Biology subjects

Rudge, T.

Publications and source records attributed to Rudge, T..

4 recordsLinked to original sources

bioRxiv2026

FluOpti: an open-source system for programmable whole-plate optogenetics and multi-fluorescence imaging

Bacteria are able to self-organize into complex spatial communities, such as colonies, biofilms and swarms. Probing cells and gene networks with dynamic stimuli while preserving their spatial organization is therefore essential for understanding how bacterial communities organize across spatial and temporal scales. Optogenetics offers a powerful approach for such a task given the precise control of stimulus delivery without the perturbations normally associated with the addition of liquid inducers. However, most optogenetics devices have been developed to work with liquid cell cultures or to deliver a spatial pattern without the concurrent recording of gene responses and colony growth. Here, we describe FluOpti, an open source, low-cost device for controlling gene expression, through programmable light inputs, and recording multi-fluorescence responses and colony growth across whole petri dishes. White light LEDs are used for brightfield imaging while green and red LEDs are used as optogenetic inputs to activate and inactivate target genes via the CcaS/R two component system in E. coli. Low cost blue and orange acrylic are used as excitation and emission filters for fluorescence imaging, respectively. We developed custom software to analyze colony growth and optogenetic responses from 72-hour time-lapse experiments. A mathematical model was developed to predict gene expression levels in response to green-to-red light ratio stimuli. We use FluOpti to reveal a spatially structured response to optogenetic stimuli, with gene activation rates differing in cells located at the center and edge of colonies. to validate its use at a whole petri dish scale, FluOpti was used to depict how Voronoi territories can act as predictors of colony size, in congruence with previous studies. Together, these results demonstrate the utility of the device for studying gene networks at multiple spatio-temporal scales, from individual colonies to the whole petri dish. Performing optogenetics studies in whole petri dishes while preserving spatial arrangements could offer valuable insights into the spatial biology of gene networks in microbial populations.

bioengineering↗

bioRxiv2026

Self-generated environmental feedback drives traveling waves of gene expression in bacterial colonies

Bacterial colonies grow within microenvironments that they continuously reshape through nutrient uptake, metabolism and mechanical interaction. However, in colonies carrying engineered gene circuits, how these self-generated environmental changes feed back on gene expression to produce spatiotemporal organization remains poorly understood. Here we show that growth and gene expression are dynamically coupled during the maturation of founding colonies, with growth-driven environmental changes organizing gene expression into traveling waves. By combining quantitative time-lapse microscopy, mathematical modeling and image-based parameter inference, we demonstrate that edge-dominated colony expansion consistent with mechanical constraints on growth is followed by density-dependent growth arrest in which the total area occupied by colonies does not converge to a fixed carrying capacity of the shared growth environment. We then find that colonies form two distinct traveling waves of gene expression. An intra-colony wave emerges only after growth arrest and is observed in both constitutive genes and distinct regulated circuit architectures, indicating that it is not a result of circuit topology. Our observations are consistent with nutrient depletion during growth followed by subsequent recovery after growth arrest. At later times, an inter-colony wave emerges that is consistent with a colony-produced diffusible factor spreading through the shared medium. Together, these findings reveal that the colony environment is not a passive background but an active and intrinsic component of spatiotemporal gene regulatory dynamics, in which self-generated environmental feedback couples mechanical constraints, nutrient dynamics and gene expression across spatial scales.

Synthetic Biology↗

bioRxiv2022

Experimental Data Connector (XDC): Integrating the Capture of Experimental Data and Metadata Using Standard Formats and Digital Repositories

Accelerating the development of synthetic biology applications requires reproducible experimental findings. Different standards and repositories exist to exchange experimental data and metadata. However, the associated software tools often do not support a uniform data capture, encoding, and exchange of information. A connection between digital repositories is required to prevent siloing and loss of information. To this end, we developed the Experimental Data Connector (XDC). It captures experimental data and related metadata by encoding it in standard formats and storing the converted data in digital repositories. Experimental data is then uploaded to Flapjack and the metadata to SynBioHub in a consistent manner linking these repositories. This produces complete connected experimental datasets that are exchangeable. The information is captured using a single template Excel Workbook, which can be integrated into existing experimental workflow automation processes. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/520467v1_ufig3.gif" ALT="Figure 3"> View larger version (50K): org.highwire.dtl.DTLVardef@1c5f886org.highwire.dtl.DTLVardef@3f2a6dorg.highwire.dtl.DTLVardef@fa6cb2org.highwire.dtl.DTLVardef@f63236_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2017

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential for STEM teaching in a high school environment, using it to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for STEM education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

synthetic biology↗