Biology subjects

Tabor, J. J.

Publications and source records attributed to Tabor, J. J..

9 recordsLinked to original sources

bioRxiv2025

Changes in Spo0A~P pulsing frequency control biofilm matrix deactivation

Under starvation conditions, B. subtilis survives by differentiating into one of two cell types: biofilm matrix-producing cells or sporulating cells. These two cell-differentiation pathways are activated by the same phosphorylated transcription factor - Spo0A~P. Despite sharing the activation mechanism, these cell fates are mutually exclusive at the single-cell level. This decision has been shown to be controlled by the effects of growth rate on gene dosage and protein dilution in the biofilm matrix production network. In this work, we explore an alternative mechanism of growth rate-mediated control of this cell fate decision. Namely, using deterministic and stochastic modeling, we investigate how the growth-rate-dependent pulsing dynamics of Spo0A~P affect biofilm matrix deactivation and activation. Specifically, we show that the Spo0A~P pulsing frequency tunes the biofilm matrix deactivation probability without affecting the probability of biofilm matrix activation. Interestingly, we found that DNA replication is the cell cycle stage that most substantially contributes to the deactivation of biofilm matrix production. Finally, we report that the deactivation of biofilm matrix production is not primarily regulated by the effects of growth rate on gene dosage and protein dilution. Instead, it is driven by changes in the pulsing period of Spo0A~P. In summary, our findings elucidate the mechanism governing biofilm deactivation during the late stages of starvation, thereby advancing our understanding of how bacterial networks interpret dynamic transcriptional regulatory signals to control stress-response pathways. Author SummaryBacteria have evolved various adaptation mechanisms to survive under challenging environmental conditions. For instance, under mild starvation, B. subtilis bacteria form biofilms -- communities of cells encapsulated in a protective extracellular matrix. On the other hand, these bacteria differentiate into highly resistant spores under severe starvation. Interestingly, sporulating cells are often found within biofilm communities, but they do not contribute to biofilm matrix production. This is thought to be an energy-conservation strategy, as biofilm formation is an energy-intensive process and is therefore halted before sporulation begins. Though previous work has focused on the mechanisms driving biofilm disassembly, few studies have explored the regulatory processes that B. subtilis employs to halt matrix production prior to starting sporulation. In this study, we use mathematical models to demonstrate that the temporal dynamics of the biofilm master regulator Spo0A~P control the deactivation of matrix production. Understanding the regulation of biofilm, a common lifestyle in bacteria, can lead to the development of synthetic strategies to either enhance or disrupt biofilm formation, with potential applications in medicine and industry.

systems biology↗

bioRxiv2024

Probiotic acoustic biosensors for noninvasive imaging of gut inflammation

Inflammatory bowel diseases (IBD) affect millions of people globally, result in severe symptoms, and are difficult to diagnose and monitor - often necessitating the use of invasive and costly methods such as colonoscopies or endoscopies. Engineered gut bacteria offer a promising alternative due to their ability to persist in the gastrointestinal (GI) tract and sense and respond to specific environmental signals. However, probiotics that have previously been engineered to report on inflammatory and other disease biomarkers in the Gl tract rely on fluorescent or bioluminescent reporters, whose signals cannot be resolved in situ due to the poor penetration of light in tissue. To overcome this limitation, we introduce probiotic biosensors that can be imaged in situ using ultrasound - a widely available, inexpensive imaging modality providing sub-mm spatial resolution deep inside the body. These biosensors are based on the clinically approved probiotic bacterium E. coli Nissle, which we engineered to transiently colonize the GI tract, sense inflammatory biomarkers, and respond by expressing air-filled sound-scattering protein nanostructures called gas vesicles. After optimizing biomolecular signaling circuits to respond sensitively to the biomarkers thiosulfate and tetrathionate and produce strong and stable ultrasound contrast, we validated our living biosensors in vivo by noninvasively imaging antibiotic-induced inflammation in mice. By connecting cell-based diagnostic agents to ultrasound, this "diagnostic yogurt" will make it easier, cheaper, and less painful to diagnose and monitor IBD or other GI conditions.

bioengineering↗

bioRxiv2023

Microbial biosensor for sensing and treatment of intestinal inflammation

Substantial synthetic biology efforts have been made to engineer biosensors to detect intestinal inflammation, however none target the most clinically accepted biomarker, calprotectin. To develop an in situ biosensor for calprotectin, we optimized a zinc uptake regulator (Zur) regulated promoter coupled with a memory circuit that can detect and record intestinal inflammation in vivo. The level of activation strongly correlates with calprotectin levels in the colon of two independent mouse models of colitis. Coupling of the biosensor with the production of the anti-inflammatory cytokine IL-10 allowed for the resolution of chemically induced colitis, demonstrating the ability of the biosensor to sense and respond to disease. This work highlights the utility of developing synthetic organisms for the diagnosis and treatment of intestinal disease using clinically validated biomarkers. One sentence summaryWe have optimized a microbial biosensor to detect and respond to the clinically relevant intestinal inflammation biomarker calprotectin.

synthetic biology↗

bioRxiv2021

Meeting Measurement Precision Requirements for Effective Engineering of Genetic Regulatory Networks

Reliable, predictable engineering of cellular behavior is one of the key goals of synthetic biology. As the field matures, biological engineers will become increasingly reliant on computer models that allow for the rapid exploration of design space prior to the more costly construction and characterization of candidate designs. The efficacy of such models, however, depends on the accuracy of their predictions, the precision of the measurements used to parameterize the models, and the tolerance of biological devices for imperfections in modeling and measurement. To better understand this relationship, we have derived an Engineering Error Inequality that provides a quantitative mathematical bound on the relationship between predictability of results, model accuracy, measurement precision, and device characteristics. We apply this relation to estimate measurement precision requirements for engineering genetic regulatory networks given current model and device characteristics, recommending a target standard deviation of 1.5-fold. We then compare these requirements with the results of an interlaboratory study to validate that these requirements can be met via flow cytometry with matched instrument channels and an independent calibrant. Based on these results, we recommend a set of best practices for quality control of flow cytometry data and discuss how these might be extended to other measurement modalities and applied to support further development of genetic regulatory network engineering.

synthetic biology↗

bioRxiv2021

High-throughput discovery of peptide activators of a bacterial sensor kinase

Bacteria use two-component system (TCS) signaling pathways to sense and respond to peptides involved in host defense, quorum sensing, and inter-bacterial warfare. However, little is known about the peptide-sensing capabilities of these TCSs. Here, we develop a high-throughput E. coli display method to characterize the effects of human antimicrobial peptides (AMPs) on the pathogenesis-regulating TCS PhoPQ of Salmonella Typhimurium. We find that PhoPQ senses AMPs comprising diverse sequences, structures, and biological functions. Using thousands of AMP variants, we identify sub-domains and biophysical features responsible for PhoPQ activation. We show that most of the newfound activators induce PhoPQ in S. Typhimurium, suggesting a role in virulence regulation. Finally, we find that PhoPQ homologs from Klebsiella pneumoniae and extraintestinal pathogenic E. coli, which occupy different in vivo niches, exhibit distinct AMP response profiles. Our high-throughput method enables new insights into the specificities, mechanisms, and evolutionary dynamics of TCS-mediated peptide sensing in bacteria.

synthetic biology↗

bioRxiv2021

Independent control of mean and noise by convolution of gene expression distributions

Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from a single promoter. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.

synthetic biology↗

bioRxiv2020

Optogenetic control of gut bacterial metabolism

Gut microbial metabolism is associated with host longevity. However, because it requires direct manipulation of microbial metabolism in situ, establishing a causal link between these two processes remains challenging. We demonstrate an optogenetic method to control gene expression and metabolite production from bacteria residing in the host gut. We genetically engineer an Escherichia coli strain that synthesizes and secretes colanic acid (CA) under the quantitative control of light. Using this optogenetically-controlled strain to induce CA production directly in the Caenorhabditis elegans gut, we reveal the local effect of CA in protecting intestinal mitochondria from stress-induced hyper-fragmentation. We also exploit different intensities of light to determine that the lifespan-extending effect of CA is positively correlated with its levels produced from bacteria. Our results show that optogenetic control offers a rapid, reversible and quantitative way to fine-tune gut bacterial metabolism and uncover its local and systemic effects on host health and aging.

synthetic biology↗

bioRxiv2019

Multiplexing cell-cell communication

The engineering of advanced multicellular behaviors, such as the programmed growth of biofilms or tissues, requires cells to communicate multiple aspects of physiological information. Unfortunately, few cell-cell communication systems have been developed for synthetic biology. Here, we engineer a genetically-encoded channel selector device that enables a single communication system to transmit two separate intercellular conversations. Our design comprises multiplexer and demultiplexer sub-circuits constructed from a total of 12 CRISPRi-based transcriptional logic gates, an acyl homoserine lactone-based communication module, and three inducible promoters that enable small molecule control over the conversations. Experimentally-parameterized mathematical models of the sub-components predict the steady state and dynamical performance of the full system. Multiplexed cell-cell communication has applications in synthetic development, metabolic engineering, and other areas requiring the coordination of multiple pathways amongst a community of cells.\n\nOne Sentence SummaryWe have engineered a synthetic genetic system that enables bacteria to have two separate conversations over a single chemical \"wire\" by separating the conversations in time.

synthetic biology↗

bioRxiv2016

A two-state photoconversion model predicts the spectral response dynamics of optogenetic systems

In optogenetics, light signals are used to control genetically engineered photoreceptors, and in turn manipulate biological pathways with unmatched precision. Recently, evolved photoreceptors with diverse in vitro-measured wavelength and intensity-dependent photoswitching properties have been repurposed for synthetic control of gene expression, proteolysis, and numerous other cellular processes. However, the relationship between the input light spectrum and in vivo photoreceptor response dynamics is poorly understood, restricting the utility of these optogenetic tools. Here, we advance a classic in vitro two-state photoreceptor model to reflect the in vivo environment, and combine it with simplified mathematical descriptions of signal transduction and output gene expression through our previously engineered green/red and red/far red photoreversible bacterial two-component systems (TCSs). Additionally, we leverage our recent open-source optical instrument to develop a workflow of spectral and dynamical characterization experiments to parameterize the model for both TCSs. To validate our approach, we challenge the model to predict experimental responses to a series of complex light signals very different from those used during parameterization. We find that the model generalizes remarkably well, predicting the results of all categories of experiments with high quantitative accuracy for both systems. Finally, we exploit this predictive power to program two simultaneous and independent dynamical gene expression signals in bacteria expressing both TCSs. This multiplexed gene expression programming approach will enable entirely new studies of how metabolic, signaling, and decision-making pathways integrate multiple gene expression signals. Additionally, our approach should be compatible with a wide range of optogenetic tools and model organisms.\n\nSignificance statementLight-switchable signaling pathways (optogenetic tools) enable precision studies of how biochemical networks underlie cellular behaviors. We have developed a versatile mathematical model based on a two-state photoconversion mechanism that we have applied to the E. coli CcaSR and Cph8-OmpR optogenetic tools. This model enables accurate prediction of the gene expression response to virtually any light source or mixture of light sources. We express both optogenetic tools in the same cell and apply our model to program two simultaneous and independent gene expression signals in the same cell. This method can be used to study how biological pathways integrate multiple inputs and should be extensible to other optogenetic tools and host organisms.

synthetic biology↗