Biology subjects

O'Donnell, R.

Publications and source records attributed to O'Donnell, R..

5 recordsLinked to original sources

bioRxiv2026

Once in a blue moon: an unexpected evolutionary route to blue floral pigmentation in orchids

Blue flowers are rare in the hyperdiverse orchid family, and the genetic mechanisms enabling their blue delphinidin-based pigmentation remain poorly understood. Within the Australian orchid subtribe Caladeniinae (~350 spp.), repeated transitions from maroon to blue flowers, followed by reversions to maroon, provide a unique opportunity to investigate blue flower evolution. Using phylotranscriptomics, anthocyanin profiling, molecular evolutionary analyses, and gene expression data from 51 species, we reconstructed the genetic changes associated with these transitions. Despite its near-universal role in delphinidin biosynthesis across flowering plants, unexpectedly, we found no evidence for a functional CYP75A-mediated flavonoid 3'5'-hydroxylase (F3'5'H) pathway. Instead, blue-flowered species possess a duplicated CYP75B lineage gene (CYP75B-D) with apparent 5'-hydroxylase activity, a derived D-type dihydroflavonol reductase (DFR), and a distinct anthocyanin biosynthetic pathway co-expression pattern. Phylogenetic analyses suggest that the D-type DFR pre-dated blue flower evolution, representing a permissive evolutionary shift later coupled with the evolution of CYP75B-D. Notably, blue flower evolution coincided with repeated pollinator transitions and major palaeoenvironmental change during the Middle Miocene. Together, these findings reveal an unexpected route to blue floral pigmentation and suggest that its evolution arose through the interaction of molecular innovation, regulatory evolution, and ecological opportunity.

evolutionary biology↗

bioRxiv2021

Computational Simulation of 4-D Micro-Circular Network in Zebrafish Tail Amputation and Regeneration

Wall shear stress (WSS) in the micro-vasculature contributes to biomechanical cues that regulate mechanotransduction underlying vascular development, regeneration, and homeostasis. We hereby elucidate the interplay between hemodynamic shear forces and luminal remodeling in response to vascular injury and regeneration in the zebrafish model of tail amputation. Using the transgenic Tg(fli1:eGFP; Gata1:ds-red) line, we were able to track the enhanced green-fluorescent protein (eGFP)-labeled endothelial lining of the 3-D microvasculature for post-image segmentation and reconstruction of fluid domain for computational fluid dynamics (CFD) simulation. At 1 day post amputation (dpa), dorsal aorta (DA) and posterior cardinal vein (PCV) were severed, and vasoconstriction developed in the dorsal longitudinal anastomotic vessel (DLAV) with a concomitant increase in WSS in the segmental vessels (SV) proximal to the amputation site and a decrease in WSS in SVs distal to amputation. Simultaneously, we observed angiogenesis commencing at the tips of the amputated DLAV and PCV where WSS was minimal in the absence of blood flow. At 2 dpa, vasodilation occurred in a pair of SVs proximal to amputation, resulting in increased flow rate and WSS, whereas in the SVs distal to amputation, WSS normalized to the baseline. At 3 dpa, the flow rate in the arterial SV proximal to amputation continued to rise and merged with DLAV that formed a new loop with PCV. Thus, our CFD modeling uncovered a well-coordinated micro-vascular adaptation process following tail amputation, accompanied by the rise and fall of WSS and dynamic changes in flow rate during vascular regeneration.

bioengineering↗

bioRxiv2021

The Memory for Latent Representations: An Account of Working Memory that Builds on Visual Knowledge for Efficient and Detailed Visual Representations

Visual knowledge obtained from our lifelong experience of the world plays a critical role in our ability to build short-term memories. We propose a mechanistic explanation of how working memories are built from the latent representations of visual knowledge and can then be reconstructed. The proposed model, Memory for Latent Representations (MLR), features a variational autoencoder with an architecture that corresponds broadly to the human visual system and an activation-based binding pool of neurons that binds items attributes to tokenized representations. The simulation results revealed that the shapes of familiar items can be encoded and retrieved efficiently from latents in higher levels of the visual hierarchy. On the other hand, novel patterns that are completely outside the training set can be stored from a single exposure using only latents from early layers of the visual system. Moreover, a given stimulus in working memory can have multiple codes, representing specific visual features such as shape or color, in addition to categorical information. Finally, we validated our model by testing a series of predictions against behavioral results obtained from WM tasks. The model provides a compelling demonstration of how visual knowledge yields compact visual representation for efficient memory encoding.

neuroscience↗

bioRxiv2020

Novel mTORC1 inhibitors kill Glioblastoma stem cells

Glioblastoma Multiforme (GBM) is an aggressive tumor of the brain, with an average post-diagnosis survival of 15 months. GBM stem cells (GBMSC) resist the standard-of-care therapy, temozolomide, and are considered a major contributor to tumor resistance. mTORC1 regulates cell proliferation and has been shown by others to have reduced activity in GBMSC. We recently identified a novel chemical series of human-safe piperazine-based brain-penetrant mTORC1-specific inhibitors. We assayed piperazine-mTOR binding strength by two biophysical measurements-- biolayer interferometry and field effect biosensing, and these confirmed each other and demonstrated a structure-activity relationship. Since mTORC1 is reduced in human GBMSC, and as mTORC1 inhibitors have been tested in previous GBM clinical trials, we tested the killing potency of the tightest-binding piperazines and observed these were potent GBMSC killers. GBMSCs are resistant to the standard-of-care temozolomide therapy--but temozolomide supplemented with tight-binding piperazine meclizine and flunarizine greatly enhanced GBMSC death over temozolomide alone. Lastly, we investigated IDH1-mutated GBMSC mutations that are known to affect mitochondrial and mTORC1 metabolism, the tight-binding Meclizine provoked ‘synthetic lethality’ in IDH1-mutant GBMSCs. These data tend to support a novel clinical strategy for GBM, i.e. the co-administration of meclizine or flunarizine as adjuvant therapy in the treatment of GBM, and IDH1-mutant GBM.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2019

β-Caryophyllene Enhances the Transcriptional Upregulation of Cholesterol Biosynthesis in Breast Cancer Cells

{beta}-caryophyllene (BCP) exhibits anti-proliferative properties in cancer cells. Here, we examine the hypothesis that BCP induces membrane remodeling. Our data show that high concentrations of BCP increase membrane permeability of human breast cells (hBrC) causing detachment and cell death. At a sub-lethal concentration of BCP, we show that BCP induces a striking upregulation of genes involved in cholesterol biosynthesis, including the gene that encodes for HMGCoA reductase (HMGCR), the rate-determining step in cholesterol biosynthesis. In addition, stearoyl-CoA desaturase (SCD) is also upregulated which would lead to the enhanced formation of monounsaturated fatty acids, specifically oleate and palmitoleate from stearoyl CoA and palmitoyl CoA, respectively. These fatty acids are major components of membrane phospholipids and cholesterol esters. Together, these data suggest that cells respond to BCP by increasing the synthesis of components found in membranes. These responses could be viewed as a repair mechanism and/or as a mechanism to mount resistance to the cytotoxic effect of BCP. Blocking HMGCR activity enhances the cytotoxicity of BCP, suggesting that BCP may provide an additional therapeutic tool in controlling breast cancer cell growth.

cancer biology↗