Biology subjects

Wright, M. E.

Publications and source records attributed to Wright, M. E..

7 recordsLinked to original sources

bioRxiv2026

A Spatiotemporal Atlas of Extranuclear Androgen Receptor Proximal Interaction Networks

Androgen receptor-interacting proteins (AR-IPs) number close to 1,000, yet their organization across subcellular space and time remains uncharted. Proximity labeling identifies direct partners and neighboring proteins, thereby expanding AR-IPs to AR-proximal interacting proteins (AR-PIPs). Using proximity labeling quantitative mass spectrometry (PL-qMS), we construct a spatiotemporal atlas of the cytosolic, microsomal, and nuclear compartments in LNCaP prostate tumor cells. PL-qMS recovered 82.2% of the known AR-interactome in extranuclear compartments and 84.2% in the nucleus, identifying 4,751 AR-PIPs that remodel across an androgen time course. The retromer formed an androgen-sensitive AR-proximal interaction network (AR-PIN) verified by proximity ligation assays (PLAs). Moreover, partial VPS26A disruption attenuated androgen-regulated transcription and mislocalized the AR coactivator TMF1, defining a retromer-AR-TMF1 axis. In the nucleus, AR-PINs recover 100% of the Launonen 2021 ChIP-SICAP chromatome and reveal a PLA-verified translation-to-transcription handoff involving eIF4G and 4E-BP1. This spatiotemporal atlas provides a proximal framework for probing AR function in cells.

systems biology↗

bioRxiv2026

A Temporal Atlas of the Nuclear Androgen Receptor Proximal Interactome

The authors have withdrawn this manuscript because this manuscript has been merged with another preprint (BIORXIV/2026/742469). Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. The merged preprint can be found at doi: 10.64898/2026.08.03.742469

systems biology↗

bioRxiv2026

Short Linear Motifs as a General Organizing Principle of the Nuclear-Receptor Proximal Interactome

The AR-interactome comprises [~]1,000 androgen receptor-interacting proteins (AR-IPs), yet how a single receptor engages so many partners across compartments remains mechanistically unclear. We integrate proximity-labeling quantitative mass spectrometry across cytosolic, microsomal, and nuclear compartments of LNCaP prostate cancer cells and resolve 4,751 AR-proximal interacting proteins (AR-PIPs), more than four times the size of the AR-interactome. Anchoring on the LXXLL coactivator recognition motif, LXXLL motifs are systematically depleted in AR-PIPs after length control, consistent with low-affinity, transient engagement at the AR AF-2 charge clamp. LXXLL-bearing AR-PIPs include AR itself and canonical AR coactivators altered by amplification, deletion, or motif-spanning mutations in metastatic and castration-resistant prostate cancers. AR-V7, which lacks AF-2, retains LXXLL-depleted Mode 1 partners and loses the LXXLL-enriched Mode 2 cloud, thereby validating a two-mode engagement framework for nuclear receptor-proximal interactomes.

bioinformatics↗

bioRxiv2026

SYNTAX Reads the Motif and Domain Grammar of the Androgen Receptor Proximal Interactome

A receptors interactome is usually reported as a protein list, yet the sequence rules that organize it have never been read out. We introduce SYNTAX, a scan of 356 short linear motif classes and 573 protein domains that corrects the length, burden, and degeneracy artifacts of motif counting, and apply it to 4,751 androgen receptor (AR)-proximal interacting proteins (AR-PIPs) across three subcellular compartments and an androgen time course. ARs signature coactivator motif, LXXLL, is the most depleted class, while the neighborhood speaks a disorder-resident signaling vocabulary of SUMOylation sites, SPOP and SIAH degrons, and nuclear-import signals. The paradox resolves once incidental motifs are removed. ARs coactivator core forms a small, 9-fold-enriched inner shell within a signaling periphery. The grammar reproduces in an estrogen receptor-beta interactome (r = 0.89) and generalizes to the 5-HT2A serotonin receptor and EGFR. SYNTAX interfaces with the Predictive Proximal Proteome (PPP) Database, a queryable AR-PIP resource.

bioinformatics↗

bioRxiv2026

Neuroendocrine influences on dynamic cerebrovascular function and implications for functional MRI

To fully profile how ovarian hormones interact with cerebrovascular function, it is vital to consider, not just resting physiology, but also dynamic aspects of cerebrovasculature that support neural activity. This study uses hypercapnic cerebrovascular reactivity (CVR) and the visually-evoked haemodynamic response function (HRF) to investigate the influence of menstrual-related changes in oestradiol and progesterone on dynamic aspects of the cerebrovascular system. 20 menstruating females (age mean[SD]=23.01[4.01]years) completed a 3T MRI scanning session during the early follicular, late follicular, and mid-luteal phases of their menstrual cycle. Circulating hormones were measured via blood samples. Simultaneous blood oxygen level dependant (BOLD)-CVR and cerebral blood flow (CBF)-CVR data were collected using a pseudocontinuous arterial spin labelling (pCASL) acquisition using a dual-excitation (DEXI) readout during periods of hypercapnia (5% CO2). The HRF was estimated using a whole brain EPI scan during high-contrast radial checkerboard presentation. Both oestradiol and additional progesterone variance were associated with increased CVR (both BOLD-CVR and CBF-CVR; p<0.001) and altered HRF shape (p<0.005). No statistically significant regional effects were found. A secondary experiment investigated the impact of using either canonical or individually mapped HRF in a standard fMRI processing pipeline; namely, population receptive field (pRF) mapping. Results across phases suggest that neither hormone was associated with pRF size when modelled using a canonical HRF (both p>0.05). However, a significant neuroendocrine influence on pRF sizes was discovered when using individually measured HRFs (p<0.001). This study found evidence that dynamic cerebrovascular functions are sensitive to menstrual-related ovarian hormones, which may be a potential mechanism underlying menstrual symptomatology and has implications for fMRI studies that assume intact neurovascular coupling processes in women, regardless of menstrual staging, to make inferences about neural activity.

neuroscience↗

bioRxiv2024

Endocrine modulation of cortical and retinal blood flow across the menstrual cycle

The ovarian hormones, oestrogen and progesterone, have vaso- and neuroprotective effects, likely due to interactions with the cerebrovascular system. This study investigates their neuroendocrine influence on a range of cerebral and retinal vascular functions across a healthy menstrual cycle. Twenty-six healthy, menstruating females completed imaging sessions and assessment of circulating hormone levels during their early follicular, late follicular, and mid-luteal phase (1-4, 10-12 and 20-22 days after menses onset). Cerebral blood flow (CBF), arterial arrival time (AAT), global oxygen extraction fraction (OEF), cerebrovascular metabolic rate of oxygen (CMRO2), carotid artery radius and carotid pulsatility index (PI) were measured using 3T MRI. Retinal vessel density and blood flow resistance were assessed with optical coherence tomography angiography (OCT-A). Assessed with linear models, increased oestradiol was related to increased global CBF ({chi}2(1)=41.682; p=1.074x10-10). An independent progesterone increase was also associated with increased global CBF ({chi}2(1)=14.979; p=0.0001). In the retina, a relationship was found between oestradiol and decreased retinal blood flow resistance ({chi}2(1)=5.28; p=0.0215), which was primarily driven by centrally localised vessels. This study finds that circulating oestrogen increases blood flow in the eye and brain, while progesterone significantly impacts the brain alone. These effects suggest a potential pathway for neuroprotective mechanisms.

neuroscience↗

bioRxiv2022

Habitat Suitability Modeling and Ecological Forecasting of Northern Goshawk Nesting Habitat

Northern Goshawks (Accipiter gentilis) are dynamic forest raptors often used as a management indicator species in forest management planning. Despite their use as indicators, there is a limited understanding of habitat requirements for goshawks, especially in dry forested landscapes as climate change occurs. We examined goshawk nesting habitat on the Helena-Lewis and Clark National Forest (HLCNF) in central Montana to further understand climate change on goshawk nesting habitat. The HLCNF receives low annual precipitation, making this forest useful to understand climate change in dry forest in structure and ecology. We measured characteristics of nest sites throughout the HLCNF and used principle component analysis to predict important variables for nest trees and nesting habitat for goshawks in this landscape. We also used remote sensing and GIS to create a composite map predicting areas of high, medium and low suitability for nesting habitat for goshawks in the HLCNF. We used the composite map to predict potential impacts of mountain pine beetle (Dendroctonus ponderosae), fire, and climate change to Northern Goshawk habitat in the HLCNF. The best indicators of a chosen nest tree were diameter at breast height, tree height, and tree status, which can be considered indicative of trees preferred for nesting by goshawks. The best indicators for nest forest were canopy closure, slope angle, and slope position, which indicate habitat areas of high suitability for goshawk nesting. Two forecast models where developed based on climate change predictions. After overlapping a projected mountain pine beetle risk map and fire frequency risk map onto the modeled of high suitability goshawk nesting habitat, we calculated that 52 % of modeled high suitability habitat may be at risk for mountain pine beetle blight and 66 % high suitability habitat at risk for frequent wildfires, which will reduce goshawk habitat quality.

ecology↗