Biology subjects

Ziegler, Y.

Publications and source records attributed to Ziegler, Y..

3 recordsLinked to original sources

bioRxiv2026

TWIST: A diagnostic framework for representing tree water deficit dynamics in process-based forest models

Dendrometer-derived tree water deficit (TWD) contains physiologically rich information and is increasingly used to monitor tree drought stress, yet process-based forest models rarely include a directly comparable representation of TWD dynamics. Existing hydraulic models can represent internal water storage in detail, but their parameter demands limit broader application. Here, we introduce the Tree Water Imbalance and Storage Tracker (TWIST), a parsimonious and physiologically interpretable framework that derives volume-based TWD dynamics. The module is driven by transpiration and relative soil water content and uses three empirical parameters to control transpiration-driven internal water depletion, deficit refilling, and additional soil-water uptake limitation. It also derives relative tree water content (RWCtree) from the simulated deficit and an estimate of the available internal water pool. We tested TWIST by coupling it to the process-based ecosystem model LandscapeDNDC. Parameters were optimized for 2018 and evaluated independently for 2019-2024 against normalized dendrometer-derived TWD at a Czech beech site. Simulated TWD trajectories broadly agreed with observed daily and seasonal dynamics, while RWCtree translated them into a physiologically interpretable proxy for internal dehydration. TWIST demonstrated capability to reproduce key TWD drought-response patterns, including diurnal depletion-replenishment cycles, reduced nocturnal rehydration with declining soil moisture, and progressive deficit accumulation. By representing TWD and RWCtree as diagnostic model outputs, TWIST makes dendrometer-derived drought-stress information more directly usable in forest models. It thereby provides a practical basis for linking tree-level drought-stress signals with stand-level simulations and, potentially, remotely sensed indicators of canopy water status.

Plant Biology↗

bioRxiv2021

Targeting metabolic adaptations in the breast cancer liver metastatic niche using dietary approaches to improve endocrine therapy efficacy

Estrogen receptor-positive (ER+) metastatic tumors contribute to nearly 70% of breast cancer-related deaths. Most patients with ER+ metastatic breast cancer (MBC) undergo treatment with the estrogen receptor antagonist fulvestrant (Fulv) as standard-of-care. Yet, among such patients, metastasis in liver is associated with reduced overall survival compared to other metastasis sites. The factors underlying the reduced responsiveness of liver metastases to ER-targeting agents remain unknown, impeding the development of more effective treatment approaches to improve outcomes for patients with ER+ liver metastases. We therefore evaluated site-specific changes in MBC cells and determined the mechanisms through which the liver metastatic niche specifically influences ER+ tumor metabolism and drug resistance. We characterized ER activity of MBC cells both in vitro, using a novel system of tissue-specific extracellular matrix hydrogels representing the stroma of ER+ tumor metastatic sites (liver, lung and bone), and in vivo, in liver and lung metastasis mouse models. ER+ metastatic liver tumors and MBC cells grown in liver hydrogels displayed upregulated expression of glucose metabolism enzymes in response to Fulv. Furthermore, differential ER activity, but not expression, was detected in liver hydrogels. In vivo, increased glucose metabolism led to increased glycogen deposition in liver metastatic tumors, while a fasting-mimicking diet increased efficacy of Fulv treatment to reduce the metastatic burden. ImplicationsOur findings identify a novel mechanism of endocrine resistance driven by the liver tumor microenvironment. These results may guide the development of dietary strategies to circumvent drug resistance in liver metastasis, with potential applicability in other metastatic diseases.

cancer biology↗

bioRxiv2020

Dual-Mechanism Estrogen Receptor Inhibitors Reveal an Ensemble of Binding Modes for Robust Breast Cancer Antagonism

Efforts to improve estrogen receptor-a (ER)-targeted therapies in breast cancer have relied upon a single mechanism, with ligands having a single side chain on the ligand core that extends outward to determine antagonism of breast cancer growth. Here, we describe inhibitors with two ER-targeting moieties, one of which uses an alternate structural mechanism to generate full antagonism, freeing the side chain to independently determine other critical properties of the ligands. By combining two molecular targeting approaches into a single ER ligand, we have generated antiestrogens that function through new mechanisms and structural paradigms to achieve antagonism. These dual-mechanism ER inhibitors (DMERIs) cause alternate, non-canonical structural perturbations of the receptor ligand-binding domain (LBD) to drive antagonism of proliferation in ER-positive breast cancer cells and in allele-specific resistance models. Solution structural and coregulator peptide binding analyses with DMERIs highlight marked differences from current standard-of-care, single-mechanism antiestrogens. These findings uncover an enhanced flexibility of the ER LBD through which it can access non-consensus conformational modes in response to DMERI binding, broadly and effectively suppressing ER activity. Significance StatementTo address the unmet clinical need for effectively suppressing estrogen receptor (ER) activity with both de novo resistance and in advanced ER-positive breast cancers that are resistant to standard-of-care antiestrogens, we have developed dual-mechanism ER inhibitors (DMERIs) that employ two distinct ER targeting moieties. These DMERI elicited non-canonical structural perturbations of the receptor ligand-binding domain and stabilized multiple antagonist sub-states within the dimer to generate highly efficacious antagonism of proliferation in ER-positive breast cancer cells and in allele-specific resistance models. This work reveals new conformational modes by which the activity of ER can be effectively suppressed to block breast cancer proliferation.

cancer biology↗