Stochastic tuning of gene expression enables cellular adaptation in the absence of pre-existing regulatory circuitry

Cells adapt to familiar changes in their environment by activating predefined regulatory programs that establish adaptive gene expression states. These hard-wired pathways, however, may be inadequate for adaptation to environments never encountered before. Here, we reveal evidence for an alternative mode of gene regulation that enables adaptation to adverse conditions without relying on external sensory information or genetically predetermined cis-regulation. Instead, individual genes achieve optimal expression levels through a stochastic search for improved fitness. By focusing on improving the overall health of the cell, the proposed stochastic tuning mechanism discovers global gene expression states that are fundamentally new and yet optimized for novel environments. We provide experimental evidence for stochastic tuning in the adaptation of Saccharomyces cerevisiae to laboratory-engineered environments that are foreign to its native gene-regulatory network. Stochastic tuning operates locally at individual gene promoters, and its efficacy is modulated by perturbations to chromatin modification machinery

Noninvasive biophotonic imaging for studies of infectious disease

According to World Health Organization estimates, infectious organisms are responsible for approximately one in four deaths worldwide. Animal models play an essential role in the development of vaccines and therapeutic agents but large numbers of animals are required to obtain quantitative microbiological data by tissue sampling. Biophotonic imaging (BPI) is a highly sensitive, nontoxic technique based on the detection of visible light, produced by luciferase-catalysed reactions (bioluminescence) or by excitation of fluorescent molecules, using sensitive photon detectors. The development of bioluminescent/fluorescent microorganisms therefore allows the real-time noninvasive detection of microorganisms within intact living animals. Multiple imaging of the same animal throughout an experiment allows disease progression to be followed with extreme accuracy, reducing the number of animals required to yield statistically meaningful data. In the study of infectious disease, the use of BPI is becoming widespread due to the novel insights it can provide into established models, as well as the impact of the technique on two of the guiding principles of using animals in research, namely reduction and refinement. Here, we review the technology of BPI, from the instrumentation through to the generation of a photonic signal, and illustrate how the technique is shedding light on infection dynamics in vivo

Using enhanced number and brightness to measure protein oligomerization dynamics in live cells

Protein dimerization and oligomerization are essential to most cellular functions, yet measurement of the size of these oligomers in live cells, especially when their size changes over time and space, remains a challenge. A commonly used approach for studying protein aggregates in cells is number and brightness (N&B), a fluorescence microscopy method that is capable of measuring the apparent average number of molecules and their oligomerization (brightness) in each pixel from a series of fluorescence microscopy images. We have recently expanded this approach in order to allow resampling of the raw data to resolve the statistical weighting of coexisting species within each pixel. This feature makes enhanced N&B (eN&B) optimal for capturing the temporal aspects of protein oligomerization when a distribution of oligomers shifts toward a larger central size over time. In this protocol, we demonstrate the application of eN&B by quantifying receptor clustering dynamics using electron-multiplying charge-coupled device (EMCCD)-based total internal reflection microscopy (TIRF) imaging. TIRF provides a superior signal-to-noise ratio, but we also provide guidelines for implementing eN&B in confocal microscopes. For each time point, eN&B requires the acquisition of 200 frames, and it takes a few seconds up to 2 min to complete a single time point. We provide an eN&B (and standard N&B) MATLAB software package amenable to any standard confocal or TIRF microscope. The software requires a high-RAM computer (64 Gb) to run and includes a photobleaching detrending algorithm, which allows extension of the live imaging for more than an hour