Fungal hydrophobins.

<p>Fungal hydrophobins are unique amphipathic proteins with multiple roles in the fungal life cycle and in mediating interactions between fungus and host. There is diversity in the primary sequences of hydrophobins but they share a similar core three-dimensional structure and a pattern of four disulfide bonds (shown in amber) that stabilize the structures. Increasingly, these proteins show potential for modification of hydrophobic nanomaterials and in solubilizing lipophilic drugs.</p

Additional file 1 of iPSC-derived PSEN2 (N141I) astrocytes and microglia exhibit a primed inflammatory phenotype

Additional file 1: Supplementary Methods. Table S1. Primary antibodies used for immunofluorescence. Table S2. Secondary antibodies used for immunofluorescence. Fig. S1. Sanger sequencing chromatograms showing APOE genotyping of codon 112 (rs429358) and codon 158 (rs7412) for all iPSC lines. Yellow highlight indicates the position of the single nucleotide polymorphism. Fig. S2. Immunofluorescence images of iPSCs from three healthy control lines (Ctrl-06, Ctrl-71, Ctrl-88) and three familial AD lines harbouring a PSEN2 (N141I) mutation (fAD-08, fAD-948, fAD-950). The cells were stained for pluripotency markers Nanog (red), Oct 3 (green) and all nuclei were counterstained with DAPI (blue). Scale bars = 50 μm. Fig. S3. Immunofluorescence images of iPSC-derived NPCs from three healthy control lines (Ctrl-06, Ctrl-71, Ctrl-88) and three familial AD lines harbouring a PSEN2 (N141I) mutation (fAD-08, fAD-948, fAD-950). The cells were stained for A the neural progenitor markers Pax-6 (red) and Nestin (green), B a pluripotency marker Oct3 (green) and all nuclei were counterstained with DAPI (blue). Scale bars = 50 μm. Fig. S4. Immunofluorescence images of iPSC-derived astrocytes from three healthy control lines (Ctrl-06, Ctrl-71, Ctrl-88) and three familial AD lines harbouring a PSEN2 (N141I) mutation (fAD-08, fAD-948, fAD-950). The cells were stained for A astrocyte markers GFAP (red) and S100β (green), B the NPC marker nestin (green). All nuclei were counterstained with DAPI (blue). Scale bars = 50 μm. Fig. S5. Transcriptomic analysis of iPSC-derived cell types and primary human fetal astrocytes. A Principal component analysis and B cluster analysis of iPSC-derived astrocytes (black) from healthy control lines (lines 06, 71 & 88) generated in our study and commercially-available primary astrocytes grown in our lab (green) combined with a datasets from Tcw et al (23), including primary astrocytes (purple), iPSC-derived NPCs (light blue), astrocytes (dark blue) and neurons (yellow). Contrast matrix of differential gene expression between cell types comparing datasets C our iPSC-derived astrocytes vs. Tcw et al’s primary astrocyte and iPSC-derived neurons datasets, D Tcw et al’s dataset alone, E our data alone. Fig. S6 Immunofluorescence images of iPSC-derived microglia-like cells from three healthy control lines (Ctrl-06, Ctrl-71, Ctrl-88) and three familial AD lines harbouring a PSEN2 (N141I) mutation (fAD-08, fAD-948, fAD-950). Images show cells stained for A the microglial markers IBA1 (red), TREM2 (green), B CX3CR1 (red) and all nuclei were counterstained with DAPI (blue). Scale bars = 50 μm. Fig. S7. Multi-cytokine array of Alzheimer’s or healthy iPSC-derived astrocytes A basally and B after 24 h exposure to 10 μM Aβ42 and iPSC-derived microglia-like cells C basally and D after 24 h exposure to 10 μM Aβ42. The figure displays the mean ± SD of three cell lines with the average of two experimental duplicates per line. Multiple unpaired, non-parametric Mann-Whitney t-tests adjusting for a 0.05 false discovery rate were used to test whether there were statistically significant differences between mean cytokine/chemokine release of AD-derived and healthy control astrocytes and microglia-like cells (*p < 0.05, **p < 0.01). Cytokines that yielded an average intensity value less than 10% of the maximum (represented by the dotted line) were considered background and not included in the statistical analysis. Fig. S8. Multi-cytokine array of APOE ε3/ε3 and APOE ε3/ε4 iPSC-derived astrocytes A basally and B after 24 h exposure to 10 μM Aβ42 and iPSC-derived microglia-like cells C basally and D after 24 h exposure to 10 μM Aβ42. The figure displays the mean ± SD of three cell lines with the average of two experimental duplicates per line. Multiple unpaired, non-parametric Mann–Whitney t-tests adjusting for a 0.05 false discovery rate were used to test whether there were statistically significant differences between mean cytokine/chemokine release of APOE ε3/ε3 and APOE ε3/ε4 astrocytes and microglia-like cells (*p < 0.05). Cytokines that yielded an average intensity value less than 10% of the maximum (represented by the dotted line) were considered background and not included in the statistical analysis. Fig. S9. Concentrations of A Aβ42, B Aβ40, C the ratio of Aβ42:40 and D total Aβ protein quantified from iPSC-derived astrocyte supernatants 72 h after plating. Secreted Aβ concentrations were measured using a highly sensitive ELISA and normalised to total protein concentration determined by BCA. The figure displays the mean ± SD of three cell lines with n ≥ 2 independent experiments per line. A post hoc unpaired t-test was used to test whether there were statistically significant differences between mean of APOE ε3/ε3 and APOE ε3/ε4 astrocytes

A Coumarin-Based Array for the Discrimination of Amyloids

Self-assembly of misfolded proteins can lead to the formation of amyloids, which are implicated in the onset of many pathologies including Alzheimer’s disease and Parkinson’s disease. The facile detection and discrimination of different amyloids are crucial for early diagnosis of amyloid-related pathologies. Here, we report the development of a fluorescent coumarin-based two-sensor array that is able to correctly discriminate between four different amyloids implicated in amyloid-related pathologies with 100% classification. The array was also applied to mouse models of Alzheimer’s disease and was able to discriminate between samples from mice corresponding to early (6 months) and advanced (12 months) stages of Alzheimer’s disease. Finally, the flexibility of the array was assessed by expanding the analytes to include functional amyloids. The same two-sensor array was able to correctly discriminate between eight different disease-associated and functional amyloids with 100% classification