Biology subjects

Howard, G.

Publications and source records attributed to Howard, G..

4 recordsLinked to original sources

bioRxiv2025

Structural Determinants and Biochemical Characterization of LORELEI as a GPI-Anchored Protein

Glycosylphosphatidylinositol-anchored proteins play critical roles in plant development, reproduction, and environmental responses. However, their biochemical characterization in plants remains limited. LORELEI, a putative glycosylphosphatidylinositol-anchored protein involved in pollen tube reception and early seed development in Arabidopsis thaliana, has lacked direct biochemical evidence confirming its glycosylphosphatidylinositol anchoring. This study employed biochemical approaches to validate LORELEI as a glycosylphosphatidylinositol-anchored protein. We demonstrate that ectopic expression of wild-type LORELEI fused to a reporter protein in vegetative tissues associates with a detergent-resistant membrane fraction and is sensitive to glycosylphosphatidylinositol-specific cleavage enzymes, thereby confirming that it is a glycosylphosphatidylinositol-anchored protein. Moreover, we show that mutations in the {omega}-sites or the glycosylphosphatidylinositol attachment signal of LORELEI disrupt its membrane localization, highlighting the necessity of these structural elements for proper glycosylphosphatidylinositol anchoring. Analysis of a reporter-fused LORELEI protein in the loss of function mutant of glycosylphosphatidylinositol 8, which encodes the catalytic subunit of glycosylphosphatidylinositol transamidase complex involved in glycosylphosphatidylinositol anchor addition, results in the appearance of prominent higher molecular weight bands, further supporting its role in glycosylphosphatidylinositol anchoring of the LORELEI protein. This study provides direct biochemical evidence confirming LORELEI as a glycosylphosphatidylinositol-anchored protein and sheds light on the structural determinants required for its glycosylphosphatidylinositol anchoring. Additionally, our study demonstrates that heterologous ectopic expression of LORELEI in vegetative tissues provides a viable alternative for the biochemical characterization of glycosylphosphatidylinositol-anchored proteins predominantly expressed in hard-to-access and small-sized female gametophytes. Our findings underscore the role of GPI anchoring in membrane localization and biosynthesis of GPI-anchored proteins in plants.

plant biology↗

bioRxiv2021

Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules

While acquired chemoresistance is recognized as a key challenge to treating many types of cancer, the dynamics with which drug sensitivity changes after exposure are poorly characterized. Most chemotherapeutic regimens call for repeated dosing at regular intervals, and if drug sensitivity changes on a similar time scale then the treatment interval could be optimized to improve treatment performance. Theoretical work suggests that such optimal schedules exist, but experimental confirmation has been obstructed by the difficulty of deconvolving the simultaneous processes of death, adaptation, and regrowth taking place in cancer cell populations. Here we present work characterizing dynamic changes in sensitivity to the chemotherapeutic doxorubicin in three breast cancer cell lines subjected to treatment schedules varying in concentration, interval between pulse treatments, and number of sequential pulse treatments. Cell populations are monitored longitudinally through automated imaging for 600-800 hours, and this data is used to calibrate a family of cancer growth models derived from the bi-exponential model which characterizes resistant and sensitive subpopulations. We identify a model incorporating both a period of growth arrest in surviving cells and a delay in the death of chemosensitive cells which outperforms the original bi-exponential growth model in Akaike Information Criterion based model selection, and use the calibrated model to quantify the performance of each drug schedule. We find that the inter-treatment interval is a key variable in determining the performance of sequential dosing schedules and identify an optimal retreatment time for each cell line which extends regrowth time by 40%-106%, demonstrating that the time scale of changes in chemosensitivity following doxorubicin exposure allows optimization of drug scheduling by varying this inter-treatment interval.

cancer biology↗

bioRxiv2020

AtPIG-S, a predicted Glycosylphosphatidylinositol Transamidase Subunit, is critical for pollen tube growth in Arabidopsis

BackgroundGlycosylphosphatidylinositol (GPI) addition is one of the several post-translational modifications to proteins that increase their affinity for membranes. In eukaryotes, the GPI transamidase complex (GPI-T) catalyzes the attachment of pre-assembled GPI anchors to GPI-anchored proteins (GAPs) through a transamidation reaction. A mutation in AtGPI8 (gpi8-2), the putative catalytic subunit of GPI-T in Arabidopsis, is transmitted normally through the female gametophyte (FG), indicating the FG tolerates loss of GPI transamidation. In contrast, gpi8-2 almost completely abolishes male gametophyte (MG) function. Still, the unexpected finding that gpi8-2 FGs function normally requires further investigation. Additionally, specific developmental defects in the MG caused by loss of GPI transamidation remain poorly characterized. ResultsHere we investigated the effect of loss of AtPIG-S, another GPI-T subunit, in both gametophytes. Like gpi8-2, we showed that a mutation in AtPIG-S (pigs-1) disrupted synergid localization of LORELEI (LRE), a putative GAP critical for pollen tube reception by the FG, yet is transmitted normally through the FG. Conversely, pigs-1 severely impaired male gametophyte (MG) function during pollen tube emergence and growth in the pistil. A pPIGS:PIGS-GFP transgene complemented these MG defects and enabled generation of pigs-1/pigs-1 seedlings, but seemingly failed to rescue the function of AtPIG-S in the sporophyte, as pigs-1/pigs-1, pPIGS:PIGS-GFP seedlings died soon after germination. ConclusionsCharacterization of pigs-1 provided further evidence that the FG tolerates loss of GPI transamidation more than the MG and that the MG compared to the FG may be a better haploid system to study the role of GPI-anchoring. pigs-1 pollen develops normally and thus represent a tool in which GPI anchor biosynthesis and transamidation of GAPs have been uncoupled, offering a potential way to study free GPI in plant development. While previously reported male fertility defects of GPI biosynthesis mutants could have been due either to loss of GPI or GAPs lacking the GPI anchor, our results clarified that the loss of mature GAPs underlie male fertility defects of GPI-deficient pollen grains, as pigs-1 is defective only in the downstream transamidation step. Our study also provided further evidence that GPI transamidation is essential in seedling development.

plant biology↗

bioRxiv2019

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations from exponential growth only at higher densities due to limited resources such as space and nutrients. However, recent pre-clinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models however, tumor growth data is limited by the lower limit of detection (i.e. a measurable lesion) and confounding variables, such as tumor microenvironment and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to consider the small number of cells in this low-density regime and use the moment approach for stochastic parameter estimation to calibrate the stochastic growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells depends on cell number. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging tumors and relapse.\n\nAuthor SummaryThe growth kinetics of cancer cells at very low cell densities are of utmost clinical importance as the ability of a small number of newly transformed or surviving cells to grow exponentially and thus, to \"take off\" underlies tumor formation and relapse after treatment. Mathematical models of stochastic tumor cell growth typically assume a stochastic birth-death process of cells impacted by limited nutrients and space when cells reach high density, resulting in the widely accepted logistic growth model. Here we present an in-depth investigation of alternate growth models adopted from ecology to describe potential deviations from a simple cell autonomous birth-death model at low cell densities. We show that our stochastic modeling framework is robust and can be used to identify the underlying structure of stochastic growth trajectories from both simulated and experimental data taken from a controlled in vitro setting in which we can capture data from the relevant low cell density regime. This work suggests that the assumption of cell autonomous proliferation via a constant exponential growth rate at low cell densities may not be appropriate for all cancer cell growth dynamics. Consideration of cooperative behavior amongst tumor cells in this regime is critical for elucidating strategies for controlling tumor cell growth.

cancer biology↗