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Previous studies revealed DNA damage to occur during the toxic action of PaT, a fungal anticodon ribonuclease (ACNase) targeting the translation machinery via tRNA cleavage. Here, we demonstrate that other translational stressors induce DNA damage-like responses in yeast as well: not only zymocin, another ACNase from the dairy yeast Kluyveromyces lactis, but also translational antibiotics, most pronouncedly hygromycin B (HygB). Specifically, DNA repair mechanisms BER (base excision repair), HR (homologous recombination) and PRR (post replication repair) provided protection, whereas NHEJ (non-homologous end-joining) aggravated toxicity of all translational inhibitors. Analysis of specific BER mutants disclosed a strong HygB, zymocin and PaT protective effect of the endonucleases acting on apurinic sites. In cells defective in AP endonucleases, inactivation of the DNA glycosylase Ung1 increased tolerance to ACNases and HygB. In addition, Mag1 specifically contributes to the repair of DNA lesions caused by HygB. Consistent with DNA damage provoked by translation inhibitors, mutation frequencies were elevated upon exposure to both fungal ACNases and HygB. Since polymerase ζ contributed to toxicity in all instances, error-prone lesion-bypass probably accounts for the mutagenic effects. The finding that differently acting inhibitors of protein biosynthesis induce alike cellular responses in DNA repair mutants is novel and suggests the dependency of genome stability on translational fidelity.

BackgroundChildren presenting with proliferative lupus nephritis (LN) are treated with intensified immunosuppressive protocols. Data on renal outcome and treatment toxicity is scare.MethodsTwelve-month renal outcome and comorbidity were assessed in 79 predominantly Caucasian children with proliferative LN reported to the Lupus Nephritis Registry of the German Society of Paediatric Nephrology diagnosed between 1997 and 2015.ResultsAt the time of diagnosis, median age was 13.7 (interquartile range 11.8–15.8) years; 86% showed WHO histology class IV, nephrotic range proteinuria was noted in 55%, and median estimated glomerular filtration rate amounted to 75 ml/min/1.73 m2. At 12 months, the percentage of patients with complete and partial remission was 38% and 41%, respectively. Six percent of patients were non-responders and 15% presented with renal flare. Nephrotic range proteinuria at the time of diagnosis was associated with inferior renal outcome (odds ratio 5.34, 95% confidence interval 1.26–22.62, p = 0.02), whereas all other variables including mode of immune-suppressive treatment (e.g., induction treatment with cyclophosphamide (IVCYC) versus mycophenolate mofetil (MMF)) were not significant correlates. Complications were reported in 80% of patients including glucocorticoid toxicity in 42% (Cushingoid appearance, striae distensae, cataract, or osteonecrosis), leukopenia in 37%, infection in 23%, and menstrual disorder in 20%. Growth impairment, more pronounced in boys than girls, was noted in 78% of patients.ConclusionsIn this cohort of juvenile proliferative LN, renal outcome at 12 months was good irrespectively if patients received induction treatment with MMF or IVCYC, but glucocorticoid toxicity was very high underscoring the need for corticoid sparing protocols.

BackgroundThis study correlates the clinical presentation of Henoch–Schönlein purpura nephritis (HSPN) with findings on initial renal biopsy.MethodsData from 202 pediatric patients enrolled in the HSPN registry of the German Society of Pediatric Nephrology reported by 26 centers between 2008 and 2014 were analyzed. All biopsy reports were re-evaluated for the presence of cellular crescents or chronic pathological lesions (fibrous crescents, glomerular sclerosis, tubular atrophy >5%, and interstitial fibrosis >5%).ResultsPatients with HSPN with cellular glomerular crescents were biopsied earlier after onset of nephritis (median 24 vs 36 days, p = 0.04) than those without, whereas patients with chronic lesions were biopsied later (57 vs 19 days, p < 0.001) and were older (10.3 vs 8.6 years, p = 0.01) than those without. Patients biopsied more than 30 days after the onset of HSPN had significantly more chronic lesions (52 vs 22%, p < 0.001), lower eGFR (88 vs 102 ml/min/1.73m2, p = 0.01), but lower proteinuria (2.3 vs 4.5 g/g, p < 0.0001) than patients biopsied earlier. Children above 10 years of age had lower proteinuria (1.98 vs 4.58 g/g, p < 0.001), lower eGFR (86 vs 101 ml/min/1.73m2, p = 0.002) and were biopsied significantly later after onset of nephritis (44 vs 22 days, p < 0.001) showing more chronic lesions (45 vs 30%, p = 0.03). Proteinuria and renal function at presentation decreased with age.ConclusionsIn summary, we find an age-dependent presentation of HSPN with a more insidious onset of non-nephrotic proteinuria, impaired renal function, longer delay to biopsy, and more chronic histopathological lesions in children above the age of 10 years. Thus, HSPN presents more like Immunoglobulin A (IgA) nephritis in older than in younger children.

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.