Biology subjects

Barry, S.

Publications and source records attributed to Barry, S..

12 recordsLinked to original sources

bioRxiv2026

Aberrant GPX4 processing reveals its critical roles in maintaining ROS homeostasis in Citrus

Glutathione peroxidases (GPXs) are key antioxidant enzymes that contribute to cellular redox homeostasis through reactive oxygen species (ROS) detoxification and modulation of redox signaling pathways. Although GPX functions have been studied in many annual plants, their roles in woody perennial crops remain poorly understood. Here, we characterized the GPX gene family in Citrus sinensis and investigated the function of CsGPX4, the closest homolog of Arabidopsis thaliana AtGPX8 because of its potential role in mediating oxidative stress signaling. Overexpression of CsGPX4 induced an oxidative stress phenotype that includes chlorosis, growth inhibition, cellular degeneration, and elevated intracellular ROS accumulation. Immunoblot and MALDI-TOF analyses showed that CsGPX4 overexpression resulted in a truncated proteoform, while the full length CsGPX4 was able to accumulate in Nicotiana benthamiana, indicating a species-specific post-translational truncation. The truncated CsGPX4 proteoform exhibited an altered subcellular localization shifting from cytoplasmic and nuclear localization to membrane-associated compartment in citrus cells. The truncated form of CsGPX4 had a reduced glutathione peroxidase activity compared to the full-length protein. Proteomic profiling suggested reprogramming of pathways associated with redox detoxification, cytoskeleton organization, hormone signaling, and stress responses. Our study identifies a citrus-specific post-translational regulatory mechanism that modulates CsGPX4 localization and enzymatic activity. This suggests that citrus may employ a species-specific proteolysis processing as a protective mechanism to maintain redox homeostasis during oxidative stress.

plant biology↗

bioRxiv2025

Chaperone AIP Couples mTORC1 Activation and Catabolic Metabolism During Neonatal Development

To grow and divide cells must tightly coordinate anabolic programs with the availability of nutrients and growth factors. This balance is especially critical during postnatal development, when biosynthetic and energetic demands are high, and nutrient supply and neonates have to adapt to periods of fasting. These conditions place acute stress on the proteostasis network, making autophagy essential for nutrient recycling. We found that the chaperone aryl hydrocarbon receptor-interacting protein (AIP) supports both arms of this metabolic balance: promoting anabolic PI3K-AKT signaling for mTORC1 activation and enabling catabolic processes such as proteasomal degradation and autophagy. Loss of AIP causes a severe neonatal metabolic disorder, where affected infants fail to thrive postnatally. Our findings establish AIP as a central regulator of neonatal metabolic adaptation and cellular homeostasis. One Sentence SummaryAIP integrates nutrient sensing and protein recycling to sustain neonatal survival.

developmental biology↗

bioRxiv2024

Biallelic Loss of Molecular Chaperone Molecule AIP Results in a Novel Severe Multisystem Disease Defined by Defective Proteostasis

Children born with deleterious biallelic variants of the chaperone aryl hydrocarbon receptor interacting protein (AIP) have a novel pediatric metabolic disease presenting a severe, complex clinical phenotype characterized by failure to develop following birth. Analysis of Aip knockout mouse embryonic fibroblasts and patient-derived dermal fibroblasts revealed that AIP was required to support proteostasis; including proteasome activity, induction of autophagy and lysosome function. aip knockout zebrafish, recapitulated the phenotype of the children; dying at an early stage of development when autophagy is required to adapt to periods of starvation. Our results demonstrate that AIP plays a crucial role in initiating autophagy and maintaining proteostasis in vitro and in vivo. One Sentence SummaryHomozygous loss of the chaperone AIP results in a novel pediatric disease exhibiting multiple features of a lysosomal storage disease.

molecular biology↗

bioRxiv2024

Temperature drives seagrass recovery across the Western North Atlantic

Climate-driven shifts in herbivores, temperature and nutrient runoff threaten coastal ecosystem resilience. However, our understanding of ecological resilience, particularly for foundation species, remains limited due to a rarity of field experiments that are conducted across appropriate spatial and temporal scales and that investigate multiple stressors. This study aimed to evaluate the resilience of a widespread tropical marine plant (turtlegrass) to disturbances across its geographic range and how this is impacted by environmental gradients in (a)biotic factors. We assessed the resilience (i.e. recovery) of turtlegrass to a simulated disturbance (complete above- and belowground biomass removal) over a year. Contrary to temperate studies, higher temperature generally enhanced seagrass recovery. While nutrients and light availability had minimal impact, combined high levels of nutrients and herbivore grazing (meso and megaherbivore) reduced aboveground recovery. Our results suggest that the resilience of some tropical species, especially in cooler subtropical waters, may initially increase with warming.

ecology↗

bioRxiv2024

A linear ontogeny accounts for the development of naive, memory and tumour-infiltrating regulatory T cells in mice

Foxp3+ Regulatory T cells (Treg) are a subset of CD4+ T cells that play critical functions in maintaining tolerance to self antigens and suppressing autoimmunity, regulating immune responses to pathogens and have a role in the pathophysiology of anti-tumoural immunity. Treg ontogeny is complex since they are generated following recognition of self antigens in the thymus during normal T cell development (thymic Treg), but are also induced from mature conventional T cells when activated by foreign antigen with appropriate additional cues (inducible Treg). How these distinct ontogenic pathways contribute to the maintenance and function of the mature Treg compartment in health and disease remains unclear. Here, we use a combination of fate mapping approaches in mice to map the ontogeny of Treg subsets throughout life and estimate rates of production, loss and self-renewal. We find that naive and effector/memory (EM) Treg subsets exhibit distinct dynamics but are both continuously replenished by de novo generation throughout life. Using an inducible Foxp3-dependent Cre fate reporter system, we show that naive Treg and not conventional T cells, are the predominant precursors of EM Treg in adults. Tonic development of new EM Treg is not influenced by foreign antigens from commensals, rather suggesting a role for self recognition. To investigate the ontogeny of Treg development in malignant disease, we used the same fate reporter systems to characterise the Treg infiltrate of three different model tumours. In all three cases, we found that Treg derived from pre-existing, EM Treg. Together, these results reveal a predominantly linear pathway of Treg development from thymic origin to EM Treg associated with pathophysiology of malignant disease, that is driven by self antigen recognition throughout.

immunology↗

bioRxiv2022

Multi-omic profiling of breast cancer cells uncovers stress MAPK-associated sensitivity to AKT degradation

Over 50% of human tumors display hyperactivation of the serine/threonine kinase AKT. Despite evidence of clinical efficacy, there remains scope to improve upon the therapeutic window of the current generation of AKT inhibitors. Here we report the development of a second-generation AKT degrader, INY-05-040, which outperformed catalytic AKT inhibition with respect to cellular suppression of AKT-driven phenotypes in breast cancer cell lines. A systematic growth inhibition screen across 288 cancer cell lines confirmed a substantially higher potency for INY-05-040 (median GI50adj = 1.1 {micro}M) compared to our first-generation AKT degrader (INY-03-041; median GI50adj = 3.1 {micro}M), with both compounds outperforming catalytic AKT inhibition with GDC-0068 (median GI50adj > 10 {micro}M). Using multi-omic profiling and causal network integration in breast cancer cells, we demonstrate that the enhanced efficacy of INY-05-040 is associated with sustained suppression of AKT signaling, followed by a potent induction of the stress mitogen activated protein kinase (MAPK) c-Jun N-terminal kinase (JNK). Further integration of growth inhibition assays with publicly available transcriptomic, proteomic, and reverse phase protein array (RPPA) measurements established low baseline JNK signaling as a biomarker for breast cancer sensitivity to AKT degradation. Collectively, our study presents a systematic framework for mapping the network-wide signaling effects of therapeutically relevant compounds, and identifies INY-05-040 as a potent pharmacological suppressor of AKT signaling.

cancer biology↗

bioRxiv2022

Predicting catchment suitability for biodiversity at national scales

Biomonitoring of water quality and catchment management are often disconnected, due to mismatching scales. Great effort and money is spent each year on routine reach-scale surveying across many sites, particularly in the UK, and typically with a focus on pre-defined indicators of organic pollution to compare observed vs expected subsets of common macroinvertebrate indicator species. Threatened species are often ignored due to their rarity as are many invasive species, which are seen as undesirable even though they are increasingly common in freshwaters, especially in urban ecosystems. However, these taxa are monitored separately for reasons related to biodiversity concerns rather than for gauging water quality. Repurposing such monitoring data could therefore provide important new biomonitoring tools that can help catchment managers to directly link the water quality that they aim to control with the biodiversity that they are trying to protect. Here we used the England Non-Native and Rare/Protected species records that track these two groups of species as a proof-of-concept for linking catchment scale management of freshwater ecosystems and biodiversity to a range of potential drivers across England. We used national land use (Centre for Ecology and Hydrology land cover map) and water quality indicator (Environment Agency water quality data archive) datasets to predict the presence or absence of 48 focal threatened or invasive species of concern routinely sampled by the English Environment Agency at catchment scale, with a median accuracy of 0.81 area under the receiver operating characteristic curve. A variety of water quality indicators and land-use types were useful in predictions, highlighting that future biomonitoring schemes could use such complementary measures to capture a wider spectrum of drivers and responses. In particular, the percentage of a catchment covered by freshwater was the single most important metric, reinforcing the need for space/habitat to support biodiversity. We show how our method could inform new catchment management approaches, by highlighting how key relationships can be identified and how to understand, visualise and prioritise catchments that are most suitable for restorations or water quality interventions. The scale of this work, in terms of number of species, drivers and locations, represents a step towards a new approach to catchment management that enables managers to link drivers they can control (water quality and land use) to the biota they are trying to protect (biodiversity).

ecology↗

bioRxiv2022

A novel method accounting for predictor uncertainty and model transferability of invasive species distribution models

Predicting novel ranges of non-native species is a critical component to understanding the biosecurity threat posed by pests and diseases on economic, environmental and social assets. Species distribution models (SDMs) are often employed to predict the potential ranges of exotic pests and diseases in novel environments and geographic space. To date, researchers have focused on model complexity, data available for model fitting, the size of the geographic area to be considered and how the choice of model impacts results. These investigations are coupled with considerable examination of how model evaluation methods and test scores are influenced by these choices. An area that remains under-discussed is how to account for uncertainty in predictor selection while also selecting variables that increase a models ability to predict to novel environments (model transferability). Here we propose a novel method to finesse this problem by using multiple simple (bivariate) models to search for the candidate sets of predictor variables that are likely to produce transferable models. Once identified, each set is then used to construct 2-dimensional niche envelopes of pest presence/absence. This process ultimately results in a number of possible models that can be used to predict pest potential distributions, however, rather than relying on a single model, we ensemble these models in an attempt to account for predictor uncertainty. We apply this method to both virtual species and real species data, and find that it generally performs well against conventional approaches for statistically fitting numerous variables in a single model. While our methods only consider simple ecological relationships of species to environmental predictors, they allow for increased model transferability because they reduce the likelihood of over-fitting and collinearity issues. Simple models are also likely to be more conservative (over-predict potential distributions) relative to complex models containing many covariates - making them more appropriate for risk-averse applications such as biosecurity. The approach we have explored transforms a model selection problem, for which there is no true correct answer amongst the typically distal covariates on offer, to one of model uncertainty. We argue that increased model transferability at the expense of model interpretation is perhaps more important for effective rapid predictions and management of non-native species and biological invasions.

ecology↗

bioRxiv2020

Training a neural network to learn other dimensionality reduction removes data size restrictions in bioinformatics and provides a new route to exploring data representations

High dimensionality omics and hyperspectral imaging datasets present difficult challenges for feature extraction and data mining due to huge numbers of features that cannot be simultaneously examined. The sample numbers and variables of these methods are constantly growing as new technologies are developed, and computational analysis needs to evolve to keep up with growing demand. Current state of the art algorithms can handle some routine datasets but struggle when datasets grow above a certain size. We present a training deep learning via neural networks on non-linear dimensionality reduction, in particular t-distributed stochastic neighbour embedding (t-SNE), to overcome prior limitations of these methods. One Sentence SummaryAnalysis of prohibitively large datasets by combining deep learning via neural networks with non-linear dimensionality reduction.

bioinformatics↗

bioRxiv2020

Mutational inactivation of Apc in the intestinal epithelia compromises cellular organisation

The tumour suppressor adenomatous polyposis coli (Apc) regulates diverse effector pathways essential for cellular homeostasis. Truncating mutations in Apc, leading to the loss of its Wnt pathway and microtubule regulatory domains, are oncogenic in human and murine intestinal epithelia and drive malignant transformation. Whereas uncontrolled proliferation via Wnt pathway deregulation is an unequivocal consequence of oncogenic Apc mutations, it is not known whether loss of its other control systems contribute to tumorigenesis. Here we employ in vitro models of tumorigenesis to unmask the molecular barriers erected by Apc that maintain normal epithelial homeostasis in the murine intestinal epithelia. We determine that (i) enterocyte proliferation, (ii) microtubule dynamics and (iii) epithelial morphology are controlled by three independent molecular pathways, each corrupted by oncogenic Apc mutations. The key result of the study is to establish that Apc regulates three individual biological fates in the intestinal epithelia, through three distinct effector pathways, a significant advance to our understanding of normal tissue homeostasis, the molecular architecture of epithelial tissue and the aetiology of intestinal cancer.

cell biology↗

bioRxiv2019

Targeting DNA damage response and Replication Stress in Pancreatic Cancer

Continuing recalcitrance to therapy cements pancreatic cancer (PC) as the most lethal malignancy, which is set to become the second leading cause of cancer death in our society. We interrogated the transcriptome, genome, proteome and functional characteristics of 61 novel PC patient-derived cell lines to define novel therapeutic strategies targeting the DNA damage response (DDR) and replication stress. We show that patient-derived cell lines faithfully recapitulate the epithelial component of pancreatic tumors including previously described molecular subtypes. Biomarkers of DDR deficiency, including a novel signature of homologous recombination deficiency, co-segregates with response to platinum and PARP inhibitor therapy in vitro and in vivo. We generated a novel signature of replication stress with potential clinical utility in predicting response to ATR and WEE1 inhibitor treatment. Replication stress and DDR deficiency are independent of each other, creating opportunities for therapy in DDR proficient PC, and post-platinum therapy.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC=\"FIGDIR/small/713545v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (47K):\norg.highwire.dtl.DTLVardef@106f2b8org.highwire.dtl.DTLVardef@1294d22org.highwire.dtl.DTLVardef@86f5d3org.highwire.dtl.DTLVardef@751e13_HPS_FORMAT_FIGEXP M_FIG C_FIG STATEMENT OF SIGNIFICANCEWe define therapeutic strategies that target subgroups of PC using novel signatures of DNA damage response deficiency and replication stress. This potentially offers patients with DNA repair defects therapeutic options outside standard of care platinum chemotherapy and is being tested in clinical trials on the Precision-Panc platform.

cancer biology↗

bioRxiv2017

MatchMiner: An open source computational platform for real-time matching of cancer patients to precision medicine clinical trials using genomic and clinical criteria

BackgroundMolecular profiling of cancers is now routine at many cancer centers, and the number of precision cancer medicine clinical trials, which are informed by profiling, is steadily rising. Additionally, these trials are becoming increasingly complex, often having multiple arms and many genomic eligibility criteria. Currently, it is a challenging for physicians to match patients to relevant clinical trials using the patients genomic profile, which can lead to missed opportunities. Automated matching against uniformly structured and encoded genomic eligibility criteria is essential to keep pace with the complex landscape of precision medicine clinical trials.\n\nResultsTo meet these needs, we built and deployed an automated clinical trial matching platform called MatchMiner at the Dana-Farber Cancer Institute (DFCI). The platform has been integrated with Profile, DFCIs enterprise genomic profiling project, which contains tumor profile data for >20,000 patients, and has been made available to physicians across the Institute. As no current standard exists for encoding clinical trial eligibility criteria, a new language called Clinical Trial Markup Language (CTML) was developed, and over 178 genomically-driven clinical trials were encoded using this language. The platform is open source and freely available for adoption by other institutions.\n\nConclusionMatchMiner is the first open platform developed to enable computational matching of patient-specific genomic profiles to precision cancer medicine clinical trials. Creating MatchMiner required developing clinical trial eligibility standards to support genome-driven matching and developing intuitive interfaces to support practical use-cases. Given the complexity of tumor profiling and the rapidly changing multi-site nature of genome-driven clinical trials, open source software is the most efficient, scalable, and economical option for matching cancer patients to clinical trials.

bioinformatics↗