bioRxiv Science⌕ Search

bioRxiv · 10.1101/2021.05.27.445994

Polyelectrolyte Coating of Ferumoxytol Differentially Impacts on Labeling of Inflammatory and Steady-State Dendritic Cell Subtypes

Abstract

Engineered magnetic nanoparticles (MNPs) are emerging as advanced tools for medical applications. The coating of MNPs using polyelectrolytes (PEs) is a versatile means to tailor MNP properties and is used to optimize MNP functionality. Dendritic cells (DCs) are critical regulators of adaptive immune responses. Functional distinct DC subsets exist either under steady-state or inflammatory conditions, which are explored for the specific treatment of various diseases, such as cancer, autoimmunity or transplant rejection. Here, the impact of PE coating of ferumoxytol for uptake into both inflammatory and steady-state DCs and cellular responses to the MNP labeling is addressed. Labeling efficiency by uncoated and PE-coated ferumoxytol is highly variable in different DC subsets, and PE coating significantly improves the labeling of steady-state DCs. Uncoated ferumoxytol results in increased cytotoxicity of steady-state DCs after labeling that is abolished by the PE coating, while no increased cell death is observed in inflammatory DCs. Furthermore, uncoated and PE-coated ferumoxytol appears immunologically inert in inflammatory DCs but induces activation of steady-state DCs. These results show that PE coating of MNPs can be applied to endow particles with desired properties for enhanced uptake and cell type-specific responses in distinct target DC populations.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Celikkin, N., Wong, J. E., Zenke, M., Hieronymus, T.. 2021-05-27. Polyelectrolyte Coating of Ferumoxytol Differentially Impacts on Labeling of Inflammatory and Steady-State Dendritic Cell Subtypes. https://doi.org/10.1101/2021.05.27.445994

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The yeast Gcn2 protein kinase mediates P-body formation both through its activity with eIF2α and with non-canonical substrates

P-bodies (PBs) are control hubs for RNA processing and storage that form when translation initiation is inhibited, including during stress. In yeast, Gcn2 is the sole eIF2 alpha kinase that inhibits translation initiation in response to diverse stresses. We show that PB formation depends strongly on Gcn2 during amino acid starvation but only partially during oxidative stress. Constitutively active Gcn2 also induces PB formation in unstressed cells. Surprisingly, PBs are still constitutively formed in a gcn3 mutant strain that is insensitive to eIF2 alpha phosphorylation suggesting that Gcn2 also promotes PB formation independently of eIF2 alpha phosphorylation. Analysis of several putative Gcn2-substrates involved in RNA metabolism identified several proteins required for Gcn2-mediated PB formation. Among these, Smu2, which was not previously implicated in PB formation, localises to PBs and is required for stress-induced coalescence of mRNA granules into PBs. Together, our findings indicate that Gcn2 promotes PB formation via two complementary routes: eIF2 alpha phosphorylation, which generates untranslated mRNAs, and Smu2-dependent maturation of mRNA granules into PBs.

cell biology↗

Quantitative Head-to-Tail Analysis Reveals Heterogeneous Cellular Organization and Connexin Expression in the Porcine Sinoatrial Node

Background: The sinoatrial node (SAN) is an integral component of the cardiac conduction system that dictates heart rhythm. Optical mapping studies have demonstrated functional differences between the superior and inferior leading pacemaking sites in the human SAN; however, the mechanistic connections between structure and function in the SAN through intra-tissue and inter-tissue current source-sink relationships have not been fully resolved. Methods: Porcine SAN longitudinal cryosections along the head-to-tail axis were immunostained and analyzed for regional cell organization and connexin (CX) isoform expression. Results: Quantification of pacemaking cardiomyocyte (PCM) density revealed >9-fold more PCMs within a SAN volume than suggested by a widely cited estimate, assuming comparable PCM densities across species. The SAN head region consisted of large PCM clusters with low aspect ratios, high PCM density, low fibroblast density, and PCMs with the highest HCN4 expression and lowest CX40 and CX43 expression. These characteristics are consistent with an electrically well-insulated, strong current-source that supports pacemaking function. Although the SAN tail also exhibited high local PCM density, its smaller PCM clusters, lower HCN4 expression, and higher CX40, CX43, and CX45 expression rendered it a weaker current source. The SAN mid-region exhibited large PCM clusters aligned in the head-to-tail axis and the highest expression of CX40 and CX45, an expression profile that suggests a fast-conducting intra-tissue pathway that electrically links the leading pacemaking sites at the head and tail. The peripheral SAN at the head and tail also exhibited higher CX expression of all isoforms than the central subregions, an organization consistent with enhanced inter-tissue coupling required for proper pacing function. Conclusions: Our data provide novel insights into the distinct regional micro-organization of the SAN along the head-to-tail axis, which through intra-tissue and inter-tissue coupling, likely modulates the balance of current source-sink relationships that supports robust pacemaking and pacing functions.

cell biology↗

Inference of cell division parameters in bacteria under transient growth conditions

Most quantitative models of bacterial cell division assume steady-state growth, yet natural environments are highly dynamic. Here, we infer division control parameters of E. coli from single-cell size trajectories under nonsteady growth. We describe growth as a continuous process interrupted by stochastic divisions, whose propensity depends on cell size and on the size added since birth. Combining an estimation of time-dependent single-cell growth rates with a maximum-likelihood estimator that we previously validated on synthetic data, we obtain time-resolved estimates of the mean added size at division, its noise, and a strategy parameter that measures how added size depends on birth size. This parameter vanishes for the adder, in which cells add, on average, a fixed size regardless of their size at birth, and is negative for sizer-adder control, in which larger-born cells add less size. We apply this approach to published single-cell data covering steady exponential growth, gradual nutrient depletion, and exit from starvation. We implement a time-resolved model selection based on the Akaike information criterion, concluding that the adder is sufficient during steady growth, whereas size dynamics during entry into and exit from stationary phase are better explained by transient deviations toward sizer-adder control. The framework provides a general method to quantify time-resolved changes in the scale, stochasticity, and strategy of division in nonsteady environments.

cell biology↗