plot of control, mutant TDP-43 and mutant TDP-43+HDAC6 inhibitor. C Quantification of nucleo-cytoplasmic ratio (N/C) fluorescent intensity of TDP-43 in motor neurons, each dot represents one analyzed cell, unpaired Mann-Whitney-test.
Figure 9Quantification of relative nuclear mCherry TDP-43 on total fraction, ratio paired-t-test.
Figure 1P. falciparum symptomatic (n=30) and asymptomatic (n=40) infected individuals, as well as light-microscopy and PCR parasite-negative healthy immune controls (n=31) were recruited for the study. A-F. Clinical parameters determined in the study include age (A), gender (B), parasitemia (C), hemoglobin (g/dL blood) (D), hematocrit (E), and platelet count (F). Boxes represent the 25th to 75th percentiles, whiskers show the range (minimum to maximum), and lines represent the median. Significance was determined by the Kruskal-Wallis test with Dunn's multiple comparisons (A, D-F), the Chi-square test (B), and the Mann-Whitney test (C) using 30 (symptomatic), 40 (asymptomatic) and 31 (healthy immune controls) biological replicates. ****p<0.0001.P. falciparum symptomatic (n=30) and asymptomatic (n=40) infected individuals, as well as light-microscopy and PCR parasite-negative healthy immune controls (n=31) were recruited for the study. G. Antibody titers specific for P. falciparum parasite lysate. Bars represent the mean ± SD of using 29 (symptomatic), 35 (asymptomatic) and 26 (healthy immune controls) biological replicates. The dotted line depicts the average antibody background levels of malaria-naive healthy Melbourne controls. H. Mean antibody titers as determined by ELISA to the P. falciparum recombinant proteins EBA-175, EBA-140, PfRh2, PfRh4, PfRh5, and PfRipr.
Figure 3Unsupervised identification of differentially abundant high-dimensional cell populations between clinical groups was performed using CITRUS (FDR<5%). between P. falciparum symptomatic infected individuals and asymptomatic participants or healthy immune controls. A-E. tSNE plots of clinical groups and viSNE plots depicting expression of selected surface markers, relative abundance and cellular phenotype of differentially abundant clusters identified among CXCR3+CCR6- memory CD4+ T cells (A), CXCR3-CCR6- memory CD4+ T cells (B), circulating memory TFH cells (C), classical MBCs (D), and atypical MBCs (E). The tSNE plots in the top or each panel display cell density and represent pooled data for each group as calculated in the clustering analysis while the viSNE plots on each top panel depict relevant marker expression on tSNE overlays. The lower panels from left to right show differentially abundant populations identified in purple on a tSNE overlay, whiskers showing the range (minimum to maximum), with lines representing the median of 16 (symptomatic), 24 (asymptomatic) and 24 (healthy immune controls) biological replicates, while the pink histograms illustrate marker expression in identified differentially abundant populations, relative to background expression, shown in lilac.
Figure 4PBMCs from P. falciparum symptomatic (n=6) and asymptomatic (n=5) infected individuals as well as healthy immune controls (n=6) were selected for RNA-seq analysis. A. Estimated proportions of PBMC sub-populations determined from cell-type deconvolution from study participant transcriptional profiles.PBMCs from P. falciparum symptomatic (n=6) and asymptomatic (n=5) infected individuals as well as healthy immune controls (n=6) were selected for RNA-seq analysis. D. Blood transcriptional module (BTM) analysis showing significant BTMs differentially enriched for pairwise comparisons (FDR<15%).
Figure 5Gene expression profiles of PBMCs from P. falciparum symptomatic and healthy immune controls were compared. A. Unsupervised hierarchical clustering heat map of the 922 differentially expressed genes (DEGs) between symptomatic P. falciparum malaria and healthy immune controls using the complete method and Euclidian measure of distance. B. Mean-difference plot displaying genes differentially expressed between symptomatic P. falciparum malaria and healthy immune controls. Each gene is plotted as a single point determined by log-fold-change and average transcript abundance. Red genes are overrepresented, and blue genes are underrepresented in symptomatic malaria.Gene expression profiles of PBMCs from P. falciparum symptomatic and healthy immune controls were compared. F. Upstream regulator analysis of the 922 DEGs between symptomatic P. falciparum malaria and healthy immune controls. The red lines represent a significant activation z-score of ±2.Gene expression profiles of PBMCs from P. falciparum symptomatic and healthy immune controls were compared. Hierarchical clustering heatmap (G) displaying DEGs in symptomatic P. falciparum malaria and healthy immune controls predicted to be controlled by IFN-γ and IL-13 upstream regulators.
Figure 6Gene expression profiles of PBMCs from P. falciparum symptomatic and asymptomatic infected participants were compared. C. Heat map of the 418 DEGs in P. falciparum symptomatic and asymptomatic infected participants as well as in healthy immune controls. E. Volcano plot displaying selected genes clusters 1 and 2 from heatmap in C scaled by Log2-fold-change and -Log10(P-value) differentially expressed between P. falciparum symptomatic and asymptomatic infected individuals. Genes in red are overrepresented in symptomatic malaria and genes in blue are overrepresented in asymptomatic malaria.Gene expression profiles of PBMCs from P. falciparum symptomatic and asymptomatic infected participants were compared. F. Mean RPKMs + SEM of selected genes in P. falciparum malaria symptomatic (n=6) and asymptomatic (n=5) individuals. Dotted red lines depict transcriptional levels of healthy immune controls, Mann-Whitney test of biological replicates,*p<0.05.
Figure 7Gene expression profiles of bulk PBMCs from P. falciparum-infected asymptomatic individuals and healthy immune controls were compared. A. Hierarchical clustering heat map of the 171 differentially expressed genes (DEGs) in P. falciparum asymptomatic and healthy immune control participants. C. Mean-difference plot displaying DEGs between asyptomatic P. falciparum malaria and healthy immune controls. Each gene is plotted as a single point determined by log-fold-change and average transcript abundance. Red genes are overrepresented, and blue genes are underrepresented in asymptomatic malaria.Gene expression profiles of bulk PBMCs from P. falciparum-infected asymptomatic individuals and healthy immune controls were compared. E. Mean RPKMs + SEM of selected genes in P. falciparum malaria asymptomatic individuals (n=5) and healthy immune controls (n=6). Dotted red lines depict transcriptional levels of P. falciparum-infected symptomatic individuals, Mann-Whitney test of biological replicates, *p<0.05.
Figure 8A. Volcano plot showing genes upregulated in symptomatic individuals that were significantly correlated with IgM+ activated MBCs. B. Volcano plot showing genes upregulated in symptomatic individuals that were significantly correlated with T-bet+ CD4+ T cells.
Figure 9B-G. PBMCs from P. falciparum symptomatic (n=6) and asymptomatic (n=6) infected individuals as well as healthy immune controls (n=6) were stained with a panel of antibodies and analyzed by flow cytometry. tSNE plots (B) display cell density of the pooled data for each group, (C) shows a projection of the FlowSOM clusters on a tSNE plot, and (D) is a heatmap depicting the celluar phenotype of clusters of CTLA-4+CD3+CD19- cells. Bar plots representing mean relative abundance of biological replicates + SEM of relevant clusters among clinical groups (E), Mann-Whitney test, *p<0.05. The panel on the left shows the average CTLA-4 mean fluorescent intensity (MFI) or 6 biological replicates in cluster 4 + SEM, Mann-Whitney test, **p<0.01, while representative histograms of CTLA-4 expression in cluster 4 are shown on the right (F). Marker intensity within clusters 1 and 6 (G).
Figure 1Human Aβ exhibits a biphasic profile in CSF of APP transgenic miceA, B Aβ40 and Aβ42 concentrations in CSF of male APP23 mice (heterozygous; 3 (n = 14), 6 (n = 12), 8 (n = 10), 12 (n = 11), 19 (n = 9), and 25 (n = 6) months of age). CSF Aβ40 (F(1, 56) = 22.351, P < 0.001) as well as CSFAβ42 (F(1, 56) = 38.597, P < 0.001) followed a significant quadratic trend.C Aβ42/40 ratio in CSF of APP23 mice showed a delayed decrease with age (F(1, 56) = 53.894, P < 0.001).D, E Aβ40 and Aβ42 concentrations in CSF of male and female APP24 mice (homozygous; 2 (n = 13), 3-4 (n = 16), 7-8 (n = 15), 18-19 (n = 14), 24 (n = 16), and 30 (n = 18) months of age). CSF Aβ40 followed a significant quadratic trend (F(1, 86) = 6.678, P = 0.011) and CSF Aβ42 best fitted a cubic trend (F(1, 86) = 30.599, P < 0.001).F Aβ42/40 ratio in CSF of APP24 mice showed a delayed decrease with age (F(1, 86) = 64.936, P < 0.001).G, H Aβ40 and Aβ42 in the CSF of female APP51 mice (heterozygous; 3 (n = 6), 15 (n = 8), and 24 (n = 8) months of age; 22 mice in total). CSF Aβ40 (F(1, 19) = 37.349, P < 0.001) as well as CSFAβ42 (F(1, 19) = 107.670, P < 0.001) followed a significant quadratic trend.I Aβ42/40 ratio in CSF of APP51 mice showed a delayed decrease with age (F(1, 19) = 26.367, P < 0.001).
Figure 2HumanAβ in CSF and brain of APP transgenic miceA APP23CSFAβ40 and Aβ42 in the same animals as shown in Fig1. CSFAβ42 and Aβ40 are expressed as percentages of levels measured in the youngest age group.B, C Aβ40 and Aβ42 (pmol/g wet brain) in the FA-soluble brain extract from the same APP23mice showed a robust increase with age; ANOVA revealed a significant cubic trend (F(1, 56) = 221.114, P < 0.001 and F(1, 56) = 370.947, P < 0.001, respectively).D APP24 CSF Aβ40 and Aβ42 in the same animals shown in Fig1 as percentage of the youngest age group.E, F Aβ40 and Aβ42 (pmol/g wet brain) in the brain from the same APP24mice also showed a robust increase with age; ANOVA revealed a significant cubic trend (F(1, 86) = 202.173, P < 0.001 and F(1, 86) = 139.941, P < 0.001, respectively).G APP51 CSF Aβ40 and Aβ42 in the same animals shown in Fig1 as percentages of levels in the youngest age group.H, I Aβ40 and Aβ42 (pmol/g wet brain) in the brain from the same APP51 mice showed a robust increase with age; ANOVA revealed a significant quadratic trend (F(1, 19) = 12.960, P = 0.002 and F(1, 19) = 19.366, P < 0.001, respectively).
Figure 3Aβplaque pathology in the brains of APP23miceAβimmunostaining (CN3 antibody, dark blue) in 25-μm sagittal brain sections shows only sparse Aβ deposits primarily in the frontal cortex of 6- to 8-month-old APP23mice. At 12 months and thereafter, there is a progressive increase in plaque number and size and a progressive involvement of different brain regions. Insets highlight the plaque characteristics at the different ages. Scale bar, 100 μm.The mean number of Aβ plaques per section per hemibrain increased with age in 3- to 12-month-old mice. Only four mice were analyzed in the 3-month-old age group, as APP23mice do not develop plaques at this age (Sturchler-Pierrat et al, 1997). The 6-, 8-, and 12-month-old age groups included 12, 10, and 11 mice, respectively (these are the same mice that were used for CSF and brainAβ measurements). Note that the Aβ plaques became too numerous and often could no longer be individually distinguished in the age groups > 12 months of age. Data are represented as group means ± SEM.