Generation of two human NRF2 knockout iPSC clones using CRISPR/Cas9 editing

The nuclear factor erythroid 2-related factor 2 (NFE2L2, known as NRF2) regulates the expression of antioxidative and anti-inflammatory proteins. In order to investigate its impact during viral infections and testing of antiviral compounds, we applied CRISPR/Cas9 editing to eliminate NRF2 in the human iPS cell line MHHi001-A and generated two NRF2 knockout iPSC clones MHHi001-A-6 and MHHi001-A-7. After differentiation into epithelia or endothelial cells, these cells are useful tools to examine the antiviral effects of activators of the NRF2 signaling pathway

Elevated phospholipids and acylcarnitines C4 and C5 in cerebrospinal fluid distinguish viral CNS infections from autoimmune neuroinflammation

Abstract Background Viral and autoimmune encephalitis may present with similar symptoms, but require different treatments. Thus, there is a need for biomarkers to improve diagnosis and understanding of pathogenesis. We hypothesized that virus-host cell interactions lead to different changes in central nervous system (CNS) metabolism than autoimmune processes and searched for metabolite biomarkers in cerebrospinal fluid (CSF) to distinguish between the two conditions. Methods We applied a targeted metabolomic/lipidomic analysis to CSF samples from patients with viral CNS infections (n = 34; due to herpes simplex virus [n = 9], varicella zoster virus [n = 15], enteroviruses [n = 10]), autoimmune neuroinflammation (n = 25; autoimmune anti-NMDA-receptor encephalitis [n = 8], multiple sclerosis [n = 17), and non-inflamed controls (n = 31; Gilles de la Tourette syndrome [n = 20], Bell’s palsy with normal CSF cell count [n = 11]). 85 metabolites passed quality screening and were evaluated as biomarkers. Standard diagnostic CSF parameters were assessed for comparison. Results Of the standard CSF parameters, the best biomarkers were: CSF cell count for viral infections vs. controls (area under the ROC curve, AUC = 0.93), Q-albumin for viral infections vs. autoimmune neuroinflammation (AUC = 0.86), and IgG index for autoimmune neuroinflammation vs. controls (AUC = 0.90). Concentrations of 2 metabolites differed significantly (p < 0.05) between autoimmune neuroinflammation and controls, with proline being the best biomarker (AUC = 0.77). In contrast, concentrations of 67 metabolites were significantly higher in viral infections than controls, with SM.C16.0 being the best biomarker (AUC = 0.94). Concentrations of 68 metabolites were significantly higher in viral infections than in autoimmune neuroinflammation, and the 10 most accurate metabolite biomarkers (AUC = 0.89–0.93) were substantially better than Q-albumin (AUC = 0.86). These biomarkers comprised six phosphatidylcholines (AUC = 0.89–0.92), two sphingomyelins (AUC = 0.89, 0.91), and acylcarnitines isobutyrylcarnitine (C4, AUC = 0.92) and isovalerylcarnitine (C5, AUC = 0.93). Elevated C4 and C5 concentrations suggested dysfunctional mitochondrial β-oxidation and correlated only moderately with CSF cell count (Spearman ρ = 0.41 and 0.44), indicating that their increase is not primarily driven by inflammation. Conclusions Changes in CNS metabolism differ substantially between viral CNS infections and autoimmune neuroinflammation and reveal CSF metabolites as pathophysiologically relevant diagnostic biomarkers for the differentiation between the two conditions. In viral CNS infections, the observed higher concentrations of free phospholipids are consistent with disruption of host cell membranes, whereas the elevated short-chain acylcarnitines likely reflect compromised mitochondrial homeostasis and energy generation

3D structural modeling of 4OI-XPO1 interactions based on the co-crystal structure of XPO1 (CRM1) with leptomycin B (PDB ID: 6TVO).

Both 4OI and leptomycin B are covalently bound to the reactive Cys528 (marked with an asterisk *) and interact extensively with the hydrophobic NES-binding groove. A. 4OI binds the site through hydrophobic interactions between the octyl chain and Ile521, Leu525, Met545, Val565 and Leu569 in the hydrophobic pockets Φ2 and Φ3 of the NES-binding site. The C1-carboxyl group further stabilizes binding through two hydrogen bonds with Lys537 and Lys568. These hydrophobic and electrostatic interactions optimally direct the methylene group of 4OI towards Cys528 and could be the driving force for the covalent Michael 1,4-addition. B. Overlay of 4OI (cyan) and leptomycin B (magenta) in the NES-binding groove showing about 70% occupancy by leptomycin B and 40% by 4OI. Lipophilicity protein surface at the NES-binding cleft: lipophilic (green), hydrophilic (violet), neutral (white), α-helices (gold). * = Cys528. (EPS)</p

Percentage of infected cells throughout an 8 h time course of IAV infection.

A549 cells were pretreated with the compounds (SEL, 1 μM; 4OI, 100 μM; BARD, 0.1 μM; SFN, 10 μM) for 12 h, were then infected with IAV PR8M (MOI = 1) for 1 h and subsequently incubated in fresh medium containing the compounds. Analysis based on the same images as used for Fig 2C–2F. Total number of cells was determined by counting DAPI-positive nuclei, and IAV infected cells by counting cells staining positive for NP in nucleus, cytoplasm or both. Data correspond to averages from 7 microscopic fields. A. Percentage of infected cells at 4, 6, and 8 h p.i. One-way ANOVA with Tukey’s post-hoc test. * ≤0.05, ** ≤0.01, *** ≤0.001, **** ≤0.0001. (EPS)</p

The compounds favor nuclear retention of p53 in IAV-infected A549 cells.

A549 cells were treated and infected as described for Fig 2. p53 was detected by indirect immunofluorescence 8 h p.i., using Alexa Fluor 568 labeled secondary antibody. A. Representative immunofluorescence images p53 = red. Nuclei = blue (DAPI). Pink signal in merged images = nuclear localized p53. The positive staining granular pattern is a technical artefact and was considered background signal. Negative control = no primary antibody. B. Fraction of all cells with nuclear p53 staining. Cells with nuclear p53 staining were counted by visual inspection by two independent examiners who were blinded to the identity of the specimens. n = 4 microscopic fields, means ±SEM. One-way ANOVA with Tukey’s post-hoc test, using infected untreated wild-type or knock-down cells as reference. * ≤0.05, ** ≤0.01, *** ≤0.001, **** ≤0.0001. (EPS)</p

Competition experiment demonstrating binding of 4OI and SEL to the same sites on XPO1 and KEAP1.

A,B. “Click-chemistry” pull-down assay demonstrating covalent binding of an alkynated 4OI probe (4-OI-alk) to XPO1 (A) and KEAP1 (B) in Calu-3 cells. Cells were preincubated with 1 or 4 μM unmodified SEL for 30 min. as indicated. Two hours after addition of the probe, proteins complexed with the probe were detected by immunoblot for XPO1 (A) or KEAP1 (B). C,D. Densitometry (arbitrary units) of the immunoblots, normalized to the signal obtained from the band labeled “input”. SEL competes with 4OI for complex formation with both targets, suggesting that the compounds recognize the same sites on both targets. However, competition is less efficient for complex formation with KEAP1, suggesting that 4OI has higher affinity for KEAP1 and that SEL has higher affinity for XPO1. (EPS)</p

The dynamic range of induction of anti-oxidative mRNAs by the four compounds is greater in iPSC-derived ECs than in A549 cells.

Reanalysis of the data of Figs 3J and 4C. A-D, Baseline expression of the target genes is significantly higher in A549 cells than in iPSC-derived ECs. RT-qPCR data were reanalyzed using the 2-ΔCt method, using HPRT mRNA as reference. Differences in expression (expressed on log2 scale) in the absence of treatment was compared between A549 and iPSC-derived ECs, either in uninfected or infected cells. n = 3, means ±SEM. T-test. * ≤0.05, ** ≤0.01, *** ≤0.001, **** ≤0.0001. E, Induction of the target genes by the treatments is greater in iPSC-derived ECs than in A549 cells. Fold change (expressed as linear values) was computed for each cell type and compound by the 2-ΔΔCt method, using infected untreated cells as reference. Differences between the two cell types in fold change due to the same treatment were assessed by T-test. * ≤0.05, ** ≤0.01, *** ≤0.001, **** ≤0.0001. (EPS)</p

Viruses with pharmacologic evidence of XPO1 (CRM1)-dependence.

Viruses with pharmacologic evidence of XPO1 (CRM1)-dependence.</p

Covalent binding energies of the compounds to human XPO1 (CRM1).

Covalent binding energies of the compounds to human XPO1 (CRM1).</p

Covalent binding energies of the compounds to the BTB domain of human KEAP1.

Covalent binding energies of the compounds to the BTB domain of human KEAP1.</p