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Fc-fusion proteins are an emerging class of protein therapeutics that combine the properties of biological ligands with the unique properties of the fragment crystallizable (Fc) domain of an immunoglobulin G (IgG). Due to their diverse higher-order structures (HOSs), Fc-fusion proteins remain challenging characterization targets within biopharmaceutical pipelines. While high-resolution biophysical tools are available for HOS characterization, they frequently demand extended time frames and substantial quantities of purified samples, rendering them impractical for swiftly screening candidate molecules. Herein, we describe the development of ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) workflows that aim to fill this technology gap, where we focus on probing the HOS of a model Fc-Interleukin-10 (Fc-IL-10) fusion protein engineered using flexible glycine-serine linkers. We evaluate the ability of these techniques to probe the flexibility of Fc-IL-10 in the absence of bulk solvent relative to other proteins of similar size, as well as localize structural changes of low charge state Fc-IL-10 ions to specific Fc and IL-10 unfolding events during CIU. We subsequently apply these tools to probe the local effects of glycine-serine linkers on the HOS and stability of IL-10 homodimer, which is the biologically active form of IL-10. Our data reveals that Fc-IL-10 produces significantly more structural transitions during CIU and broader IM profiles when compared to a wide range of model proteins, indicative of its exceptional structural dynamism. Furthermore, we use a combination of enzymatic approaches to annotate these intricate CIU data and localize specific transitions to the unfolding of domains within Fc-IL-10. Finally, we detect a strong positive, quadratic relationship between average linker mass and fusion protein stability, suggesting a cooperative influence between glycine-serine linkers and overall fusion protein stability. This is the first reported study on the use of IM-MS and CIU to characterize HOS of Fc-fusion proteins, illustrating the practical applicability of this approach. 

Bispecific antibodies (bsAbs) represent a critically important class of emerging therapeutics capable of targeting two different antigens simultaneously. As such, bsAbs have been developed as effective treatment agents for diseases that remain challenging for conventional monoclonal antibody (mAb) therapeutics to access. Despite these advantages, bsAbs are intricate molecules, requiring both the appropriate engineering and pairing of heavy and light chains derived from separate parent mAbs. Current analytical tools for tracking the bsAb construction process have demonstrated a limited ability to robustly probe the higher-order structure (HOS) of bsAbs. Native ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) have proven to be useful tools in probing the HOS of mAb therapeutics. In this report, we describe a series of detailed and quantitative IM-MS and CIU data sets that reveal HOS details associated with a knob-into-hole (KiH) bsAb model system and its corresponding parent mAbs. We find that quantitative analysis of CIU data indicates that global KiH bsAb stability occupies an intermediate space between the stabilities recorded for its parent mAbs. Furthermore, our CIU data identify the hole-containing half of the KiH bsAb construct to be the least stable, thus driving much of the overall stability of the KiH bsAb. An analysis of both intact bsAb and enzymatic fragments allows us to associate the first and second CIU transitions observed for the intact KiH bsAb to the unfolding Fab and Fc domains, respectively. This result is likely general for CIU data collected for low charge state mAb ions and is supported by data acquired for deglycosylated KiH bsAb and mAb constructs, each of which indicates greater destabilization of the second CIU transition observed in our data. When integrated, our CIU analysis allows us to link changes in the first CIU transition primarily to the Fab region of the hole-containing halfmer, while the second CIU transition is likely strongly connected to the Fc region of the knob-containing halfmer. Taken together, our results provide an unprecedented road map for evaluating the domain-level stabilities and HOS of both KiH bsAb and mAb constructs using CIU. 

Comprehensive and accurate comparisons of transcriptomic distributions of cells from samples taken from two different biological states, such as healthy versus diseased individuals, are an emerging challenge in single-cell RNA sequencing (scRNA-seq) analysis. Current methods for detecting differentially abundant (DA) subpopulations between samples rely heavily on initial clustering of all cells in both samples. Often, this clustering step is inadequate since the DA subpopulations may not align with a clear cluster structure, and important differences between the two biological states can be missed. Here, we introduce DA-seq, a targeted approach for identifying DA subpopulations not restricted to clusters. DA-seq is a multiscale method that quantifies a local DA measure for each cell, which is computed from its k nearest neighboring cells across a range of k values. Based on this measure, DA-seq delineates contiguous significant DA subpopulations in the transcriptomic space. We apply DA-seq to several scRNA-seq datasets and highlight its improved ability to detect differences between distinct phenotypes in severe versus mildly ill COVID-19 patients, melanomas subjected to immune checkpoint therapy comparing responders to nonresponders, embryonic development at two time points, and young versus aging brain tissue. DA-seq enabled us to detect differences between these phenotypes. Importantly, we find that DA-seq not only recovers the DA cell types as discovered in the original studies but also reveals additional DA subpopulations that were not described before. Analysis of these subpopulations yields biological insights that would otherwise be undetected using conventional computational approaches.