Person:

Paulsson, Johan

We introduce a non-intrusive method exploiting post-division single-cell variability to validate protein localization. The results show that Clp proteases, widely reported to form biologically relevant foci, are in fact uniformly distributed inside Escherichia coli cells, and that many commonly used fluorescent proteins (FPs) cause severe mislocalization when fused to homo-oligomers. Re-tagging five other reportedly foci-forming proteins with the most monomeric FP tested suggests the foci were caused by the FPs.

Genetically identical cells sharing an environment can display markedly different phenotypes. It is often unclear how much of this variation derives from chance, external signals, or attempts by individual cells to exert autonomous phenotypic programs. By observing thousands of cells for hundreds of consecutive generations under constant conditions, we dissect the stochastic decision between a solitary, motile state and a chained, sessile state in Bacillus subtilis. The motile state is memoryless, exhibiting no autonomous control over the time spent in the state, whereas chaining is tightly timed. Timing enforces coordination among related cells in the multicellular state. Further, we show that the three-protein regulatory circuit governing the decision is modular, as initiation and maintenance of chaining are genetically separable functions. As stimulation of the same initiating pathway triggers biofilm formation, we argue that autonomous timing allows a trial commitment to multicellularity that external signals could extend.

ABSTRACT The use of fluorescent and luminescent proteins in visualizing proteins has become a powerful tool in understanding molecular and cellular processes within living organisms. This success has resulted in an ever-increasing demand for new and more versatile protein-labeling tools that permit light-based detection of proteins within living cells. In this report, we present data supporting the use of the self-labeling HaloTag protein as a light-emitting reporter for protein fusions within the model prokaryote Escherichia coli. We show that functional protein fusions of the HaloTag can be detected both in vivo and in vitro when expressed within the cytoplasmic or periplasmic compartments of E. coli. The capacity to visually detect proteins localized in various prokaryotic compartments expands today's molecular biologist toolbox and paves the path to new applications. IMPORTANCE: Visualizing proteins microscopically within living cells is important for understanding both the biology of cells and the role of proteins within living cells. Currently, the most common tool is green fluorescent protein (GFP). However, fluorescent proteins such as GFP have many limitations; therefore, the field of molecular biology is always in need of new tools to visualize proteins. In this paper, we demonstrate, for the first time, the use of HaloTag to visualize proteins in two different compartments within the model prokaryote Escherichia coli. The use of HaloTag as an additional tool to visualize proteins within prokaryotes increases our capacity to ask about and understand the role of proteins within living cells.

Many key regulatory proteins in bacteria are present in too low numbers to be detected with conventional methods, which poses a particular challenge for single-cell analyses because such proteins can contribute greatly to phenotypic heterogeneity. Here we develop a microfluidics-based platform that enables single-molecule counting of low-abundance proteins by mechanically slowing-down their diffusion within the cytoplasm of live Escherichia coli (E. coli) cells. Our technique also allows for automated microscopy at high throughput with minimal perturbation to native physiology, as well as viable enrichment/retrieval. We illustrate the method by analysing the control of the master regulator of the E. coli stress response, RpoS, by its adapter protein, SprE (RssB). Quantification of SprE numbers shows that though SprE is necessary for RpoS degradation, it is expressed at levels as low as 3–4 molecules per average cell cycle, and fluctuations in SprE are approximately Poisson distributed during exponential phase with no sign of bursting.

The rate of cell growth is widely recognized as crucial for fitness in bacteria1,2 and a main driver of proteome allocation, but it is unclear how growth rates are ultimately determined. Increasing evidence suggests that other objectives also play key roles3–7, such as the rate of physiological adaption to changing environments8,9. The challenge for cells is that these objectives cannot be independently optimized, and maximizing one may even minimize another. Many such tradeoffs have indeed been hypothesized, but so far they have mostly been based on qualitative correlative studies8–11, and often lacked mechanistic bases. Here we report the occurrence of a tradeoff between steady-state growth and adaptability for Escherichia coli, upon abruptly shifting a growing culture from a preferred carbon source (e.g., glucose) to fermentation products (e.g., acetate). Such transitions, which are common for enteric bacteria, are often accompanied by multi-hour lags before growth resumes. The inverse lag time for dozens of shifts was found to quantitatively exhibit the same linear dependence on pre-shift growth rates, approaching zero (infinite lag) at the maximum growth rate. Metabolomic analysis revealed that the long lags resulted from the depletion of key metabolites due to the sudden reversal of central carbon flux imposed by these nutrient shifts. The metabolic data led us to a model of sequential flux limitation which not only explained the observed universal tradeoff between growth and adaptability, but also generated other quantitative predictions that then could be validated experimentally. This shows that the trade-off reflects the opposing enzyme requirements for effective glycolysis versus gluconeogenesis.

Synthetically engineered genetic circuits can perform a wide range of tasks but generally with lower accuracy than natural systems. Here we revisited the first synthetic genetic oscillator, the repressilator1, and modified it based on principles from stochastic chemistry in single cells. Specifically, we sought to reduce error propagation and information losses, not by adding control loops, but by simply removing existing features. This created highly regular and robust oscillations. Some streamlined circuits kept 14 generation periods over a range of growth conditions and kept phase for hundreds of generations in single cells, allowing cells in flasks and colonies to oscillate synchronously without any coupling between them. Our results show that even the simplest synthetic genetic networks can achieve a precision that rivals natural systems, and emphasize the importance of noise analyses for circuit design in synthetic biology.

Bacteria use a variety of stress-sensing systems to sense and respond to diverse stressors and to ensure their survival under adverse conditions. The gram-positive bacterium Bacillus subtilis responds to energy stress (ATP depletion) and to environmental stressors using two distinct stress-sensing pathways that converge on the alternative sigma factor σB to provoke a general stress response. Past efforts to study the σB stress response in bulk culture and on agarose pads were unable to visualize the responses of individual cells under tightly controlled conditions for extended periods of time. Here we use a microfluidics-based strategy to discern the basic features of σB activation in single cells in response to energy and environmental stress, both immediately upon stressor exposure and for tens of generations thereafter. Upon energy stress at various levels of stressor, cells exhibited fast, transient, and amplitude-modulated responses but not frequency modulation as previously reported. Upon environmental stress, which is mediated by the stressosome complex, wild-type cells primarily exhibited a transient and amplitude-modulated response. However, mutant cells producing only one of the four paralogous RsbR stressosome proteins showed striking and previously unseen differences. Whereas RsbRA-only cells mimicked the wild type, RsbRC-only cells displayed a slower but sustained overall response composed of repeated activation events in single cells.

Single-cell genetic screens can be incredibly powerful, but current high-throughput platforms do not track dynamics, and even for non-dynamic properties they struggle to separate mutants of interest from phenotypic outliers of the wild-type population. Here we introduce SIFT, Single-cell Isolation Following Time-lapse imaging, to address these limitations. After imaging and tracking individual bacteria for tens of consecutive generations under tightly controlled growth conditions, cells of interest are isolated and propagated for downstream analysis, free of contamination and without genetic or physiological perturbations. The initial platform can characterize tens of thousands of cell lineages per day, making it possible to accurately screen complex phenotypes without the need for barcoding or genetic modifications. We applied SIFT to identify a set of ultraprecise synthetic gene oscillators, with mutants spanning a 30-fold range of average periods. This revealed novel design principles in synthetic biology and demonstrated the power of SIFT to reliably screen diverse dynamic phenotypes.