Bacterial variability in the mammalian gut captured by a single-cell synthetic oscillator

David T Riglar,Lorena G Lyon,Alexander D Naydich,David L Richmond,Somenath Bakshi,Andrew A Verdegaal,Emanuele Leoncini,Laurent Potvin-Trottier,Pamela A Silver,Johan Paulsson

doi:10.1038/s41467-019-12638-z

Abstract

Synthetic gene oscillators have the potential to control timed functionsand periodic gene expression in engineered cells. Such oscillators have been refinedin bacteria in vitro, however, these systems have lacked the robustness andprecision necessary for applications in complex in vivo environments, such as themammalian gut. Here, we demonstrate the implementation of a synthetic oscillatorcapable of keeping robust time in the mouse gut over periods of days. Theoscillations provide a marker of bacterial growth at a single-cell level enablingquantification of bacterial dynamics in response to inflammation and underlyingvariations in the gut microbiota. Our work directly detects increased bacterialgrowth heterogeneity during disease and differences between spatial niches in thegut, demonstrating the deployment of a precise engineered genetic oscillator inreal-life settings.

Highlights

Differential bacterial growth underlies colonization of the gut by commensal species during childhood, pathogenic infection, and the establishment of dysbiosis in the microbiota that has been linked to an increasing array of diseases[14]
Because bacterial colonies expand radially in a uniform manner, with division only occurring at the periphery[31], synchronous repressilator 2.0 oscillations create stable macroscopic rings when fluorescent reporters are driven under repressilator 2.0 control (Fig. 1b)[5]
We developed a workflow for bacterial colony image capture and processing, which we call Repressilatorbased INference of Growth at Single-cell level (RINGS) (Fig. 1d)

Summary

Introduction

Differential bacterial growth underlies colonization of the gut by commensal species during childhood, pathogenic infection, and the establishment of dysbiosis in the microbiota that has been linked to an increasing array of diseases[14]. Several methods have been developed to estimate instantaneous, average bacterial growth rates using metagenomic sequencing data[15,16,17,18]. Single-cell methods offer different advantages, in particular providing valuable information about growth variability across a population[21,22,23,24,25,26,27,28,29] Such information is crucial to our understanding of bacterial growth in the gut, which includes a broad range of niches with different growth favorability for any given bacterial species, potentially limiting the interpretation of average growth measures. We develop and validate an imaging analysis pipeline to determine repressilator phase In this way, we investigate bacterial population dynamics during colonization of, and growth within, the mammalian gut. We reveal robust functionality and controllability of the repressilator 2.0 across diverse host and environmental contexts

Methods

Results

Conclusion