Daniel R. Larson

Precise Nanometer Localization Analysis for Individual Fluorescent Probes

Calculation of the centroid of the images of individual fluorescent particles and molecules allows localization and tracking in light microscopes to a precision about an order of magnitude greater than the microscope resolution. The factors that limit the precision of these techniques are examined and a simple equation derived that describes the precision of localization over a wide range of conditions. In addition, a localization algorithm motivated from least-squares fitting theory is constructed and tested both on image stacks of 30-nm fluorescent beads and on computer-generated images (Monte Carlo simulations). Results from the algorithm show good agreement with the derived precision equation for both the simulations and actual images. The availability of a simple equation to describe localization precision helps investigators both in assessing the quality of an experimental apparatus and in directing attention to the factors that limit further improvement. The precision of localization scales as the inverse square root of the number of photons in the spot for the shot noise limited case and as the inverse of the number of photons for the background noise limited case. The optimal image magnification depends on the expected number of photons and background noise, but, for most cases of interest, the pixel size should be about equal to the standard deviation of the point spread function.

Single-RNA counting reveals alternative modes of gene expression in yeast

Proper execution of transcriptional programs is a key requirement of gene expression regulation, demanding accurate control of timing and amplitude. How precisely the transcription machinery fulfills this task is not known. Using an in situ hybridization approach that detects single mRNA molecules, we measured mRNA abundance and transcriptional activity within single Saccharomyces cerevisiae cells. We found that expression levels for particular genes are higher than initially reported and can vary substantially among cells. However, variability for most constitutively expressed genes is unexpectedly small. Combining single-transcript measurements with computational modeling indicates that low expression variation is achieved by transcribing genes using single transcription-initiation events that are clearly separated in time, rather than by transcriptional bursts. In contrast, PDR5, a gene regulated by the transcription coactivator complex SAGA, is expressed using transcription bursts, resulting in larger variation. These data directly demonstrate the existence of multiple expression modes used to modulate the transcriptome.

Illuminating the Chemistry of Life: Design, Synthesis, and Applications of “Caged” and Related Photoresponsive Compounds

Biological systems are characterized by a level of spatial and temporal organization that often lies beyond the grasp of present day methods. Light-modulated bioreagents, including analogs of low molecular weight compounds, peptides, proteins, and nucleic acids, represent a compelling strategy to probe, perturb, or sample biological phenomena with the requisite control to address many of these organizational complexities. Although this technology has created considerable excitement in the chemical community, its application to biological questions has been relatively limited. We describe the challenges associated with the design, synthesis, and use of light-responsive bioreagents; the scope and limitations associated with the instrumentation required for their application; and recent chemical and biological advances in this field.

Real-Time Observation of Transcription Initiation and Elongation on an Endogenous Yeast Gene

In yeast, the initiation of gene expression is stochastic and is controlled by transcription factor search times. Cellular messenger RNA levels are achieved by the combinatorial complexity of factors controlling transcription, yet the small number of molecules involved in these pathways fluctuates stochastically. It has not yet been experimentally possible to observe the activity of single polymerases on an endogenous gene to elucidate how these events occur in vivo. Here, we describe a method of fluctuation analysis of fluorescently labeled RNA to measure dynamics of nascent RNA—including initiation, elongation, and termination—at an active yeast locus. We find no transcriptional memory between initiation events, and elongation speed can vary by threefold throughout the cell cycle. By measuring the abundance and intranuclear mobility of an upstream transcription factor, we observe that the gene firing rate is directly determined by trans-activating factor search times.

Single-molecule mRNA decay measurements reveal promoter- regulated mRNA stability in yeast.

Messenger RNA decay measurements are typically performed on a population of cells. However, this approach cannot reveal sufficient complexity to provide information on mechanisms that may regulate mRNA degradation, possibly on short timescales. To address this deficiency, we measured cell cycle-regulated decay in single yeast cells using single-molecule FISH. We found that two genes responsible for mitotic progression, SWI5 and CLB2, exhibit a mitosis-dependent mRNA stability switch. Their transcripts are stable until mitosis, when a precipitous decay eliminates the mRNA complement, preventing carryover into the next cycle. Remarkably, the specificity and timing of decay is entirely regulated by their promoter, independent of specific cis mRNA sequences. The mitotic exit network protein Dbf2p binds to SWI5 and CLB2 mRNAs cotranscriptionally and regulates their decay. This work reveals the promoter-dependent control of mRNA stability, a regulatory mechanism that could be employed by a variety of mRNAs and organisms.

Eukaryotic transcriptional dynamics: from single molecules to cell populations

Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.

Cortactin phosphorylation regulates cell invasion through a pH-dependent pathway

Cortactin phosphorylation induces recruitment of the sodium-hydrogen exchanger NHE1 to invadopodia, resulting in pH changes that regulate cortactin-cofilin binding and invadopodium dynamics.

A single molecule view of gene expression.

Analyzing the expression of single genes in single cells appears minimalistic in comparison to gene expression studies based on more global approaches. However, stimulated by advances in imaging technologies, single-cell studies have become an essential tool in understanding the rules that govern gene expression. This quantitative view of single-cell gene expression is based on counting mRNAs in single cells, monitoring transcription in real time, and visualizing single proteins. Parallel advances in mathematical models based on stochastic, discrete descriptions of biochemical processes have provided crucial insights into the underlying cellular mechanisms that control expression. The view that has emerged is rooted in a probabilistic understanding of cellular processes that quantitatively explains both the mean and the variation observed in gene-expression patterns among single cells. Thus, the close coupling between imaging and mathematical theory has established single-cell analysis as an essential branch of systems biology.

Temporally resolved interactions between antigen-stimulated IgE receptors and Lyn kinase on living cells

Upon cross-linking by antigen, the high affinity receptor for immunoglobulin E (IgE), FcɛRI, is phosphorylated by the Src family tyrosine kinase Lyn to initiate mast cell signaling, leading to degranulation. Using fluorescence correlation spectroscopy (FCS), we observe stimulation-dependent associations between fluorescently labeled IgE-FcɛRI and Lyn-EGFP on individual cells. We also simultaneously measure temporal variations in the lateral diffusion of these proteins. Antigen-stimulated interactions between these proteins detected subsequent to the initiation of receptor phosphorylation exhibit time-dependent changes, suggesting multiple associations between FcɛRI and Lyn-EGFP. During this period, we also observe a persistent decrease in Lyn-EGFP lateral diffusion that is dependent on Src family kinase activity. These stimulated interactions are not observed between FcɛRI and a chimeric EGFP that contains only the membrane-targeting sequence from Lyn. Our results reveal real-time interactions between Lyn and cross-linked FcɛRI implicated in downstream signaling events. They demonstrate the capacity of FCS cross-correlation analysis to investigate the mechanism of signaling-dependent protein–protein interactions in intact, living cells.

Imaging Transcription in Living Cells

The advent of new technologies for the imaging of living cells has made it possible to determine the properties of transcription, the kinetics of polymerase movement, the association of transcription factors, and the progression of the polymerase on the gene. We report here the current state of the field and the progress necessary to achieve a more complete understanding of the various steps in transcription. Our Consortium is dedicated to developing and implementing the technology to further this understanding.