Biology subjects

Evans, S.

Publications and source records attributed to Evans, S..

7 recordsLinked to original sources

bioRxiv2026

Evolutionary stabilisation of stressful metabolism via integrated biocomputing and essential-gene metabolic locking circuits

Synthetic genetic circuits enable microbial differentiation from growth to production, yet metabolic burden, imbalance and toxicity frequently drive strain degeneration. Yeast strains engineered to produce different terpene products exhibited divergent genetic responses to metabolic stresses, but commonly underwent progressive loss of induction of synthetic GAL regulatory circuits, either across the entire population or within subpopulations. Using di- and tri-input biocomputing circuits, the essential glutamine synthetase gene GLN1 was coupled to GAL induction, thereby enabling stabilisation and evolutionary adaptation of the synthetic genetic circuits and stressful heterologous terpene synthetic pathways. The integrated biocomputing and metabolic coupling circuit systems not only prevent strain degeneration but also enable interrogation of non-degenerative evolutionary shifts, providing a platform for metabolic engineering optimisation.

synthetic biology↗

bioRxiv2018

Fast two-photon volumetric imaging of an improved voltage indicator reveals electrical activity in deeply located neurons in the awake brain

Imaging of transmembrane voltage deep in brain tissue with cellular resolution has the potential to reveal information processing by neuronal circuits in living animals with minimal perturbation. Multi-photon voltage imaging in vivo, however, is currently limited by speed and sensitivity of both indicators and imaging methods. Here, we report the engineering of an improved genetically encoded voltage indicator, ASAP3, which exhibits up to 51% fluorescence responses in the physiological voltage range, sub-millisecond activation kinetics, and full responsivity under two-photon illumination. We also introduce an ultrafast local volume excitation (ULOVE) two-photon scanning method to sample ASAP3 signals in awake mice at kilohertz rates with increased stability and sensitivity. ASAP3 and ULOVE allowed continuous single-trial tracking of spikes and subthreshold events for minutes in deep locations, with subcellular resolution, and with repeated sampling over multiple days. By imaging voltage in visual cortex neurons, we found evidence for cell type-dependent subthreshold modulation by locomotion. Thus, ASAP3 and ULOVE enable continuous high-speed high-resolution imaging of electrical activity in deeply located genetically defined neurons during awake behavior.

neuroscience↗

bioRxiv2018

Integrating Vectors for Genetic Studies in the Rare Actinomycete Amycolatopsis marina

Few natural product pathways from rare Actinomycetes have been studied due to the difficulty in applying molecular approaches in these genetically intractable organisms. In this study, we sought to identify integrating vectors, derived using phage int/attP loci, that would efficiently integrate site-specifically in the rare Actinomycete, Amycolatopsis marina DSM45569. Analysis of the genome of A. marina DSM45569 indicated the presence of attB-like sequences for TG1 and R4 integrases. The TG1 and R4 attBs were active in in vitro recombination assays with their cognate purified integrases and attP loci. Integrating vectors containing either the TG1 or R4 int/attP loci yielded exconjugants in conjugation assays from E. coli to A. marina DSM45569. Site-specific recombination of the plasmids into the host TG1 or R4 attB sites was confirmed by sequencing. The presence of homologous TG1 and R4 attB sites in other species of this genus indicates that vectors based on TG1 and R4 integrases could be widely applicable.\n\nImportanceRare Actinomycetes have the same potential of natural product discovery as Streptomyces, but the potential has not been fully explored due to the lack of efficient molecular biology tools. In this study, we identified two serine integrases, TG1 and R4, which could be used in the rare Actinomycetes species, Amycolatopsis marina, as tools for genome integration. The high level of conservation between the attB sites for TG1 and R4 in a number of Amycolatopsis species suggested that plasmids with the integration systems from these phages should be widely useful in this genus.

microbiology↗

bioRxiv2018

A human cell model of cardiac pathophysiological valvulogenesis

Genetically modified mice have advanced our understanding of valve development and related pathologies. Yet, little is known regarding human valvulogenesis in health and diseases. Genuine human in vitro models that reproduce valvular (patho)biology are thus needed. We here developed a human pluripotent stem cell-derived model fit to decode the early steps of human valvulogenesis and to recapitulate valve disease traits in a dish.\n\nUsing cellular based, single cell omics-informed and in vivo-validated approaches, we derived a population of pre-valvular endocardial cells from a pluripotent stem cell source. These human prevalvular cells (HPVCs) expressed gene patterns conforming to the atrio-ventricular canal (AVC) endocardium signature originally established in E9.0 mouse embryos. In fact, HPVC treated with BMP2, cultured onto mouse AVC cushions, or transplanted into the AVC of embryonic mouse hearts, underwent endothelial-to-mesenchymal transition and expressed markers of valve interstitial cells of different valvular layers demonstrating tissue functionality. HPVCs also differentiated into tendinous/chondrogenic cells in line with the valvular repertoire. Extending this valvulogenic model to patient specific iPS cells, we recapitulated features of mitral valve prolapse and uncovered that dysregulation of the SHH pathway is likely to be at the origin of the disease thus providing a putative therapeutic target.\n\nHuman pluripotent stem cells recapitulate early valvulogenesis and provide a powerful model to systematically decipher the origin and lineage contribution of different valvular cell types in humans as well as to study valve diseases in a dish.

developmental biology↗

bioRxiv2018

IL-11 is a therapeutic target in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) remains a progressive disease despite best medical management. We previously identified IL-11 as a critical factor for cardiovascular fibrosis and examine here its role in pulmonary fibrosis. IL-11 is consistently upregulated in IPF genomic datasets, which we confirmed by histology. Pulmonary fibroblasts stimulated with IL-11 transform into invasive myofibroblasts whereas fibroblasts from Il11ra deleted mice did not respond to pro-fibrotic stimuli. In the mouse, injection of recombinant Il-11 or fibroblast-specific expression of Il-11 caused pulmonary fibrosis. We then generated a neutralising IL-11 binding antibody that blocks lung fibroblast activation across species. In a mouse model of IPF, anti-IL-11 therapy attenuated lung fibrosis and specifically blocked Erk activation. These data prioritise IL-11 as an accessible drug target in IPF.\n\nOne Sentence SummaryNon-canonical IL-11 signalling is a central hallmark of idiopathic pulmonary fibrosis and represents a novel target for antibody therapies.

molecular biology↗

bioRxiv2018

Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data

The problem of 3D chromosome structure inference from Hi-C datasets is important and challenging. While bulk Hi-C datasets contain contact information derived from millions of cells, and can capture major structural features shared by the majority of cells in the sample, they do not provide information about local variability between cells. Single cell Hi-C can overcome this problem, but contact matrices are generally very sparse, making structural inference more problematic. We have developed a Bayesian multiscale approach, named SIMBA3D, to infer 3D structures of chromosomes from single cell Hi-C while including the bulk Hi-C data and some regularization terms as a prior. We study the landscape of solutions for each single-cell Hi-C dataset as a function of prior strength and demonstrate clustering of solutions using data from the same cell.

bioinformatics↗

bioRxiv2016

Exonic somatic mutations contribute risk for autism spectrum disorder

Genetic risk factors for autism spectrum disorder (ASD) have yet to be fully elucidated. Somatic mosaic mutations (SMMs) have been implicated in several neurodevelopmental disorders and overgrowth syndromes. Here, we systematically evaluate SMMs by leveraging whole-exome sequencing (WES) data on a large family-based ASD cohort, the Simons Simplex Collection (SSC). We find evidence that ~10% of previously published de novo mutations are potentially SMMs. When using a custom somatic calling pipeline, we recalled all SSC WES data. We validated high and low confidence mutation predictions for a subset of families with single molecule molecular inversion probes. With these validation data, we iteratively developed a high confidence calling approach integrating logistic regression modeling and additional heuristics and applied it to the full cohort. Surprisingly, we found evidence of significant synonymous SMM burden in probands, with mutations more likely to be close to splicing sites. Overall, we observe no strong evidence of missense SMM burden. However, we do observe nominally significant signal for missense SMMs in those families without germline mutations, which strengthens specifically in genes intolerant to mutations. In contrast to missense germline mutations, missense SMMs show potential enrichment for chromatin modifiers. We observe 7-10% of parental mosaics are transmitted germline to a child as occult de novo mutations, which has important implications for recurrence risk for families and potential subclinical ASD features. Finally, we find SMMs in previously implicated high-confidence ASD risk genes, including CHD2, CTNNB1, KMT2C, SYNGAP1, and RELN, further suggesting that this class of mutations contribute to population risk.

genetics↗