Engineering of pH-dependent antigen binding properties for toxin-targeting IgG1 antibodies using light-chain shuffling.

Immunoglobulin G (IgG) antibodies that bind their cognate antigen in a pH-dependent manner (acid-switched antibodies) can release their bound antigen for degradation in the acidic environment of endosomes, while the IgGs are rescued by the neonatal Fc receptor (FcRn). Thus, such IgGs can neutralize multiple antigens over time and therefore be used at lower doses than their non-pH-responsive counterparts. Here, we show that light-chain shuffling combined with phage display technology can be used to discover IgG1 antibodies with increased pH-dependent antigen binding properties, using the snake venom toxins, myotoxin II and α-cobratoxin, as examples. We reveal differences in how the selected IgG1s engage their antigens and human FcRn and show how these differences translate into distinct cellular handling properties related to their pH-dependent antigen binding phenotypes and Fc-engineering for improved FcRn binding. Our study showcases the complexity of engineering pH-dependent antigen binding IgG1s and demonstrates the effects on cellular antibody-antigen recycling.

Substrate O-glycosylation actively regulates extracellular proteolysis.

Extracellular proteolysis critically regulates cellular and tissue responses and is often dysregulated in human diseases. The crosstalk between proteolytic processing and other major post-translational modifications (PTMs) is emerging as an important regulatory mechanism to modulate protease activity and maintain cellular and tissue homeostasis. Here, we focus on matrix metalloproteinase (MMP)-mediated cleavages and N-acetylgalactosamine (GalNAc)-type of O-glycosylation, two major PTMs of proteins in the extracellular space. We investigated the influence of truncated O-glycan trees, also referred to as Tn antigen, following the inactivation of C1GALT1-specific chaperone 1 (COSMC) on the general and MMP9-specific proteolytic processing in MDA-MB-231 breast cancer cells. Quantitative assessment of the proteome and N-terminome using terminal amine isotopic labelling of substrates (TAILS) technology revealed enhanced proteolysis by MMP9 within the extracellular proteomes of MDA-MB-231 cells expressing Tn antigen. In addition, we detected substantial modifications in the proteome and discovered novel ectodomain shedding events regulated by the truncation of O-glycans. These results highlight the critical role of mature O-glycosylation in fine-tuning proteolytic processing and proteome homeostasis by modulating protein susceptibility to proteolytic degradation. These data suggest a complex interplay between proteolysis and O-GalNAc glycosylation, possibly affecting cancer phenotypes.

Functional selectivity of Receptor Tyrosine Kinases regulates distinct cellular outputs.

Functional selectivity refers to the activation of differential signalling and cellular outputs downstream of the same membrane-bound receptor when activated by two or more different ligands. Functional selectivity has been described and extensively studied for G-protein Coupled Receptors (GPCRs), leading to specific therapeutic options for dysregulated GPCRs functions. However, studies regarding the functional selectivity of Receptor Tyrosine Kinases (RTKs) remain sparse. Here, we will summarize recent data about RTK functional selectivity focusing on how the nature and the amount of RTK ligands and the crosstalk of RTKs with other membrane proteins regulate the specificity of RTK signalling. In addition, we will discuss how structural changes in RTKs upon ligand binding affects selective signalling pathways. Much remains to be known about the integration of different signals affecting RTK signalling specificity to orchestrate long-term cellular outcomes. Recent advancements in omics, specifically quantitative phosphoproteomics, and in systems biology methods to study, model and integrate different types of large-scale omics data have increased our ability to compare several signals affecting RTK functional selectivity in a global, system-wide fashion. We will discuss how such methods facilitate the exploration of important signalling hubs and enable data-driven predictions aiming at improving the efficacy of therapeutics for diseases like cancer, where redundant RTK signalling pathways often compromise treatment efficacy.