Biology subjects

Riglar, D. T.

Publications and source records attributed to Riglar, D. T..

8 recordsLinked to original sources

bioRxiv2026

A whole organism screening platform identifies gut microbiome microproteins that modulate host metabolism

Advances in metagenomic sequencing over the past two decades have identified vast numbers of previously uncharacterised small open reading frames that may encode microproteins (<50aa). Although computational tools have accelerated gene sequence prediction from metagenomic data, the function of most annotated proteins remains unknown and untested, especially in the context of host-microbiome interactions. Here, we present a scalable phenotypic screening pipeline to identify gut microbiome-derived proteins that modulate host function. Using the nematode worm Caenorhabditis elegans as a whole animal model that is amenable to systematic screening approaches, our pipeline integrates high-throughput cloning, expression and delivery to worms via feeding, followed by behavioural phenomics screening. We apply this approach to a pilot library of 126 uncharacterised microproteins (< 50 aa) from healthy human gut metagenomes, identifying a set of high-interest targets with potential activity and ultimately validating a microprotein that modulates host fatty acid metabolism when expressed. With protein-based therapies increasingly recognised as a promising alternative to traditional small molecules, this work highlights the potential of a target-agnostic approach for the systematic screening and discovery of novel bioactive proteins.

microbiology↗

bioRxiv2025

Cleared tissue dual-view oblique plane microscopy

We present a dual-view oblique plane microscope (dOPM) for imaging thick optically cleared tissue samples using a silicone immersion primary objective. The custom-designed remote refocusing relay utilizes stock optics to achieve remote refocusing in refractive index-matched samples. The spatial resolution of the system was characterized using a series of fluorescent bead phantoms with refractive indices ranging from 1.4-1.5, with the point spread function full width at half maximum measuring [~]0.5 {micro}m laterally and [~]1 {micro}m axially for a refractive index-matched bead sample, with minimal degradation over a >250 {micro}m axial range. We characterize how the remote refocusing performance at sample refractive indices up to n = 1.5 can be partially compensated for using adjustment of the correction collar on the primary objective. We apply the system to imaging a range of biological samples with varied refractive indices. Combined with tiled acquisition, image stitching and multi-view image fusion, the microscope enables multicolour imaging of mm-wide and [~]250 {micro}m thick optically cleared mouse ovarian cancer and colon tissue samples with subcellular resolution. We also image a whole Drosophila melanogaster fruit fly brain. The system offers a platform for fast and high-resolution, multicolour volumetric imaging across spatial scales, integrated on a commercially available microscope frame.

biophysics↗

bioRxiv2024

Imaging of live bacterial whole-cell biosensors illuminates spatial sialic acid availability within the inflamed mammalian gut

Host mucin-derived sialic acids are key drivers of microbial colonisation, growth and pathogenicity within the mammalian gut. However, their study is hindered by complex spatiotemporal dynamics: Many gut metabolites, including sialic acids, are rapidly consumed, transformed or absorbed by the microbiota or host, meaning that conventional measurements of faeces or bulk digesta often fail to capture their true local availability. In contrast, engineered bacterial-whole cell biosensors provide an in situ read-out of metabolite exposure at the point and time of use, before these molecules are depleted. Here, we demonstrate increases in the bioavailability of sialic acid in the inflamed mouse gut using an engineered Escherichia coli biosensor that reports on sialic acid exposure via NanR-regulated transcriptional circuit. The biosensor robustly colonises the mouse gut and remains functional for at least six weeks. Through organ-scale imaging at single bacterial resolution we observe strong correlations between disease status and biosensor response in two inflammation models. Profiling along the length of the gut uncovers regional variations between the maximal sialic acid sensing and the peak inflammatory response within host tissues in a murine colitis model. Simultaneous tracking of host and microbial markers of inflammation informs the therapeutic response to sialidase inhibition, which accelerates disease recovery. Together, these data illuminate the complex spatial dynamics involved in shared host-microbiome metabolism and demonstrate the broader power of using engineered bacterial biosensors to monitor in situ bioavailability of rapidly turned-over metabolites within the gut.

synthetic biology↗

bioRxiv2023

A discovery platform to identify inducible synthetic circuitry from varied microbial sources

Gut microbes encode a variety of systems for molecular sensing and controlling conditional gene expression within the mammalian gut. Synthetic biology approaches such as whole-cell biosensing and sense-and-respond therapeutics aim to tap into this vast sensing repertoire to drive clinical and pre-clinical applications. An ongoing constraint is the limited number of well-characterized inducible circuit components to specifically sense in vivo conditions of interest, such as disease. Here, we extend the flexibility and power of a biosensor screening platform using bacterial memory circuits encoded in a gut commensal E. coli. We construct libraries driven by potential sensory components derived from a combination of E. coli promoters or bacterial two-component systems (TCSs) sourced from diverse gut bacteria. Each is tagged with unique DNA barcodes using a pooled construction method. Using our pipeline, we evaluate sensor activity and performance heterogeneity across in vitro and in vivo conditions including using a mouse inflammation model. We demonstrate the methods ability to identify biosensors of interest, including the identification of unannotated TCSs. Following the optimisation of library construction, analysis, and delivery to account for the challenges of working with engineered bacteria within a conventional mammalian gut microbiome, we identify and validate several further biosensors of interest responding to the murine gut environment, and specifically during inflammatory conditions. This approach can be applied to transcriptionally activated sensing elements of any type and will allow for rapid development of new biosensors that can advance synthetic biology approaches for complex environments.

synthetic biology↗

bioRxiv2023

On-grid purification of electron microscopy samples via a 3D-printed flow-cell

While recent advances in cryo-EM, coupled with single particle analysis, have the potential to allow structure determination in a near-native state from vanishingly few individual particles, this vision has yet to be realised in practise. Requirements for particle numbers that currently far exceed the theoretical lower limits, challenges with the practicalities of achieving high concentrations for difficult-to-produce samples, and inadequate sample-dependent imaging conditions, all result in significant bottlenecks preventing routine structure determination using cryo-EM. Therefore, considerable efforts are being made to circumvent these bottlenecks by developing affinity purification of samples on-grid; at once obviating the need to produce large amounts of protein, as well as more directly controlling the variable, and sample-dependent, process of grid preparation. In this proof-of-concept study, we demonstrate a further practical step towards this paradigm, developing a 3D-printable flow-cell device to allow on-grid affinity purification from raw inputs such as whole cell lysates, using graphene oxide-based affinity grids. Our flow-cell device can be interfaced directly with routinely-used laboratory equipment such as liquid chromatographs, or peristaltic pumps, fitted with standard chromatographic (1/16") connectors, and can be used to allow binding of samples to affinity grids in a controlled environment prior to the extensive washing required to remove impurities. Furthermore, by designing a device which can be 3D printed and coupled to routinely used laboratory equipment, we hope to increase the accessibility of the techniques presented herein to researchers working towards single-particle macromolecular structures.

biophysics↗

bioRxiv2019

Synthetic gene circuits enable systems-level biosensor discovery at the host-microbe interface

The composition and function of the gut microbiota are strongly associated with human health, and dysbiosis is linked to an array of diseases, ranging from obesity and diabetes to infection and inflammation. Engineering synthetic circuits into gut bacteria to sense, record and respond to in vivo signals is a promising new approach for the diagnosis, treatment and prevention of disease. Here, we repurpose a synthetic bacterial memory circuit to rapidly screen for and discover new in vivo-responsive biosensors in commensal gut Escherichia coli. We develop a pipeline for rapid systems-level library construction and screening, using next-generation sequencing and computational analysis, which demonstrates remarkably robust identification of responsive biosensors from pooled libraries. By testing both genome-wide and curated libraries of potential biosensor triggers--each consisting of a promoter and ribosome binding site (RBS)--and using RBS variation to augment the range of trigger sensitivity, we identify and validate triggers that selectively activate our synthetic memory circuit during transit through the gut. We further identify biosensors with increased response in the inflamed gut through comparative screening of our libraries in healthy mice and those with intestinal inflammation. Our results demonstrate the power of systems-level screening for the identification of novel biosensors in the gut and provide a platform for disease-specific screening using synthetic circuits, capable of contributing to both the understanding and clinical management of intestinal illness. IMPORTANCEThe gut is a largely obscure and inaccessible environment. The use of live, engineered probiotics to detect and respond to disease signals in vivo represents a new frontier in the management of gut diseases. Engineered probiotics have also shown promise as a novel mechanism for drug delivery. However, the design and construction of effective strains that respond to the in vivo environment is hindered by our limited understanding of bacterial behavior in the gut. Our work expands the pool of potential biosensors for the healthy and diseased gut, providing insight into host-microbe interactions and enabling future development of increasingly complex synthetic circuits. This method also provides a framework for rapid prototyping of engineered systems and for application across bacterial strains and disease models.

synthetic biology↗

bioRxiv2018

Variability of bacterial behavior in the mammalian gut captured using a growth-linked single-cell synthetic gene oscillator

The dynamics of the bacterial population that comprises the gut microbiota plays key roles in overall mammalian health. However, a detailed understanding of bacterial growth within the gut is limited by the inherent complexity and inaccessibility of the gut environment. Here, we deploy an improved synthetic genetic oscillator to investigate dynamics of bacterial colonization and growth in the mammalian gut under both healthy and disease conditions. The synthetic oscillator, when introduced into both Escherichia coli and Salmonella Typhimurium maintains regular oscillations with a constant period in generations across growth conditions. We determine the phase of oscillation from individual bacteria using image analysis of resultant colonies and thereby infer the number of cell divisions elapsed. In doing so, we demonstrate robust functionality and controllability of the oscillator circuits activity during bacterial growth in vitro, in a simulated murine gut microfluidic environment, and in vivo within the mouse gut. We determine different dynamics of bacterial colonization and growth in the gut under normal and inflammatory conditions. Our results show that a precise genetic oscillator can function in a complex environment and reveal single cell behavior under diverse conditions where disease may create otherwise impossible-to-quantify variability in growth across the population.

synthetic biology↗

bioRxiv2018

Inducible Cooperation in a Synthetic Gut Bacterial Consortium Introduces Population Balance and Stability

In nature, microbes interact antagonistically, neutrally or beneficially. To shed light on the effects of positive interactions in microbial consortia we introduced metabolic dependencies and metabolite overproduction into four bacterial species. While antagonistic interactions govern the wildtype consortium behavior, the genetic modifications alleviated antagonistic interactions and resulted in beneficial interactions. Engineered cross-feeding increased population evenness, a component of ecological diversity, in different environments including in a more complex gnotobiotic mouse gut environment. Our findings suggest that metabolite cross-feeding could be used as a tool for intentionally shaping microbial consortia in complex environments.\n\nImportanceMicrobial communities are ubiquitous in nature. Bacterial consortia live in and on our body and in our environment and more recently, biotechnology is applying microbial consortia for bioproduction. As part of our body, bacterial consortia influence us in health and disease. Microbial consortia function is determined by its composition, which in turn is driven by the interactions between species. Further understanding of microbial interactions will help us deciphering how consortia function in complex environments and may enable us to modify microbial consortia for health and environmental benefits.

synthetic biology↗