Biomedical subjects

Brian L Sprague

Publications and source records attributed to Brian L Sprague.

7 recordsLinked to original sources

PubMed2006

Analysis of binding at a single spatially localized cluster of binding sites by fluorescence recovery after photobleaching.

Cells contain many subcellular structures in which specialized proteins locally cluster. Binding interactions within such clusters may be analyzed in live cells using models for fluorescence recovery after photobleaching (FRAP). Here we analyze a three-dimensional FRAP model that accounts for a single spatially localized cluster of binding sites in the presence of both diffusion and impermeable boundaries. We demonstrate that models completely ignoring the spatial localization of binding yield poor estimates for the binding parameters within the binding site cluster. In contrast, we find that ignoring only the restricted axial height of the binding-site cluster is far less detrimental, thereby enabling the use of computationally less expensive models. We also identify simplified solutions to the FRAP model for limiting behaviors where either diffusion or binding dominate. We show how ignoring a role for diffusion can sometimes produce serious errors in binding parameter estimation. We illustrate application of the method by analyzing binding of a transcription factor, the glucocorticoid receptor, to a tandem array of mouse mammary tumor virus promoter sites in live cells, obtaining an estimate for an in vivo binding constant (10(-7) M), and a first approximation of an upper bound on the transcription-factor residence time at the promoter (approximately 170 ms). These FRAP analysis tools will be important for measuring key cellular binding parameters necessary for a complete and accurate description of the networks that regulate cellular behavior.

Adenocarcinoma↗

PubMed2005

Partner-regulated interaction of IFN regulatory factor 8 with chromatin visualized in live macrophages.

IFN regulatory factor (IRF) 8 is a transcription factor that directs macrophage differentiation. By fluorescence recovery after photobleaching, we visualized the movement of IRF8-GFP in differentiating macrophages. Recovery data fitted to mathematical models revealed two binding states for IRF8. The majority of IRF8 was highly mobile and transiently interacted with chromatin, whereas a small fraction of IRF8 bound to chromatin more stably. IRF8 mutants that did not stimulate macrophage differentiation showed a faster recovery, revealing little interaction with chromatin. A macrophage activation signal by IFN-gamma/LPS led to a global slowdown of IRF8 movement, leading to increased chromatin binding. In fibroblasts where IRF8 has no known function, WT IRF8 moved as fast as the mutants, indicating that IRF8 does not interact with chromatin in these cells. However, upon introduction of IRF8 binding partners, PU.1 and/or IRF1, the mobility of IRF8 was markedly reduced, producing a more stably bound component. Together, IRF8-chromatin interaction is dynamic in live macrophages and influenced by partner proteins and immunological stimuli.

Animals↗

PubMed2005

Tension-dependent regulation of microtubule dynamics at kinetochores can explain metaphase congression in yeast.

During metaphase in budding yeast mitosis, sister kinetochores are tethered to opposite poles and separated, stretching their intervening chromatin, by singly attached kinetochore microtubules (kMTs). Kinetochore movements are coupled to single microtubule plus-end polymerization/depolymerization at kinetochore attachment sites. Here, we use computer modeling to test possible mechanisms controlling chromosome alignment during yeast metaphase by simulating experiments that determine the 1) mean positions of kinetochore Cse4-GFP, 2) extent of oscillation of kinetochores during metaphase as measured by fluorescence recovery after photobleaching (FRAP) of kinetochore Cse4-GFP, 3) dynamics of kMTs as measured by FRAP of GFP-tubulin, and 4) mean positions of unreplicated chromosome kinetochores that lack pulling forces from a sister kinetochore. We rule out a number of possible models and find the best fit between theory and experiment when it is assumed that kinetochores sense both a spatial gradient that suppresses kMT catastrophe near the poles and attachment site tension that promotes kMT rescue at higher amounts of chromatin stretch.

Cell Cycle Proteins↗

PubMed2005

FRAP analysis of binding: proper and fitting.

Dynamic molecular interactions are fundamental to all cellular processes. In vivo analyses of these interactions are frequently done using fluorescence recovery after photobleaching (FRAP). Proper interpretation of FRAP data yields information about the binding interactions of fluorescently tagged molecules, including the number of binding states and the binding strength of each state. This binding information can be gleaned from appropriate models of the process underlying a FRAP recovery. Continued application and development of these approaches promise to provide crucial information for a quantitative description of the molecular networks that regulate cellular function.

Diffusion↗

PubMed2004

Dynamic interactions of a transcription factor with DNA are accelerated by a chromatin remodeller.

Most components in the nucleus are in a state of dynamic equilibrium maintained by the rapid mobility of nuclear proteins within and between compartments. Mobility is believed to reflect transient binding, but the identity of the binding sites and the function of the transient interactions are a matter of debate. Furthermore, we know little about how these processes may be regulated. Here, we investigate the nature and regulation of transcription factor binding and mobility in the nucleus of yeast cells. Using the Ace1p transcriptional activator, we show that nonspecific DNA binding interactions seem to have a role in retarding Ace1p nuclear mobility. Surprisingly, we find that this binding is a regulated process using a chromatin remodeller to speed up Ace1p interactions at nonspecific DNA sites. Our results suggest that transcription factor mobility represents a diffusion-driven, rapid sampling of nonspecific DNA sites, and that chromatin remodellers accelerate this genomic search process.

Binding Sites↗

PubMed2004

Analysis of binding reactions by fluorescence recovery after photobleaching.

Fluorescence recovery after photobleaching (FRAP) is now widely used to investigate binding interactions in live cells. Although various idealized solutions have been identified for the reaction-diffusion equations that govern FRAP, there has been no comprehensive analysis or systematic approach to serve as a guide for extracting binding information from an arbitrary FRAP curve. Here we present a complete solution to the FRAP reaction-diffusion equations for either single or multiple independent binding interactions, and then relate our solution to the various idealized cases. This yields a coherent approach to extract binding information from FRAP data which we have applied to the question of transcription factor mobility in the nucleus. We show that within the nucleus, the glucocorticoid receptor is transiently bound to a single state, with each molecule binding on average 65 sites per second. This rapid sampling is likely to be important in finding a specific promoter target sequence. Further we show that this predominant binding state is not the nuclear matrix, as some studies have suggested. We illustrate how our analysis provides several self-consistency checks on a FRAP fit. We also define constraints on what can be estimated from FRAP data, show that diffusion should play a key role in many FRAP recoveries, and provide tools to test its contribution. Overall our approach establishes a more general framework to assess the role of diffusion, the number of binding states, and the binding constants underlying a FRAP recovery.

Algorithms↗

PubMed2003

Mechanisms of microtubule-based kinetochore positioning in the yeast metaphase spindle.

It has been hypothesized that spatial gradients in kMT dynamic instability facilitate mitotic spindle formation and chromosome movement. To test this hypothesis requires the analysis of kMT dynamics, which have not been resolved at the single kMT level in living cells. The budding yeast spindle offers an attractive system in which to study kMT dynamics because, in contrast to animal cells, there is only one kMT per kinetochore. To visualize metaphase kMT plus-end dynamics in yeast, a strain containing a green fluorescent protein fusion to the kinetochore protein, Cse4, was imaged by fluorescence microscopy. Although individual kinetochores were not resolvable, we found that models of kMT dynamics could be evaluated by simulating the stochastic kMT dynamics and then simulating the fluorescence imaging of kMT plus-end-associated kinetochores. Statistical comparison of model-predicted images to experimentally observed images demonstrated that a pure dynamic instability model for kMT dynamics in the yeast metaphase spindle was unacceptable. However, when a temporally stable spatial gradient in the catastrophe or rescue frequency was added to the model, there was reasonable agreement between the model and the experiment. These results provide the first evidence of temporally stable spatial gradients of kMT catastrophe and/or rescue frequency in living cells.

Cell Movement↗