Formation of amyloid-beta (Aβ) oligomer pores in the membrane of neurons has been proposed to explain neurotoxicity in Alzheimerʼs disease (AD). Here, we present the threedimensional structure of an Aβ oligomer formed in a membrane mimicking environment, namely an Aβ(1-42) tetramer, which comprises a six stranded β-sheet core. The two faces of the β-sheet core are hydrophobic and surrounded by the membrane-mimicking environment while the edges are hydrophilic and solvent-exposed. By increasing the concentration of Aβ(1-42) in the sample, Aβ(1-42) octamers are also formed, made by two Aβ(1-42) tetramers facing each other forming a β-sandwich structure. Notably, Aβ(1-42) tetramers and octamers inserted into lipid bilayers as well-defined pores. To establish oligomer structure-membrane activity relationships, molecular dynamics simulations were carried out. These studies revealed a mechanism of membrane disruption in which water permeation occurred through lipid-stabilized pores mediated by the hydrophilic residues located on the core β-sheets edges of the oligomers.

Iron-sulfur (Fe-S) clusters are essential protein cofactors whose biosynthetic defects lead to severe diseases among which is Friedreich’s ataxia caused by impaired expression of frataxin (FXN). Fe-S clusters are biosynthesized on the scaffold protein ISCU, with cysteine desulfurase NFS1 providing sulfur as persulfide and ferredoxin FDX2 supplying electrons, in a process stimulated by FXN but not clearly understood. Here, we report the breakdown of this process, made possible by removing a zinc ion in ISCU that hinders iron insertion and promotes non-physiological Fe-S cluster synthesis from free sulfide in vitro. By binding zinc-free ISCU, iron drives persulfide uptake from NFS1 and allows persulfide reduction into sulfide by FDX2, thereby coordinating sulfide production with its availability to generate Fe-S clusters. FXN stimulates the whole process by accelerating persulfide transfer. We propose that this reconstitution recapitulates physiological conditions which provides a model for Fe-S cluster biosynthesis, clarifies the roles of FDX2 and FXN and may help develop Friedreich’s ataxia therapies.

Antibody drug conjugates (ADCs) are macromolecules composed of cytotoxic drugs covalently attached via a conditionally stable linker to monoclonal antibodies (mAbs). ADCs are among the most promising next generation of empowered mAbs foreseen to treat cancers. Compared to naked mAbs, ADCs have an increased level of complexity as the heterogeneity of conjugation cumulates with the inherent microvariability of the biomolecule. An increasing need underlying ADC's development and optimization is to improve its analytical and bioanalytical characterization by assessing three main ADC quality attributes: drug distribution, amount of naked antibody, and average drug to antibody ratio (DAR). Here, the analytical potential of native mass spectrometry (MS) and native ion mobility MS (IM-MS) is compared to hydrophobic interaction chromatography (HIC), the reference method for quality control of interchain cysteinyl-linked ADCs. Brentuximab vedotin, first in class and gold standard, was chosen for a proof of principle. High resolution native MS provided accurate mass measurement (<30 ppm) of intact ADCs together with average DAR and drug distribution, confirming the unique ability of native MS for simultaneous detection of mixtures of covalent and noncovalent products. Native IM-MS was next used for the first time to characterize an ADC. IM-MS evidenced ADC multiple drug loading, collisional cross sections measurement of each payload species attesting slight conformational changes. A semiquantitative interpretation of IM-MS data was developed to directly extrapolate average DAR and DAR distribution. Additionally, HIC fractions were collected and analyzed by native MS and IM-MS, assessing the interpretation of each HIC peak. Altogether, our results illustrate how native MS and IM-MS can rapidly assess ADC structural heterogeneity and how easily these methods can be implemented into MS workflows for in-depth ADC analytical characterization.