Stefan Helfrich

Spatiotemporal microbial single-cell analysis using a high-throughput microfluidics cultivation platform

Cell‐to‐cell heterogeneity typically evolves due to a manifold of biological and environmental factors and special phenotypes are often relevant for the fate of the whole population but challenging to detect during conventional analysis. We demonstrate a microfluidic single‐cell cultivation platform that incorporates several hundred growth chambers, in which isogenic bacteria microcolonies growing in cell monolayers are tracked by automated time‐lapse microscopy with spatiotemporal resolution. The device was not explicitly developed for a specific organism, but has a very generic configuration suitable for various different microbial organisms. In the present study, we analyzed Corynebacterium glutamicum microcolonies, thereby generating complete lineage trees and detailed single‐cell data on division behavior and morphology in order to demonstrate the platforms overall capabilities. Furthermore, the occurrence of spontaneously induced stress in individual C. glutamicum cells was investigated by analyzing strains with genetically encoded reporter systems and optically visualizing SOS response. The experiments revealed spontaneous SOS induction in the absence of any external trigger comparable to results obtained by flow cytometry (FC) analyzing cell samples from conventional shake flask cultivation. Our microfluidic setup delivers detailed single‐cell data with spatial and temporal resolution; complementary information to conventional FC results.

Live cell imaging of SOS and prophage dynamics in isogenic bacterial populations

Almost all bacterial genomes contain DNA of viral origin, including functional prophages or degenerated phage elements. A frequent but often unnoted phenomenon is the spontaneous induction of prophage elements (SPI) even in the absence of an external stimulus. In this study, we have analyzed SPI of the large, degenerated prophage CGP3 (187 kbp), which is integrated into the genome of the Gram‐positive Corynebacterium glutamicum ATCC 13032. Time‐lapse fluorescence microscopy of fluorescent reporter strains grown in microfluidic chips revealed the sporadic induction of the SOS response as a prominent trigger of CGP3 SPI but also displayed a considerable fraction (∼30%) of RecA‐independent SPI. Whereas approx. 20% of SOS‐induced cells recovered from this stress and resumed growth, the spontaneous induction of CGP3 always led to a stop of growth and likely cell death. A carbon source starvation experiment clearly emphasized that SPI only occurs in actively proliferating cells, whereas sporadic SOS induction was still observed in resting cells. These data highlight the impact of sporadic DNA damage on the activity of prophage elements and provide a time‐resolved, quantitative description of SPI as general phenomenon of bacterial populations.

Rapid inoculation of single bacteria into parallel picoliter fermentation chambers

Microfluidic single-cell cultivation devices have been successfully utilized in a variety of biological research fields. One major obstacle to the successful implementation of high throughput single-cell cultivation technology is the requirement for a simple, fast and reliable cell inoculation procedure. In the present report, an air-bubble-based cell loading methodology is described and validated for inoculating single bacteria into multiple picoliter sized growth chambers arranged in a highly parallel manner. It is shown that the application of the injected air bubble can serve as a reproducible mechanism to modify laminar flow conditions. In this way, convective flow was temporarily induced in more than 1000 cultivation chambers simultaneously, which under normal conditions operate exclusively under diffusive mass transport. Within an inoculation time of 100 s, Corynebacterium glutamicum cells were inoculated by convection at minimal stress level and single bacteria remain successfully trapped by cell-wall interactions. The procedure is easy, fast, gentle and requires only minimal fluidic control and equipment. The technique is well suited for microbial cell loading into commonly used microfluidic growth sites arranged in parallel intended for high throughput single-cell analysis.

Vizardous: interactive analysis of microbial populations with single cell resolution

MOTIVATION Single cell time-lapse microscopy is a powerful method for investigating heterogeneous cell behavior. Advances in microfluidic lab-on-a-chip technologies and live-cell imaging render the parallel observation of the development of individual cells in hundreds of populations possible. While image analysis tools are available for cell detection and tracking, biologists are still confronted with the challenge of exploring and evaluating this data. RESULTS We present the software tool Vizardous that assists scientists with explorative analysis and interpretation tasks of single cell data in an interactive, configurable and visual way. With Vizardous, lineage tree drawings can be augmented with various, time-resolved cellular characteristics. Associated statistical moments bridge the gap between single cell and the population-average level. AVAILABILITY AND IMPLEMENTATION The software, including documentation and examples, is available as executable Java archive as well as in source form at https://github.com/modsim/vizardous. CONTACT k.noeh@fz-juelich.de. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Image-Based Single Cell Profiling: High-Throughput Processing of Mother Machine Experiments

Background Microfluidic lab-on-chip technology combined with live-cell imaging has enabled the observation of single cells in their spatio-temporal context. The mother machine (MM) cultivation system is particularly attractive for the long-term investigation of rod-shaped bacteria since it facilitates continuous cultivation and observation of individual cells over many generations in a highly parallelized manner. To date, the lack of fully automated image analysis software limits the practical applicability of the MM as a phenotypic screening tool. Results We present an image analysis pipeline for the automated processing of MM time lapse image stacks. The pipeline supports all analysis steps, i.e., image registration, orientation correction, channel/cell detection, cell tracking, and result visualization. Tailored algorithms account for the specialized MM layout to enable a robust automated analysis. Image data generated in a two-day growth study (≈ 90 GB) is analyzed in ≈ 30 min with negligible differences in growth rate between automated and manual evaluation quality. The proposed methods are implemented in the software molyso (MOther machine AnaLYsis SOftware) that provides a new profiling tool to analyze unbiasedly hitherto inaccessible large-scale MM image stacks. Conclusion Presented is the software molyso, a ready-to-use open source software (BSD-licensed) for the unsupervised analysis of MM time-lapse image stacks. molyso source code and user manual are available at https://github.com/modsim/molyso.

Non-Invasive Microbial Metabolic Activity Sensing at Single Cell Level by Perfusion of Calcein Acetoxymethyl Ester

Phase contrast microscopy cannot give sufficient information on bacterial metabolic activity, or if a cell is dead, it has the fate to die or it is in a viable but non-growing state. Thus, a reliable sensing of the metabolic activity helps to distinguish different categories of viability. We present a non-invasive instantaneous sensing method using a fluorogenic substrate for online monitoring of esterase activity and calcein efflux changes in growing wild type bacteria. The fluorescent conversion product of calcein acetoxymethyl ester (CAM) and its efflux indicates the metabolic activity of cells grown under different conditions at real-time. The dynamic conversion of CAM and the active efflux of fluorescent calcein were analyzed by combining microfluidic single cell cultivation technology and fluorescence time lapse microscopy. Thus, an instantaneous and non-invasive sensing method for apparent esterase activity was created without the requirement of genetic modification or harmful procedures. The metabolic activity sensing method consisting of esterase activity and calcein secretion was demonstrated in two applications. Firstly, growing colonies of our model organism Corynebacterium glutamicum were confronted with intermittent nutrient starvation by interrupting the supply of iron and carbon, respectively. Secondly, bacteria were exposed for one hour to fatal concentrations of antibiotics. Bacteria could be distinguished in growing and non-growing cells with metabolic activity as well as non-growing and non-fluorescent cells with no detectable esterase activity. Microfluidic single cell cultivation combined with high temporal resolution time-lapse microscopy facilitated monitoring metabolic activity of stressed cells and analyzing their descendants in the subsequent recovery phase. Results clearly show that the combination of CAM with a sampling free microfluidic approach is a powerful tool to gain insights in the metabolic activity of growing and non-growing bacteria.

Inheritance of Cell-Cycle Duration in the Presence of Periodic Forcing

Periodic forcing of nonlinear oscillators leads to a large number of dynamic behaviors. The coupling of the cell cycle to the circadian clock provides a biological realization of such forcing. A previous model of forcing leads to nontrivial relations between correlations along cell lineages. Here, we present a simplified two-dimensional nonlinear map for the periodic forcing of the cell cycle. Using high-throughput single-cell microscopy, we have studied the correlations between cell-cycle duration in discrete lineages of several different organisms, including those with known coupling to a circadian clock and those without known coupling to a circadian clock. The model reproduces the paradoxical correlations and predicts new features that can be compared with the experimental data. By fitting the model to the data, we extract the important parameters that govern the dynamics. Interestingly, the model reproduces bimodal distributions for