Browsing by Author "Sha, Wei"
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- Experimental evidnece for hysteresis in the cell cycles of Xenopus Laevis egg extractsSha, Wei (Virginia Tech, 2002-08-05)In 1993, Novak and Tyson published a comprehensive mathematical model of the regulation of M-phase promoting factor (MPF) activity in Xenopus laevis eggs and egg extracts. Although this model was in agreement with existing and subsequent experimental data, fundamental predictions that the cell cycle is driven by a hysteresis loop have never been validated experimentally. The model's predictions of bifurcations that create and destroy MPF activity, indicative of hysteresis, were tested in this study. Prediction 1: The threshold concentration of cyclin B required to activate MPF is measurably higher than the threshold concentration required to inactivate MPF. The difference in thresholds implies that the MPF control system is hysteretic and bistable. To measure these thresholds, extracts in interphase or M-phase were supplemented with varying concentrations of non-degradable human cyclin B1 protein. MPF activity was determined by the morphology of sperm nuclei and by assays of histone H1 kinase activity. Consistent with the model, the activation threshold was determined to be 40 nM, which is two-fold higher than the inactivation threshold, 20 nM. Prediction 2: For cyclin levels marginally above the activation threshold concentration of cyclin B, there is a dramatic "slowing-down" in the rate of MPF activation. Supra-threshold concentrations of nondegradable cyclin B1 were added to cycloheximide-treated CSF-released extracts, and samples taken at various time-points were analyzed for MPF activity. At 40 nM cyclin B1, just above the activation threshold, the lag time for MPF activation was 45 - 60 minutes; at 50 nM cyclin B1, the lag time was between 30 - 45 minutes; and at 60 nM or higher concentrations of cyclin B1, the lag time was 20 - 30 minutes, thus confirming the prediction of the Novak-Tyson model. Prediction 3: DNA replication checkpoint increases the activation threshold concentration of cyclin B by increasing the hysteresis loop. Cycloheximide-treated, CSF-released extracts containing 1200 sperm nuclei/μl were treated with aphidicolin, then supplemented with varying concentrations of nondegradable cyclin B1. The activation threshold was 100 nM, 2.5 fold higher than in extracts lacking aphidicolin. Conclusions: These studies confirm three predictions of the Novak-Tyson model and indicate that hysteresis underlies cell cycle control in Xenopus egg extracts. These experiments validate use of mathematical models to study complex biological control systems such as the eukayotic cell cycle.
- The Genome-Wide Early Temporal Response of Saccharomyces cerevisiae to Oxidative Stress Induced by Cumene HydroperoxideSha, Wei; Martins, Ana M.; Laubenbacher, Reinhard C.; Mendes, Pedro; Shulaev, Vladimir (PLOS, 2013-09-20)Oxidative stress is a well-known biological process that occurs in all respiring cells and is involved in pathophysiological processes such as aging and apoptosis. Oxidative stress agents include peroxides such as hydrogen peroxide, cumene hydroperoxide, and linoleic acid hydroperoxide, the thiol oxidant diamide, and menadione, a generator of superoxide, amongst others. The present study analyzed the early temporal genome-wide transcriptional response of Saccharomyces cerevisiae to oxidative stress induced by the aromatic peroxide cumene hydroperoxide. The accurate dataset obtained, supported by the use of temporal controls, biological replicates and well controlled growth conditions, provided a detailed picture of the early dynamics of the process. We identified a set of genes previously not implicated in the oxidative stress response, including several transcriptional regulators showing a fast transient response, suggesting a coordinated process in the transcriptional reprogramming. We discuss the role of the glutathione, thioredoxin and reactive oxygen species-removing systems, the proteasome and the pentose phosphate pathway. A data-driven clustering of the expression patterns identified one specific cluster that mostly consisted of genes known to be regulated by the Yap1p and Skn7p transcription factors, emphasizing their mediator role in the transcriptional response to oxidants. Comparison of our results with data reported for hydrogen peroxide identified 664 genes that specifically respond to cumene hydroperoxide, suggesting distinct transcriptional responses to these two peroxides. Genes up-regulated only by cumene hydroperoxide are mainly related to the cell membrane and cell wall, and proteolysis process, while those down-regulated only by this aromatic peroxide are involved in mitochondrial function.
- Microarray data analysis methods and their applications to gene expression data analysis for Saccharomyces cerevisiae under oxidative stressSha, Wei (Virginia Tech, 2006-05-12)Oxidative stress is a harmful condition in a cell, tissue, or organ, caused by an imbalance between reactive oxygen species or other oxidants and the capacity of antioxidant defense systems to remove them. These oxidants cause wide-ranging damage to macromolecules, including proteins, lipids, DNA and carbohydrates. Oxidative stress is an important pathophysiologic component of a number of diseases, such as Alzheimer's disease, diabetes and certain cancers. Cells contain effective defense mechanisms to respond to oxidative stress. Despite much accumulated knowledge about these responses, their kinetics, especially the kinetics of early responses is still not clearly understood. The Yap1 transcription factor is crucial for the normal response to a variety of stress conditions including oxidative stress. Previous studies on Yap1 regulation started to measure gene expression profile at least 20 minutes after the induction of oxidative stress. Genes and pathways regulated by Yap1 in early oxidative stress response (within 20 minutes) were not identified in these studies. Here we study the kinetics of early oxidative stress response induced by the cumene hydroperoxide (CHP) in Saccharomyces cerevisiae wild type and yap1 mutant. Gene expression profiles after exposure to CHP were obtained in controlled conditions using Affymetrix Yeast Genome S98 arrays. The oxidative stress response was measured at 8 time points along 120 minutes after the addition of CHP, with the earliest time point at 3 minute after the exposure. Statistical analysis methods, including ANOVA, k-means clustering analysis, and pathway analysis were used to analyze the data. The results from this study provide a dynamic resolution of the oxidative stress responses in S. cerevisiae, and contribute to a richer understanding of the antioxidant defense systems. It also provides a global view of the roles that Yap1 plays under normal and oxidative stress conditions.
- The statistics of identifying differentially expressed genes in Expresso and TM4: a comparisonSioson, Allan A.; Mane, Shrinivasrao P.; Li, Pinghua; Sha, Wei; Heath, Lenwood S.; Bohnert, Hans J.; Grene, Ruth (2006-04-20)Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity.