Biology subjects

Wright, J. A.

Publications and source records attributed to Wright, J. A..

6 recordsLinked to original sources

bioRxiv2025

DeepTRACE: Flexible Machine Learning for Analysis and Discovery in Single Molecule Tracks

DeepTRACE is a machine learning tool for analysing long, complex single-molecule tracks in living cells; learning from sequences of molecular events using spatial, temporal, and photometric context. It traces how molecular processes unfold over time and space, incorporating past interactions, subcellular location, and photometric properties. DeepTRACE requires only a few hundred annotated tracks and minutes of CPU training, yet outperforms traditional methods and supports extensive downstream analysis, including the discovery of relationships absent from the training data.

biophysics↗

bioRxiv2024

Discovery of lydiamycin A biosynthetic gene cluster in the plant pathogen Rhodococcus fascians guides structural revision and identification of molecular target

The natural products actinonin and matlystatin feature an N-hydroxy-2-pentyl-succinamyl (HPS) chemophore that facilitates metal chelation and confers their metalloproteinase inhibitory activity. Actinonin is the most potent natural inhibitor of peptide deformylase (PDF) and exerts antimicrobial and herbicidal bioactivity by disrupting protein synthesis. Here, we used a genomics-led approach to identify candidate biosynthetic gene clusters (BGCs) hypothesised to produce novel HPS-containing natural products. We show that one of these BGCs is on the pathogenicity megaplasmid of the plant pathogen Rhodococcus fascians and produces lydiamycin A, a macrocyclic pentapeptide. The presence of genes predicted to make a HPS-like chemophore informed the structural recharacterisation of lydiamycin via NMR and crystallography to show it features a rare 2-pentyl-succinyl chemophore. We demonstrate that lydiamycin A inhibits bacterial PDF in vitro and show that a cluster-situated PDF gene confers resistance to lydiamycin A, representing a novel self-immunity mechanism associated with the production of a PDF inhibitor. In planta competition assays showed that lydiamycin enhances the fitness of R. fascians during plant colonisation. This study highlights how a BGC can inform the structure, biochemical target and ecological function of a natural product.

microbiology↗

bioRxiv2023

Colorectal cancer detection and treatment with engineered probiotics

Bioengineered probiotics enable new opportunities to improve colorectal cancer (CRC) screening, prevention and treatment strategies. Here, we demonstrate the phenomenon of selective, long-term colonization of colorectal adenomas after oral delivery of probiotic E. coli Nissle 1917 (EcN) to a genetically-engineered murine model of CRC predisposition. We show that, after oral administration, adenomas can be monitored over time by recovering EcN from stool. We also demonstrate specific colonization of EcN to solitary neoplastic lesions in an orthotopic murine model of CRC. We then exploit this neoplasia-homing property of EcN to develop early CRC intervention strategies. To detect lesions, we engineer EcN to produce a small molecule, salicylate, and demonstrate that oral delivery of this strain results in significantly increased levels of salicylate in the urine of adenoma-bearing mice, in comparison to healthy controls. We also assess EcN engineered to locally release immunotherapeutics at the neoplastic site. Oral delivery to mice bearing adenomas, reduced adenoma burden by [~]50%, with notable differences in the spatial distribution of T cell populations within diseased and healthy intestinal tissue, suggesting local induction of robust anti-tumor immunity. Together, these results support the use of EcN as an orally-delivered platform to detect disease and treat CRC through its production of screening and therapeutic molecules.

bioengineering↗

bioRxiv2021

Engineered bacteria detect tumor DNA in vivo

Advances in bacterial engineering have catalysed the development of living cell diagnostics and therapeutics1-3, including microbes that respond to gut inflammation4, intestinal bleeding5, pathogens6 and hypoxic tumors7. Bacteria can access the entire gastrointestinal tract8 to produce outputs measured in stool4 or urine7. Cellular memory, such as bistable switches4,9,10 or genomic rearrangements11, allows bacteria to store information over time. However, living biosensors have not yet been engineered to detect specific DNA sequences or mutations from outside the cell. Here, we engineer naturally competent Acinetobacter baylyi to detect donor DNA from the genomes of colorectal cancer (CRC) cells, organoids and tumors. We characterize the functionality of the biosensors in vitro with co-culture assays and then validate in vivo with sensor bacteria delivered to mice harboring colorectal tumors. We observe horizontal gene transfer from the tumor to the sensor bacteria in our mouse model of CRC. The sensor bacteria achieved 100% discrimination between mice with and without CRC. This Cellular Assay of Targeted, CRISPR-discriminated Horizontal gene transfer (CATCH), establishes a framework for biosensing of mutations or organisms within environments that are difficult to sample, among many other potential applications. Furthermore, the platform could be readily expanded to include production and delivery of antibiotic or antineoplastic therapeutic payloads at the detection site.

synthetic biology↗

bioRxiv2020

The BMP antagonist Gremlin1 contributes to the development of cortical excitatory neurons, motor balance and fear responses

Bone morphogenetic protein (BMP) signaling is required for early forebrain development and cortical formation. How the endogenous modulators of BMP signaling regulate the structural and functional maturation of the developing brain remains unclear. Here we show that expression of the BMP antagonist, Grem1, marks a neuroprogenitor that gives rise to layer V and VI glutamatergic neurons in the embryonic mouse brain. Lineage tracing of Grem1-expressing cells in the embryonic brain was examined by administration of tamoxifen to pregnant Grem1creERT Rosa26LSLTdtomato mice at 13.5 days post coitum (dpc), followed by collection of embryos later in gestation. In addition, at 14.5 dpc, bulk mRNA seq analysis of differentially expressed transcripts between FACS sorted Grem1 positive and negative cells was performed. We also generated Emx1-cre mediated Grem1 conditional knockout mice (Emx1-Cre;Grem1flox/flox) in which the Grem1 gene was deleted specifically in the dorsal telencephalon. Grem1Emx1cKO animals had reduced cortical thickness, especially layers V and VI and impaired motor balance and fear sensitivity compared to littermate controls. This study has revealed new roles for Grem1 in the structural and functional maturation of the developing cortex. Summary statementThe BMP antagonist, Grem1, marks neuroprogenitors that give rise to deep layer glutamatergic neurons in the embryonic mouse brain. Grem1 conditional knockout mice display cortical and behavioural abnormalities.

developmental biology↗

bioRxiv2019

Analysis of task-based functional MRI data preprocessed with fMRIPrep

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time-consuming, error-prone, and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure (BIDS) to standardize both the input datasets --MRI data as stored by the scanner-- and the outputs --data ready for modeling and analysis--, fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

bioinformatics↗