Biology subjects

Ingalls, B. P.

Publications and source records attributed to Ingalls, B. P..

7 recordsLinked to original sources

bioRxiv2025

Construction and Functional Characterization of a Heterologous Quorum Sensing Circuit in Clostridium sporogenes

Quorum sensing (QS) is a bacterial communication mechanism that regulates gene expression in a population density-dependent manner. Substantial progress has been made in the engineering of QS systems in Gram-negative bacteria, but development of engineered QS systems in Gram positive bacteria remains limited. In this study, obligate anaerobic Gram-positive bacterium Clostridium sporogenes was engineered with the Staphylococcus aureus agr-QS system to enable density-dependent gene regulation. Using LC-MS/MS, we confirmed production of autoinducing peptides in the engineered C. sporogenes strain. A QS-regulated GFP reporter demonstrated activation of expression in response to both exogenous AIP addition and increasing cell density, confirming functional integration of the agr operon. A media refreshment experiment showed that replacing the culture supernatant delayed QS activation, highlighting the importance of signal accumulation. Moreover, we observed that a non-cognate AIP from another agr specificity group acts as a competitive antagonist, inhibiting gene expression under the QS promoter. To our knowledge, this study presents the first successful engineering of the agr quorum sensing system in an obligate anaerobe, expanding the synthetic biology toolkit and offers new opportunities for bacterial therapies and metabolic engineering.

synthetic biology↗

bioRxiv2025

TrackRefiner: A tool for refinement of bacillus cell tracking data

MotivationSingle-cell resolution time-lapse microscopy of bacterial populations is a powerful tool for assessing cellular behavior and interaction dynamics. Realizing the full potential of this approach requires accurate image analysis: segmentation of individual cell objects, tracking of persistent cells from frame to frame, and connecting of mother cells to daughters when division events occur. In particular, accurate tracking is needed to produce longitudinal datasets for analysis of interactions and features that develop through time. Tracking is challenging when populations are densely packed or when cells undergo significant motion between frames. The leading software packages struggle to provide accurate data in such cases. ResultTo address this problem, we present TrackRefiner, a tool for refinement of bacillus cell tracking data. This package was specifically designed to refine the tracking outputs of CellProfiler, a commonly used image processing tool. TrackRefiner is built with a modular and publicly accessible structure, making it adaptable for integration with other image processing software. To assess the packages performance, we manually determined ground truth tracking results for eight datasets from four research groups, comprising a total of 159,349 object links. This curated dataset, the first of its kind, serves as a valuable benchmark for assessing the performance of bacillus cell tracking algorithms. For timelapses with frequent imaging, TrackRefiner consistently achieved, with one exception, over 98% detection accuracy and corrected 57-100% of tracking errors. Accuracy was reduced for images sampled at lower frequency. Availability and implementationFor easy access, TrackRefiner has been published on PyPI and Anaconda. Source code and user manuals can be accessed via Github and OSF. The manually curated benchmark dataset is also posted at these sites.

microbiology↗

bioRxiv2024

Degradation of PET Plastics by Wastewater Bacteria Engineered via Conjugation

Microplastics are contaminants of global concern that pose risks to ecosystems and human health. Focusing on PET plastics, we present a proof-of-concept for reduction of microplastic pollution: in situ engineering of bacteria in wastewater to degrade PET. Using a broad-host-range conjugative plasmid, we enabled various bacterial species from a municipal wastewater sample to express FAST-PETase, which was released into the extracellular environment. We found that FAST-PETase purified from some isolates could degrade about 40% of a 0.25 mm thick PET film within four days at 50 {degrees}C. We then demonstrate partial degradation of post-consumer PET over 5-7 days by exposure to conditioned media from isolates. These results have broad implications for addressing the global plastic pollution problem by enabling environmental bacteria to degrade PET plastics in situ.

bioengineering↗

bioRxiv2023

A benchmarked comparison of software packagesfor time-lapse image processing of monolayerbacterial population dynamics

Time-lapse microscopy offers a powerful approach for analysing cellular activity. In particular, this technique is valuable for assessing the behaviour of bacterial populations, which can exhibit growth and intercellular interactions in monolayer. Such time-lapse imaging typically generates large quantities of data, limiting the options for manual investigation. Several of image processing software packages have been developed to facilitate analysis. It can thus be a challenge to identify the software package best suited to a particular research goal. Here, we compare four software packages that support analysis of 2D time-lapse images of cellular populations: CellProfiler, SuperSegger-Omnipose, DeLTA, and FAST. We compare their performance against benchmarked results on time-lapse observations of E. coli populations. Performance varies across the packages, with each of the four out-performing the others in at least one aspect of the analysis. Not surprisingly, the packages that have been in development for longer showed the strongest performance. We found that deep-learning based approaches to object segmentation outperformed traditional approaches, but the opposite was true for frame-to-frame object tracking. We offer these comparisons, together with insight on usability, computational efficiency, and feature availability, as a guide to researchers seeking image processing solutions. Significance StatementTime-lapse microscopy provides a detailed window into the world of bacterial behavior. However, the vast amount of data produced by these techniques is difficult to analyze manually. We have analysed four software tools designed to process such data and compared their performance, using populations of commonly studied bacterial species as our test subjects. Our findings offer a roadmap to scientists, helping them choose the right tool for their research. This comparison bridges a gap between microbiology and computational analysis, streamlining research efforts.

microbiology↗

bioRxiv2022

Heterologous Expression of NoxA Confers Aerotolerance in Clostridium sporogenes

Clostridium is a genus of Gram-positive obligate anaerobic bacteria. Some species of Clostridium, including C. sporogenes, may be of use in bacteria-mediated cancer therapy. Spores of Clostridium are inert in healthy normoxic tissue, but germinate when in the hypoxic regions of solid tumors, causing tumor regression. However, such treatments fail to completely eradicate tumors because of higher oxygen levels rise at the tumors outer rim. In this study, we demonstrate that a degree of aerotolerance can be introduced to C. sporogenes by transfer of the noxA gene from C. aminovalericum. NoxA is a water-forming NADH oxidase enzyme. Thus, its activity has no detrimental effect on cell viability. In addition to its potential in cancer treatment, the noxA-expressing strain described here could be used to alleviate challenges related to oxygen sensitivity of C. sporogenes in biomanufacturing.

microbiology↗

bioRxiv2021

Kinetic modelling of β-cell metabolism reveals control points in the insulin-regulating pyruvate cycling pathways

Insulin, a key hormone in the regulation of glucose homeostasis, is secreted by pancreatic {beta}-cells in response to elevated glucose levels. Insulin is released in a biphasic manner in response to glucose metabolism in {beta}-cells. The first phase of insulin secretion is triggered by an increase in the ATP:ADP ratio; the second phase occurs in response to both a rise in ATP:ADP as well as other key metabolic signals, including a rise in the NADPH:NADP+ ratio. Experimental evidence indicates that pyruvate-cycling pathways play an important role in the elevation of the NADPH:NADP+ ratio in response to glucose. In this work we developed a kinetic model for the tricarboxylic acid cycle and pyruvate cycling pathways. We successfully validated our model against recent experimental observations and performed local and global sensitivity analysis to identify key regulatory interactions in the system. The model predicts that the dicarboxylate carrier (DIC) and pyruvate transporter (PYC) are the most important regulators of pyruvate cycling and NADPH production. In contrast, our analysis showed that variation in the pyruvate carboxylase (PC) flux was compensated by a response in the activity of mitochondrial isocitrate dehydrogenase (ICDm) resulting in minimal effect on overall pyruvate cycling flux. The model predictions suggest starting points for further experimental investigation, as well as potential drug targets for treatment of type 2 diabetes.

systems biology↗

bioRxiv2021

NLoed: A Python package for nonlinear optimal experimental design in systems biology

MotivationModelling in systems and synthetic biology relies on accurate parameter estimates and predictions. Accurate model calibration relies, in turn, on data, and on how well-suited the available data is to a particular modelling task. Optimal experimental design (OED) techniques can be used to identify experiments and data collection procedures that will most efficiently contribute to a given modelling objective. However, implementation of OED is limited by currently available software tools that are not well-suited for the diversity of nonlinear models and non-normal data commonly encountered in biological research. Moreover, existing OED tools do not make use of the state-of-the-art numerical tools, resulting in inefficient computation. ResultsHere we present the NLoed software package. NLoed is an open-source Python library providing convenient access to OED methods, with particular emphasis on experimental design for systems biology research. NLoed supports a wide variety of nonlinear, multi-input/output, and dynamic models, and facilitates modelling and design of experiments over a wide variety of data types. To support OED investigations, the NLoed package implements maximum likelihood fitting and diagnostic tools, providing a comprehensive modelling workflow. NLoed offers an accessible, modular, and flexible OED tool-set suited to the wide variety of experimental scenarios encountered in systems biology research. We demonstrate NLOEDs capabilities by applying it to experimental design for characterization of a bacterial optogenetic system. AvailabilityNLoed is available via pip from the PyPi repository; https://pypi.org/project/nloed/. Source code, documentation and examples can be found on Github at https://github.com/ingallslab/NLoed. Contactbingalls@uwaterloo.ca Supplementary informationSupplementary materials are available online.

systems biology↗