A Systems Level Analysis of Transcriptional Regulation in the Yeast Mating Response

All cells must detect and respond to changes in their environment, often through changes in gene expression. The yeast pheromone pathway has been extensively characterized and is an ideal system for studying transcriptional regulation. Here we combine computational and experimental approaches to study transcriptional regulation mediated by Ste12, the key transcription factor in the pheromone response. Our mathematical model is able to explain multiple counter-intuitive experimental results and led to several novel findings. For example, we found that the transcriptional repressors Dig1 and Dig2 positively affect transcription by stabilizing Ste12 and that this allows the transcriptional response to act on a different time scale than upstream pathway activity. We further test transcriptional regulation by exposing cells to pheromone concentrations that vary periodically in time and sweeping the frequency of the signal. Such a strategy is often used in engineering to characterize electric circuits. Using this tool we found that transcription persisted for ~40min after the pheromone was off. To investigate the sources of memory, I developed an Euler solver that made use of the parallel nature of graphics processer units (GPU) to speed up model simulations by 3-4 orders of magnitude. This speedup made it possible to systematically search the parameter space of competing models of memory, fully characterizing their behavior. Using this tool we learned that the observed memory was due to both positive feedback and a slow deactivation step. We also validate our model by making specific predictions and testing them experimentally.Doctor of Philosoph

Integrating multiple knowledge bases within Google Desktop

Google is clearly the preferred solution when searching for information. However, how does one search for information within proprietary knowledge bases? We believe that we can use the power of Google Desktop (GD) as a repository and search mechanism for local proprietary knowledge. We have constructed a multi-socketed server (using C++) which allows network clients explicit control of textual input to GD. Using the ATL/COM interface, our software registers as a GD plug-in. Our server supports GD API "events", such as note, email, and instant message, and processes events at approximately 10/s. To test the effectiveness of the system, we downloaded 600,000 posts from a popular, public threaded discussion forum and 150,000 posts from a subscription-based forum. Our server partitions these knowledge sets so that they can be independently searched. We found that when compared to forum string search functions, our partitioned GD search tool produced significantly superior results.CableLabs Favorite

An improved short-lived fluorescent protein transcriptional reporter for S. cerevisiae.

Ideal reporter genes for temporal transcription programmes have short half-lives that restrict their detection to the window in which their transcripts are present and translated. In an effort to meet this criterion for reporters of transcription in individual living cells, we adapted the ubiquitin fusion strategy for programmable N-end rule degradation to generate an N-degron version of green fluorescent protein (GFP) with a half-life of ~7 min. The GFP variant we used here (designated GFP*) has excellent fluorescence brightness and maturation properties, which make the destabilized reporter well suited for tracking the induction and attenuation kinetics of gene expression in living cells. These attributes are illustrated by its ability to track galactose- and pheromone-induced transcription in S. cerevisiae. We further show that the fluorescence measurements using the short-lived N-degron GFP* reporter gene accurately predict the transient mRNA profile of the prototypical pheromone-induced FUS1 gene. Copyright © 2012 John Wiley & Sons, Ltd

Positive roles for negative regulators in the mating response of yeast

Modeling and experimental analysis of the yeast mating pathway reveals that transcriptional repressor proteins protect a key transcriptional activator from degradation, ensuring that the system is poised to respond rapidly to pheromones and providing a novel mechanism for perfect adaptation.We combine experimentation and mathematical modeling to study the complex interplay between positive and negative regulation of gene expression in the yeast pheromone pathway.The transcriptional repressors Dig1 and Dig2 are shown to have a positive role in mating differentiation by stabilizing the transcriptional activator Ste12. This result was predicted by mathematical modeling and confirmed experimentally.The model also predicts that Ste12 degradation follows saturable kinetics. Again, this observation is confirmed experimentally.The model revealed that stabilization through protein–protein interactions provides a mechanism for robust perfect adaptation and allows the transcriptional response to occur on a time scale that is distinct from upstream signaling events.All cells must detect and respond to changes in their environment, often through changes in gene expression. The yeast pheromone pathway has been extensively characterized, and is an ideal system for studying transcriptional regulation. Here we combine computational and experimental approaches to study transcriptional regulation mediated by Ste12, the key transcription factor in the pheromone response. Our mathematical model is able to explain multiple counterintuitive experimental results and led to several novel findings. First, we found that the transcriptional repressors Dig1 and Dig2 positively affect transcription by stabilizing Ste12. This stabilization through protein–protein interactions creates a large pool of Ste12 that is rapidly activated following pheromone stimulation. Second, we found that protein degradation follows saturating kinetics, explaining the long half-life of Ste12 in mutants expressing elevated amounts of Ste12. Finally, our model reveals a novel mechanism for robust perfect adaptation through protein–protein interactions that enhance complex stability. This mechanism allows the transcriptional response to act on a shorter time scale than upstream pathway activity

Cellular Noise Suppression by the Regulator of G Protein Signaling Sst2

G proteins and their associated receptors process information from a variety of environmental stimuli to induce appropriate cellular responses. Generally speaking, each cell in a population responds within defined limits despite large variation in the expression of protein signaling components. Therefore we postulated that noise suppression is encoded within the signaling system. Using the yeast mating pathway as a model we evaluated the ability of a regulator of G protein signaling (RGS) protein to suppress noise. We found that the RGS protein Sst2 limits variability in transcription and morphogenesis in response to pheromone stimulation. While signal suppression is a result of both the GAP (GTPase accelerating) and receptor binding functions of Sst2, noise suppression requires only the GAP activity. Taken together our findings reveal a hitherto overlooked role of RGS proteins as noise suppressors, and demonstrate an ability to uncouple signal and noise in a prototypical stimulus-response pathway

What happens if you single out? An experiment

We present an experiment investigating the effects of singling out an individual on trust and trustworthiness. We find that (a) trustworthiness falls if there is a singled out subject; (b) non-singled out subjects discriminate against the singled out subject when they are not responsible of the distinct status of this person; (c) under a negative frame, the singled out subject returns significantly less; (d) under a positive frame, the singled out subject behaves bimodally, either selecting very low or very high return rates. Overall, singling out induces a negligible effect on trust but is potentially disruptive for trustworthiness

Research priorities in hypertrophic cardiomyopathy: report of a Working Group of the National Heart, Lung, and Blood Institute.

Hypertrophic cardiomyopathy (HCM) is a myocardial disorder characterized by left ventricular (LV) hypertrophy without dilatation and without apparent cause (ie, it occurs in the absence of severe hypertension, aortic stenosis, or other cardiac or systemic diseases that might cause LV hypertrophy). Numerous excellent reviews and consensus documents provide a wealth of additional background.1–8 HCM is the leading cause of sudden death in young people and leads to significant disability in survivors. It is caused by mutations in genes that encode components of the sarcomere. Cardiomyocyte and cardiac hypertrophy, myocyte disarray, interstitial and replacement fibrosis, and dysplastic intramyocardial arterioles characterize the pathology of HCM. Clinical manifestations include impaired diastolic function, heart failure, tachyarrhythmia (both atrial and ventricular), and sudden death. At present, there is a lack of understanding of how the mutations in genes encoding sarcomere proteins lead to the phenotypes described above. Current therapeutic approaches have focused on the prevention of sudden death, with implantable cardioverter defibrillator placement in high-risk patients. But medical therapies have largely focused on alleviating symptoms of the disease, not on altering its natural history. The present Working Group of the National Heart, Lung, and Blood Institute brought together clinical, translational, and basic scientists with the overarching goal of identifying novel strategies to prevent the phenotypic expression of disease. Herein, we identify research initiatives that we hope will lead to novel therapeutic approaches for patients with HCM

Challenges facing early career academic cardiologists

Early career academic cardiologists currently face unprecedented challenges that threaten a highly valued career path. A team consisting of early career professionals and senior leadership members of American College of Cardiology completed this white paper to inform the cardiovascular medicine profession regarding the plight of early career cardiologists and to suggest possible solutions. This paper includes: 1) definition of categories of early career academic cardiologists; 2) general challenges to all categories and specific challenges to each category; 3) obstacles as identified by a survey of current early career members of the American College of Cardiology; 4) major reasons for the failure of physician-scientists to receive funding from National Institute of Health/National Heart Lung and Blood Institute career development grants; 5) potential solutions; and 6) a call to action with specific recommendations