Search bioRxiv⌕ Search

bioRxiv · 10.1101/2020.04.08.032482

Thyroglobulin Interactome Profiling Uncovers Molecular Mechanisms of Thyroid Dyshormonogenesis

Abstract

Thyroglobulin (Tg) is a secreted iodoglycoprotein serving as the precursor for T3 and T4 hormones. Many characterized Tg gene mutations produce secretion-defective variants resulting in congenital hypothyroidism (CH). Tg processing and secretion is controlled by extensive interactions with chaperone, trafficking, and degradation factors comprising the secretory proteostasis network. While dependencies on individual proteostasis network components are known, the integration of proteostasis pathways mediating Tg protein quality control and the molecular basis of mutant Tg misprocessing remain poorly understood. We employ a multiplexed quantitative affinity purification-mass spectrometry approach to define the Tg proteostasis interactome and changes between WT and several CH-variants. Mutant Tg processing is associated with common imbalances in proteostasis engagement including increased chaperoning, oxidative folding, and routing towards ER-associated degradation components, yet variants are inefficiently degraded. Furthermore, we reveal mutation-specific changes in engagement with N-glycosylation components, suggesting distinct requirements for one Tg variant on dual engagement of both oligosaccharyltransferase complex isoforms for degradation. Modulating dysregulated proteostasis components and pathways may serve as a therapeutic strategy to restore Tg secretion and thyroid hormone biosynthesis.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Wright, M. T., Kouba, L., Plate, L.. 2020-04-09. Thyroglobulin Interactome Profiling Uncovers Molecular Mechanisms of Thyroid Dyshormonogenesis. https://doi.org/10.1101/2020.04.08.032482

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↗