Biology subjects

Woodard, J.

Publications and source records attributed to Woodard, J..

4 recordsLinked to original sources

bioRxiv2026

Local interaction networks reconstructed from global biodiversity data improve pollinator restoration decision making

Global pollinator declines threaten the health of ecosystems and food systems, underscoring the urgency of conservation actions such as habitat restoration. However, data gaps on plant use among pollinators continue to limit reliable design of restoration plant mixes. To address this, we present NECTAR (Network-Enhanced Conservation Tool for Analysis and Recommendation), a new modular framework that integrates multiple data modalities - including species distributions, phenological metrics, and phylogenetic data - to infer flower visitation and host plant interactions from spatial, temporal, and phylogenetic overlap, generating spatially explicit plant-insect interaction networks that guide planting recommendations for pollinator habitat restoration. We demonstrate the utility of NECTAR by generating a large plant-insect metaweb across California, comprising 2,473,729 spatially explicit interactions that included 3,792 pollinator species and 4,363 native plant species. NECTAR achieved high interaction recall across withheld interactions and independent datasets, substantially outperforming null models and matching or exceeding values reported in comparable studies. NECTAR's data-driven plant mix recommendations are predicted to support up to 2.4 times more pollinator species compared to existing resources and random selection of plants. This optimization facilitates the inclusion of multiple goals and constraints, and provides complementary decision-making information to existing resources. NECTAR offers a scalable, evidence-based framework for translating increasingly available global biodiversity data into locally actionable restoration guidance, with broad potential to improve pollinator habitat restoration worldwide.

ecology↗

bioRxiv2025

Thermodynamics and selection of the plasminogen activator inhibitor-1 latency transition

Plasminogen activator inhibitor-1 (PAI-1), like other serine protease inhibitors (SERPINs), exists in a functionally active metastable conformation. Unlike other SERPINs, PAI-1 undergoes a relatively rapid rearrangement to a lower energy latent conformation. We employ deep mutational scanning (DMS) to simultaneously probe the effects of nearly all single amino acid substitutions (92%) in PAI-1 on its latency transition as well as its ability to inhibit its canonical protease target, urokinase-type plasminogen activator (uPA). The DMS results are interpreted in the context of variant effect predictors (EVE, AlphaMissense, and CPT) and protein stability predictors (EvoEF and FoldX), as well as the evolutionary conservation of the PAI-1 sequence space across extant vertebrate species. We demonstrate that while variant effect predictors can generally partition PAI-1 as functional or non-functional with respect to uPA inhibition, they perform poorly when attempting to discriminate the effects of PAI-1 variants on its latency transition. However, by employing protein stability predictors, we demonstrate that the PAI-1 latency transition is most likely driven by changes in the energy barrier to the latency transition. Finally, we show that PAI-1s ability to inhibit uPA, as well as its thermodynamic instability in its active conformation are both under purifying selection that limits the sequence space available to PAI-1. These findings suggest that DMS of collateral fitness effects, including PAI-1s latency transition, may be better interpreted in contexts other than variant effect predictors, including protein thermodynamics and evolution.

biochemistry↗

bioRxiv2024

Polyglutamine expansion induced dynamic misfolding of Androgen Receptor

Spinal bulbar muscular atrophy (SBMA) is caused by a polyglutamine expansion (pQe) in the N-terminal transactivation domain of human androgen receptor (AR-NTD), resulting in a combination of toxic gain- and loss-of-function mechanisms. The structural basis of these processes has not been resolved due to the disordered nature of the NTD, which hinders experimental analyses of its detailed conformations. Here, using extensive computational modelling, we show that AR-NTD forms dynamic compact regions, which upon pQe re-organize dynamically, mediated partly by direct pQ interaction with the Androgen N-Terminal Signature (ANTS) motif. The altered dynamics of the NTD result in a perturbation of interdomain interactions, with potential implications for binding of the receptor protein to its response element. Oligomeric aggregation of the dynamic misfolded NTD exposes pQe, but blocks tau-5 and the FQNLF motif, which could lead to aberrant receptor transcriptional activity. These observations suggest a structural mechanism for AR dysfunction in SBMA.

pathology↗

bioRxiv2019

A case of mistaken identity: structurally similar ligand inhibits Thymidylate Kinase causing reversible filamentation of E. coli

The relationship between sequence variation and phenotype is poorly understood. Here we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in Dihydrofolate Reductase (DHFR). We find that partial loss of DHFR activity causes reversible filamentation despite SOS response indicative of DNA damage, in contrast to thymineless death (TLD) achieved by complete inhibition of DHFR activity by high concentrations of antibiotic Trimethoprim. This phenotype is triggered by a disproportionate drop in intracellular dTTP, which could not be explained by drop in dTMP based on the Michaelis-Menten like in vitro activity curve of Thymidylate Kinase (Tmk), a downstream enzyme that phosphorylates dTMP to dTDP. Instead, we show that a highly cooperative (Hill coefficient 2.5) in vivo activity of Tmk is the cause of suboptimal dTTP levels. dTMP supplementation rescues filamentation and restores in vivo Tmk kinetics to Michaelis-Menten. Overall, this study highlights the important role of cellular environment in sculpting enzymatic kinetics with system level implications for bacterial phenotype.

microbiology↗