Biology subjects

Watson, C.

Publications and source records attributed to Watson, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Biochemical characterisation of fungal bioluminescence enzymes reveals substrate inhibition and secondary turnover of 3-hydroxyhispidin by H3H

The fungal bioluminescence pathway enables autonomous light production from caffeic acid and has emerged as a versatile platform for bioimaging and synthetic biology. However, biochemical characterisation of its core enzymes remains limited. Here, we establish recombinant purification and quantitative in vitro characterisation of fungal luciferase (Luz) and hispidin-3-hydroxylase (H3H) homologues from Neonothopanus nambi and Mycena chlorophos. Complementary luminescence and mass spectrometry-based assays revealed pronounced substrate inhibition of H3H by hispidin, conserved across both homologues. Direct monitoring of substrate turnover further revealed an unexpected secondary H3H-catalysed conversion of 3-hydroxyhispidin that remained dependent on NADPH and FAD. NMR, isotope labelling and product characterisation support an additional oxidative transformation followed by formation of multiple downstream products, including caffeic acid, thereby reconnecting secondary turnover with an upstream intermediate of the pathway. H3H nevertheless retained a strong kinetic preference for hispidin over 3-hydroxyhispidin. Together, these findings reveal previously unrecognised catalytic complexity within the fungal bioluminescence pathway and provide a biochemical framework for understanding and engineering pathway flux.

biochemistry↗

bioRxiv2026

An Operant-based Touchscreen Morph Discrimination Task Does Not Detect Age-related Mnemonic Similarity Deficits in Rats

The Mnemonic Similarity Task (MST) is highly sensitive to age-related cognitive decline in humans and has been adapted for rodents using 3D objects, where aged animals show deficits in discriminating similar lures. To improve translational alignment with human testing and increase automation, we developed a touchscreen-based rat analog using a morphed Object-Cued Spatial Choice (OCSC) task with 2D image stimuli. Young (4-month) and aged (21-month) male and female Fischer 344 x Brown Norway hybrid rats were trained in Bussey-Saksida touchscreen chambers and tested on discrimination performance using image pairs that varied parametrically in feature overlap. We also assessed perirhinal cortical engagement in a subset of animals using Arc expression as a readout of activity-related principal cell firing following low-and high-overlap task epochs. Across shaping and procedural training, aged rats required more errors to reach criterion on one stimulus set, but both age groups successfully acquired the task. During morph testing, performance declined systematically as stimulus similarity increased, confirming that the task manipulated discrimination difficulty. However, contrary to expectations, young and aged rats performed similarly across overlap conditions, with no significant age-related impairment. In the Arc experiment, discrimination accuracy was again reduced by greater stimulus overlap, but Arc expression in perirhinal cortex did not differ reliably by age or overlap condition, although expression was associated with behavioral accuracy and deep layers showed higher ensemble similarity than superficial layers. These findings indicate that, while the touchscreen morph OCSC task is sensitive to stimulus similarity, it does not detect the robust age-related mnemonic discrimination deficits previously observed with 3D object-based rodent MST paradigms, underscoring the importance of considering ethological relevance when designing translational cognitive assays.

neuroscience↗

bioRxiv2026

In vivo lineage tracing across human tissues using methylation barcodes in the protocadherin gene cluster

Resolving the lineage history of human cells is fundamental to understanding ageing and cancer but remains hampered by a lack of native, high-resolution markers. Here, we identify the protocadherin (PCDH) gene cluster as a naturally occurring, highly diverse methylation barcode. While PCDH methylation creates neuronal diversity in the brain, we show that stochastic methylation patterns in this region are maintained as heritable, evolvable lineage markers across multiple non-neuronal tissues, including blood, kidney, prostate, and bladder. By tracking these barcodes in serial samples over a decade, we reveal clonal dynamics with high fidelity, quantitatively recapitulating genetic clone sizes. Crucially, PCDH barcodes identify "cryptic" clonal expansions invisible to standard driver-mutation sequencing and resolve subclonal architectures via continuous epimutation. This native barcoding system provides a scalable, driver-agnostic framework for reconstructing somatic evolution in humans.

genomics↗

bioRxiv2025

Spatial organization of the tumor-immune microenvironment in ER-positive breast cancer: remodeling during treatment and associations with clinical response

BackgroundThe tumor microenvironment influences treatment response in ER-positive breast cancer, but what distinguishes responders from non-responders and how it changes during treatment is poorly understood. MethodsER-positive breast tumors treated with neoadjuvant chemotherapy with or without bevacizumab were profiled with bulk proteomics pre-(n = 95), on-(n = 84) and post-treatment (n = 100). A subset of tumors was profiled with spatial single-cell proteomics pre-(n = 13) and on-treatment (n = 11). Cell phenotypes, spatial location and activation states were determined, and cellular colocalization assessed with spatial metrics. Bulk and spatial features were evaluated against treatment response defined by residual cancer burden. ResultsTreatment with bevacizumab amplified chemotherapy effects on proteomic signaling. The immune contexture shifted from suppressive to supportive during treatment through decreased macrophage, regulatory and anergic T-cell density and increased colocalization between epithelial cells and CD8+, CD4+ T-cells and dendritic cells. At baseline, responders had high density of effector memory T-cells, while non-responders had more naive T-cells. In addition, responders had increased colocalization of epithelial cells with macrophages, and effector memory T-cells with M1-like macrophages compared to non-responders. ConclusionsSpatially distinct tumor-immune microenvironments influence response to neoadjuvant treatment, offering valuable insights for guiding treatment decisions.

cancer biology↗

bioRxiv2025

Methylation dynamics in the decades preceding acute myeloid leukaemia

DNA methylation is emerging as a highly sensitive and specific marker of cancer initiation and progression. How these cancer-specific methylation changes are established in the decades before cancer, however, remains largely unknown. Here, we use a unique collection of longitudinal blood samples collected annually up to 15 years prior to a diagnosis of acute myeloid leukaemia to sensitively track the dynamics of DNA methylation changes at high temporal resolution. We identify thousands of differentially methylated regions (DMRs) that exhibit altered patterns of methylation up to 10 years before acute myeloid leukaemia (AML) diagnosis. Most of these DMRs are strongly associated with expanding clones carrying somatic driver mutations. We identify a subset of epigenetic driver DMRs characterised by recurrent CpG alterations that are highly shared across pre-AML cases. These are likely to reflect early epigenetic reprogramming associated with AML development. We also reveal large numbers of stochastic passenger CpGs whose differential methylation results from hitch-hiking with clonal expansions driven by somatically acquired genetic events. These passenger CpGs can be exploited for lineage tracing to discover clonal expansions driven by missing driver mutations. Our findings show widespread changes in methylation patterns during the early stages of cancer development which could be utilised for risk prediction and therapeutic intervention.

genomics↗

bioRxiv2024

Clonal dynamics and somatic evolution of haematopoiesis in mouse

Haematopoietic stem cells maintain blood production throughout life. While extensively characterised using the laboratory mouse, little is known about how the population is sustained and evolves with age. We isolated stem cells and progenitors from young and old mice, identifying 221,890 somatic mutations genome-wide in 1845 single cell-derived colonies, and used phylogenetic analysis to infer the ontogeny and population dynamics of the stem cell pool. Mouse stem cells and progenitors accrue [~]45 somatic mutations per year, a rate only about 2-fold greater than human progenitors despite the vastly different organismal sizes and lifespans. Phylogenetic patterns reveal that stem and multipotent progenitor cell pools are both established during embryogenesis, after which they independently self-renew in parallel over life. The stem cell pool grows steadily over the mouse lifespan to approximately 70,000 cells, self-renewing about every six weeks. Aged mice did not display the profound loss of stem cell clonal diversity characteristic of human haematopoietic ageing. However, targeted sequencing revealed small, expanded clones in the context of murine ageing, which were larger and more numerous following haematological perturbations and exhibited a selection landscape similar to humans. Our data illustrate both conserved features of population dynamics of blood and distinct patterns of age-associated somatic evolution in the short-lived mouse.

genomics↗

bioRxiv2024

Evolutionary dynamics in the decades preceding acute myeloid leukaemia

Somatic evolution in ageing tissues underlies many cancers. However, our quantitive understanding of the rules governing this pre-cancerous evolution remains incomplete. Here we exploit a unique collection of serial blood samples collected annually up to 15 years prior to diagnosis of acute myeloid leukaemia (AML) to provide a quantitative description of pre-cancerous evolutionary dynamics. Using deep duplex sequencing and evolutionary theory, we quantify the acquisition ages and fitness effects of the key driver events in AML development. The first driver mutations are typically acquired in the first few decades of life when the blood remains highly polyclonal. These early slow-growing clones subsequently acquire multiple further driver mutations which confer selective advantages up to 100-fold larger than the early drivers. These faster-growing clones harbouring multiple driver mutations can cause complete somatic sweeps of the blood decades before diagnosis, a feature strongly associated with future AML. Once established in the blood, the dynamics of driver mutations are highly predictable. Trajectories are shaped by strong clonal competition between lineages with limited evidence of other extrinsic factors playing a major role. Our data show that the clonal dynamics of blood are consistent with a set of remarkably simple evolutionary rules which strike a balance between chance and determinism.

cancer biology↗

bioRxiv2024

Interpretation of murine models of cardiac disease is enhanced by consideration of divergently expressed human-mouse orthologous genes

Humans and mice share remarkably similar cardiac anatomy and physiology and have many orthologous genes with high sequence similarity. Together with their small size and short lifespan, these factors are major contributors to the popularity of mice as research models. Nonetheless, findings in mice often fail to translate into humans. We propose that this may be due in part to differences in gene expression. Advances in molecular genomics have enabled profiling of gene expression at the level of individual cells through single-cell RNA-sequencing. Large repositories of human and murine data across many organs and tissues, including the heart, are now available. However, there is currently a lack of comparative research which directly quantifies similarities and differences in expression of orthologous genes between human and mouse. This study is the first, to our knowledge, to directly compare celltype-specific expression conservation and divergence between orthologous genes in human and mouse heart. Cardiac data from 7 human and mouse scRNA-seq publications was retrieved, with mouse data converted to equivalent human gene orthologues. The datasets were integrated and subjected to comparative transcriptomic analysis in R using Seurat. Classical celltype markers did not perform equally across species. We have identified species-conserved celltype marker genes, providing a useful resource to identify cardiac cell populations in both species. Further, we have identified and ranked divergence between species for each cardiac celltype, highlighting genes which vary considerably in expression between human and mouse heart. Many of these have been genetically modified to create mouse models or encode proteins targeted by pharmaceutical drugs. Researchers should carefully consider these highly divergent genes when planning, or interpreting data from, mouse models of human biology.

genomics↗

bioRxiv2023

Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging

Multiplex tissue imaging are a collection of increasingly popular single-cell spatial proteomics and transcriptomics assays for characterizing biological tissues both compositionally and spatially. However, several technical issues limit the utility of multiplex tissue imaging, including the limited number of molecules (proteins and RNAs) that can be assayed, tissue loss, and protein probe failure. In this work, we demonstrate how machine learning methods can address these limitations by imputing protein abundance at the single-cell level using multiplex tissue imaging datasets from a breast cancer cohort. We first compared machine learning methods strengths and weaknesses for imputing single-cell protein abundance. Machine learning methods used in this work include regularized linear regression, gradient-boosted regression trees, and deep learning autoencoders. We also incorporated cellular spatial information to improve imputation performance. Using machine learning, single-cell protein expression can be imputed with mean absolute error ranging between 0.05-0.3 on a [0,1] scale. Finally, we used imputed data to predict whether single cells were more likely to come from pre-treatment or post-treatment biopsies. Our results demonstrate (1) the feasibility of imputing single-cell abundance levels for many proteins using machine learning; (2) how including cellular spatial information can substantially enhance imputation results; and (3) the use of single-cell protein abundance levels in a use case to demonstrate biological relevance.

cancer biology↗

bioRxiv2023

Biochemical and functional characterization of the p.A165T missense variant of mitochondrial amidoxime-reducing component 1 in HepG2 cells

Recent genome-wide association studies have identified a missense variant p.A165T in mitochondrial amidoxime-reducing component 1 (mARC1) that is strongly associated with protection from all-cause cirrhosis and improved prognosis in nonalcoholic steatohepatitis (NASH). The precise mechanism of this protective effect is unknown. Substitution of alanine 165 with threonine is predicted to affect mARC1 protein stability and to have deleterious effects on its function. To investigate the mechanism, we have generated a knock-in mutant mARC1 A165T in human hepatoma HepG2 cells, enabling characterization of protein subcellular distribution, stability, and biochemical functions of the mARC1 mutant protein expressed from its endogenous locus. Compared to wild-type (WT) mARC1, we found that the A165T mutant exhibits significant mislocalization outside of its traditional location anchored in the mitochondrial outer membrane and reduces protein stability, resulting in lower basal levels. We evaluated the involvement of the ubiquitin proteasome system in mARC1 A165T degradation and observed increased ubiquitination and faster degradation of the A165T variant. In addition, we have shown that HepG2 cells carrying the MTARC1 p.A165T variant exhibit lower N-reductive activity on exogenously-added amidoxime substrates in vitro. The data from these biochemical and functional assays suggest a mechanism by which the MTARC1 p.A165T variant abrogates enzyme function which may contribute to its protective effect in liver disease.

cell biology↗

bioRxiv2023

Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers

CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To improve understanding of how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets suggests a diverse set of tumor adaptations to CDK4/6i therapy. Malignant cells may adapt to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression during therapy. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to better understand HR+ breast cancer tumor therapeutic adaptations to CDK4/6i therapy.

cancer biology↗

bioRxiv2022

IGHV allele similarity clustering improves genotype inference from adaptive immune receptor repertoire sequencing data

In adaptive immune receptor repertoire analysis, determining the germline variable (V) allele associated with each T- and B-cell receptor sequence is a crucial step. This process is highly impacted by allele annotations. Aligning sequences, assigning them to specific germline alleles, and inferring individual genotypes are challenging when the repertoire is highly mutated, or sequence reads do not cover the whole V region. Here, we propose an alternative naming scheme for the V alleles as well as a novel method to infer individual genotypes. We demonstrate the strength of the two by comparing their outcomes to other genotype inference methods and validated the genotype approach with independent genomic long read data. The naming scheme is compatible with current annotation tools and pipelines. Analysis results can be converted from the proposed naming scheme to the nomenclature determined by the International Union of Immunological Societies (IUIS). Both the naming scheme and the genotype procedure are implemented in a freely available R package (PIgLET). To allow researchers to explore further the approach on real data and to adapt it for their future uses, we also created an interactive website (https://yaarilab.github.io/IGHV_reference_book).

immunology↗

bioRxiv2022

A Web-based Software Resource for Interactive Analysis of Multiplex Tissue Imaging Datasets

Highly multiplexed tissue imaging (MTI) are powerful spatial proteomics technologies that enable in situ single-cell characterization of tissues. However, analysis and visualization of MTI datasets remains challenging, and we developed the Galaxy-ME software hub to address this challenge. Galaxy-ME is a web-based, interactive software hub that enables end-to-end analysis and visualization of MTI datasets and is accessible to everyone. To demonstrate its utility, Galaxy-ME was used to analyze datasets obtained from multiple MTI assays in both normal and cancerous tissues. Galaxy-ME is a publicly available web resource.

bioinformatics↗

bioRxiv2022

Mutation rates and fitness consequences of mosaic chromosomal alterations in blood

Mosaic chromosomal alterations (mCAs) are commonly detected in many cancers and have been found to arise decades before diagnosis. A quantitative understanding of the rate at which these events occur and their functional consequences could improve cancer risk prediction and yet they remain poorly characterised. Here we use clone size estimates of mCAs from the blood of 500,000 participants in the UK Biobank to estimate the mutation rates and fitness consequences of acquired gain, loss and copy-neutral loss of heterozygosity (CN-LOH) events at the chromosomal arm level. Most mCAs have moderate to high fitness effects, but occur at a low rate, being over 10-fold less common than equivalently fit SNVs. While the majority of mCAs increase in prevalence with age in a way that is consistent with a constant growth rate, we find specific examples of mCAs whose behaviour deviates from this suggesting fitness effects for these mCAs may depend on inherited variants or be influenced by extrinsic factors. We find an association between mCA fitness effect and future blood cancer risk, highlighting the important role mCAs may play in risk stratification.

genomics↗

bioRxiv2022

Unilateral Perforant Path Transection Does Not Alter Lateral Entorhinal Cortical or Hippocampal CA3 Arc Expression

It is well established that degradation of perforant path fibers is associated with age-related cognitive dysfunction and CA3 hyperactivity. Whether this fiber loss triggers a cascade of other functional changes within the hippocampus circuit has not been causatively established, however. Thus, the current study evaluated the effect of perforant path fiber loss on neuronal activity in CA3 and layer II of the lateral entorhinal cortex (LEC) in relation to mnemonic similarity task performance. Expression of the immediate early gene Arc was quantified in rats that received a unilateral right hemisphere transection of the perforant path or sham surgery that cut the cortex but left the fibers intact. Behavior-related expression of Arc mRNA was measured to test the hypothesis that fiber loss leads to elevated activation of CA3 and LEC neurons, as previously observed in aged rats that were impaired on the mnemonic similarity task. Transection of perforant path fibers, which has previously been shown to lead to a decline in mnemonic similarity task performance, did not alter Arc expression. Arc expression in CA3, however, was correlated with task performance on the more difficult discrimination trials across both surgical groups. These observations further support a link between CA3 activity and mnemonic similarity task performance but suggest the reduced input from the entorhinal cortex to the hippocampus, as observed in old age, does not causatively elevate CA3 activity.

neuroscience↗

bioRxiv2022

Multiplexed microfluidic chip for cell co-culture

Paracrine signaling is challenging to study in vitro, as conventional culture tools dilute soluble factors and offer little to no spatiotemporal control over signaling. Microfluidic chips offer potential to address both of these issues. However, few solutions offer both control over onset and duration of cell-cell communication, and high throughput. We have developed a microfluidic chip designed to culture cells in adjacent chambers, separated by valves to selectively allow or prevent exchange of paracrine signals. The chip features 16 fluidic inputs and 128 individuallyaddressable chambers arranged in 32 sets of 4 chambers. Media can be continuously perfused or delivered by diffusion, which we model under different culture conditions to ensure normal cell viability. Immunocytochemistry assays can be performed in the chip, which we modeled and fine-tuned to reduce total assay time to 1h. Finally, we validate the use of the chip for co-culture studies by showing that HEK293Ta cells respond to signals secreted by RAW 264.7 immune cells in adjacent chambers, only when the valve between the chambers is opened.

bioengineering↗

bioRxiv2022

ImmunoTyper-SR: A Novel Computational Approach for Genotyping Immunoglobulin Heavy Chain Variable Genes using Short Read Data

Human immunoglobulin heavy chain (IGH) locus on chromosome 14 includes more than 40 functional copies of the variable gene (IGHV), which, together with the joining genes (IGHJ), diversity genes (IGHD), constant genes (IGHC) and immunoglobulin light chains, code for antibodies that identify and neutralize pathogenic invaders as a part of the adaptive immune system. Because of its highly repetitive sequence composition, the IGH locus has been particularly difficult to assemble or genotype through the use of standard short read sequencing technologies. Here we introduce ImmunoTyper-SR, an algorithmic method for genotype and CNV analysis of the germline IGHV genes using Illumina whole genome sequencing (WGS) data. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGHV alleles from a given database, with constraints on the number and distribution of reads across each called allele. We have validated ImmunoTyper-SR on 12 individuals with Illumina WGS data from the 1000 Genomes Project, whose IGHV allele composition have been studied extensively through the use of long read and targeted sequencing platforms, as well as nine individuals from the NIAID COVID Consortium who have been subjected to WGS twice. We have then applied ImmunoTyper-SR on 585 samples from the NIAID COVID Consortium to investigate associations between distinct IGHV alleles and anti-type I IFN autoantibodies which have been linked to COVID-19 severity.

bioinformatics↗

bioRxiv2021

Uncovering Xenobiotics in the Dark Metabolome using Ion Mobility Spectrometry, Mass Defect Analysis and Machine Learning

The identification of xenobiotics in nontargeted metabolomic analyses is a vital step in understanding human exposure. Xenobiotic metabolism, excretion, and co-existence with other endogenous molecules however greatly complicate nontargeted studies. While mass spectrometry (MS)-based platforms are commonly used in metabolomic measurements, deconvoluting endogenous metabolites and xenobiotics is often challenged by the lack of xenobiotic parent and metabolite standards as well as the numerous isomers possible for each small molecule m/z feature. Here, we evaluate the use of ion mobility spectrometry coupled with MS (IMS-MS) and mass defect filtering in a xenobiotic structural annotation workflow to reduce large metabolomic feature lists and uncover potential xenobiotic classes and species detected in the metabolomic studies. To evaluate the workflow, xenobiotics having known high toxicities including per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) were examined. Initially, to address the lack of available IMS collision cross section (CCS) values for per- and polyfluoroalkyl substances (PFAS), 88 PFAS standards were evaluated with IMS-MS to both develop a targeted PFAS CCS library and for use in machine learning predictions. The CCS values for biomolecules and xenobiotics were then plotted versus m/z, clearly distinguishing the biomolecules and halogenated xenobiotics. The xenobiotic structural annotation workflow was then used to annotate potential PFAS features in NIST human serum. The workflow reduced the 2,423 detected LC-IMS-MS features to 80 possible PFAS with 17 confidently identified through targeted analyses and 48 additional features correlating with possible CompTox entries.

biochemistry↗