Biology subjects

Mason, M.

Publications and source records attributed to Mason, M..

10 recordsLinked to original sources

bioRxiv2026

Ancient environmental DNA reveals the distinct fingerprints of whaling and climate change on Antarctic marine biodiversity

The Southern Ocean is a disproportionately large contributor to Earth system processes, playing a crucial role in the global transport of carbon, oxygen and heat. It also hosts enormous seasonal biological productivity that supports diverse endemic marine biodiversity. Industrial whaling in the first half of the 20th century and recent human-driven climate change have both profoundly altered Antarctic ecosystems, but ecological surveys of these impacts are limited to well-known taxa in the short period since monitoring began. Here, we analysed five sediment records to reconstruct more than two centuries of ecosystem change across the Western Antarctic Peninsula, spanning periods before and during major human impacts. Environmental DNA metabarcoding of these records revealed substantial biodiversity shifts, with change accelerating in recent decades. We find a significant role for both climate change and whaling in restructuring communities, identifying unique variance in whole-community change explained by each driver. Moreover, we find a negative association between whaling and metazoan families which feed from the water column, suggesting that pre-whaling ecosystems had greater pelagic productivity. Overall, our results reveal baseline Antarctic biodiversity from long before observational records and identify a distinct fingerprint of human drivers in this fragile, rapidly changing ecosystem.

ecology↗

bioRxiv2026

Functional characterization of bat limb regulatory elements

Bats are the only mammals capable of powered flight and roost head-down. However, the molecular changes shaping bat limbs remain largely unknown. Here, we used comparative functional genomics coupled with mouse-bat sequence swaps to identify key regulatory elements important in bat limb development. We generated and compared bat and mouse forelimb and hindlimb genomic datasets at key wing developmental timepoints, followed by mouse enhancer assays to characterize sequences showing differences between species. We then swapped six mouse enhancer sequences with their corresponding bat sequences, obtaining a variety of bat limb associated phenotypes, including ossification delay, longer digits, thicker skin and symmetrical hindlimb digits. Our work provides a genomic catalog of genes and regulatory elements involved in bat limb development and through extensive characterization in mice shows how changes in regulatory elements lead to small phenotypic changes that together contribute to bat limb development.

developmental biology↗

bioRxiv2024

Genetic barcodes for ash (Fraxinus) species and generation of new wide hybrids

Native ash tree species in Europe and North America are being devastated by ash dieback and the emerald ash borer, respectively. As worldwide ash species differ in their level of susceptibility to these threats, hybrid breeding may allow resistance to be transferred among species. However, we do not know the extent to which distantly related ash species can be crossed, and many ash species are difficult to identify from morphology alone leading to some mislabelling in living collections. Here, we develop a genetic barcode system for the identification of Fraxinus species based on three low-copy-number protein coding genes. We also conduct experimental crosses among ash species in different sections. Our barcodes are effective in identifying ash samples to sectional level and in some cases to species level, and can also identify hybrids. They highlight that F. mandshurica, F. platypoda and F. chiisanensis may be frequently mistaken for one another in living collections. We succeeded in generating ten wide hybrid plants: two of section Melioides (species: F. pennsylvanica) {square} section Fraxinus (species: F. excelsior) and eight of section Ornus (species unclear) {square} section Fraxinus (species: F. excelsior). One hybrid from each of our crosses has survived natural infection with the ash dieback pathogen in Ireland. We also discovered a hybrid between section Melioides (species: F. latifolia) {square} section Fraxinus (species: F. excelsior) formed spontaneously in the ash collection at Kew. Our findings facilitate the deployment of global ash species diversity in response to alien pests and pathogens. Societal impact statementThe world-wide diversity of ash trees includes genetic information encoding resistance to the ash dieback fungus and the emerald ash borer beetle, which are currently devastating ash populations in Europe and North America. In order to mobilise this genetic diversity in conventional breeding programmes we need to be able to accurately identify ash species from around the world, and cross them with one another. Here, we present a genetic barcoding system for ash species, and a series of hybridisation experiments between European ash and other species. Two of the hybrids show early promise against ash dieback.

plant biology↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2022

Structures of human Malic Enzyme 3

Malic enzymes (ME1, ME2, and ME3) are involved in cellular energy regulation, redox homeostasis, and biosynthetic processes, through the production of pyruvate and reducing agent NAD(P)H. Recent studies have implicated the third and least well-characterized isoform, mitochondrial NADP+-dependent malic enzyme 3 (ME3), as a therapeutic target for pancreatic cancers. Here, we utilized an integrated structure approach to capture the structures of ME3 in various ligand binding states. ME3 exists as a stable tetramer and its dynamic Domain C is critical for activity. Catalytic assay results reveal that ME3 is a non-allosteric enzyme and does not require modulators for activity while structural analysis suggests that the inner stability of ME3 domain A relative to ME2 disables allostery in ME3. With structural information available for all three malic enzymes, the foundation has been laid to understand the structural and biochemical differences of these enzymes and could aid in the development of specific malic enzyme small molecule drugs.

molecular biology↗

bioRxiv2021

Flow cytometry method for absolute counting and single-cell phenotyping of mycobacteria

Detection and accurate quantitation of viable Mycobacterium tuberculosis is fundamental to understanding mycobacterial pathogenicity, tuberculosis (TB) disease progression and outcomes; TB transmission; drug action, efficacy and drug resistance. Despite this importance, methods for determining numbers of viable bacilli are limited in accuracy and precision owing to inherent characteristics of mycobacterial cell biology - including the tendency to clump, and "differential" culturability - and technical challenges consequent on handling an infectious pathogen under biosafe conditions. We developed an absolute counting method for mycobacteria in liquid cultures using a bench-top flow cytometer, and the low-cost fluorescent dyes Calcein-AM (CA) and SYBR-gold (SG). During exponential growth CA+ cell counts are highly correlated with CFU counts and can be used as a real-time alternative to simplify the accurate standardisation of inocula for experiments. In contrast to CFU counting, this method can detect and enumerate cell aggregates in samples, which we show are a potential source of variance and bias when using established methods. We show that CFUs comprise a sub-population of intact, metabolically active mycobacterial cells in liquid cultures, with CFU-proportion varying by growth conditions. A pharmacodynamic application of the flow cytometry method, exploring kinetics of fluorescent probe defined subpopulations compared to CFU is demonstrated. Flow cytometry derived Mycobacterium bovis BCG time-kill curves differ for rifampicin and kanamycin versus isoniazid and ethambutol, as do the relative dynamics of discrete morphologically-distinct subpopulations of bacilli revealed by this high-throughput single-cell technique.

microbiology↗

bioRxiv2021

Microglia become hypofunctional and release metalloproteases and tau seeds after phagocytosing live neurons with P301S tau aggregates

The microtubule-associated protein tau aggregates in multiple neurodegenerative diseases, causing inflammation and changing the inflammatory signature of microglia by unknown mechanisms. We have shown that microglia phagocytose live neurons containing tau aggregates cultured from P301S tau transgenic mice due to neuronal tau aggregate-induced exposure of the eat me signal phosphatidylserine. Here we show that after phagocytosis, microglia become hypophagocytic while releasing seed-competent insoluble tau aggregates. These microglia activate acidic {beta}-galactosidase, and release senescence-associated cytokines and matrix remodeling enzymes alongside tau, indicating a senescent phenotype. In particular, the marked NF{kappa}B-induced activation of matrix metalloprotease 3 (MMP3/stromelysinl) was replicated in the brains of P301S mutant tau transgenic mice, and in human brains from tauopathy patients. These data show that microglia that have been activated to ingest live neurons with tau aggregates behave hormetically, becoming hypofunctional while acting as vectors of tau aggregate spreading.

neuroscience↗

bioRxiv2020

Genetic program activity delineates risk, relapse, and therapy responsiveness in Multiple Myeloma

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to their previous therapies. Although many therapies exist with diverse mechanisms of action, it is not yet clear how the differences in MM biology across patients impacts the likelihood of success for existing therapies and those in the pipeline. Therefore, we not only need the ability to predict which patients are at high risk for disease progression, but also a means to understand the mechanisms underlying their risk. We hypothesized that knowledge of the biological networks that give rise to MM, specifically the transcriptional regulatory network (TRN) and the mechanisms by which mutations impact gene regulation, would enable improved predictions of disease progression and actionable insights for treatment. Here we present a method to infer TRNs from multi-omics data and apply it to the generation of a MM TRN that links chromosomal abnormalities and somatic mutations to downstream effects on gene expression via perturbation of transcriptional regulators. We find that 141 genetic programs underlie the disease and that the activity profile of these programs fall into one of 25 distinct transcriptional states. These transcriptional signatures prove to be more predictive of outcomes than do mutations and reveal plausible mechanisms for relapse, including the establishment of an immuno-suppressive microenvironment. Moreover, we observe subtype-specific vulnerabilities to interventions with existing drugs and motivate the development of new targeted therapies that appear especially promising for relapsed refractory MM.

systems biology↗

bioRxiv2019

Oncogenic Mutations in Histologically Normal Endometrium: The New Normal?

The presence of somatic driver mutations in endometriosis has previously been believed to represent early events in transformation, however our group and others have described such mutations in roughly one-third of cases of deep infiltrating or iatrogenic endometriosis. These forms of endometriosis rarely progress to malignancy. Recent studies have also shown somatic driver mutations in normal skin, blood, peritoneal washings, and esophageal epithelium. Such findings prompt speculation on whether such mutations exist in the eutopic endometrium - the likely tissue of origin of endometriosis. In the current study we investigated the presence of somatic driver mutations in histologically normal endometrium from women lacking evidence of gynecologic malignancy or endometrial hyperplasia. Twenty-five women who underwent hysterectomies and 85 women who underwent endometrial biopsies were included in this study. Formalin-fixed, paraffin-embedded tissue specimens were analyzed by means of targeted sequencing followed by orthogonal validation with droplet digital PCR. PTEN and ARID1A immunohistochemistry (IHC) was also performed as surrogates for inactivating mutations in the respective genes. Overall, we observed somatic driver-like events in over 50% of histologically normal endometrial samples analyzed, which included hotspot mutations in KRAS, PIK3CA, and FGFR2 as well as PTEN-loss by IHC. Analysis of anterior and posterior samplings collected from women who underwent hysterectomies is consistent with the presence of somatic driver mutations within clonal pockets spread throughout the uterus. The prevalence of such oncogenic mutations also increased with age (OR: 1.05 (95% CI: 1.00 - 1.10), p = 0.035). These findings have implications on our understanding of aging and so-called "normal tissues", thereby necessitating caution in the utilization of mutation-based early detection tools for endometrial or other cancers.

pathology↗

bioRxiv2017

Community assessment of cancer drug combination screens identifies strategies for synergy prediction

The effectiveness of most cancer targeted therapies is short lived since tumors evolve and develop resistance. Combinations of drugs offer the potential to overcome resistance, however the number of possible combinations is vast necessitating data-driven approaches to find optimal treatments tailored to a patients tumor. AstraZeneca carried out 11,576 experiments on 910 drug combinations across 85 cancer cell lines, recapitulating in vivo response profiles. These data, the largest openly available screen, were hosted by DREAM alongside deep molecular characterization from the Sanger Institute for a Challenge to computationally predict synergistic drug pairs and associated biomarkers. 160 teams participated to provide the most comprehensive methodological development and subsequent benchmarking to date. Winning methods incorporated prior knowledge of putative drug target interactions. For >60% of drug combinations synergy was reproducibly predicted with an accuracy matching biological replicate experiments, however 20% of drug combinations were poorly predicted by all methods. Genomic rationale for synergy predictions were identified, including antagonism unique to combined PIK3CB/D inhibition with the ADAM17 inhibitor where synergy is seen with other PI3K pathway inhibitors. All data, methods and code are freely available as a resource to the community.

bioinformatics↗