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Biomedical subjects

Margaret Werner-Washburne

Publications and source records attributed to Margaret Werner-Washburne.

13 recordsLinked to original sources
PubMed2006

Cell-directed assembly of lipid-silica nanostructures providing extended cell viability.

Amphiphilic phospholipids were used to direct the formation of biocompatible, uniform silica nanostructures in the presence of Saccharomyces cerevisiae and bacterial cell lines. The cell surfaces organize multilayered phospholipid vesicles that interface coherently with the silica host and help relieve drying stresses that develop with conventional templates. These host structures maintain cell accessibility, addressability, and viability in the absence of buffer or an external fluidic architecture. The cell surfaces are accessible and can be used to localize added proteins, plasmids, and nanocrystals. Prolonged cell viability combined with reporter protein expression enabled stand-alone cell-based sensing.

Bacillus subtilis↗
PubMed2006

Multivariate curve resolution of time course microarray data.

BACKGROUND: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), independent component analysis (ICA), or other methods. Such methods do not generally yield factors with a clear biological interpretation. Moreover, implicit assumptions about the measurement errors often limit the application of these methods to log-transformed data, destroying linear structure in the untransformed expression data. RESULTS: In this work, a method for the linear decomposition of gene expression data by multivariate curve resolution (MCR) is introduced. The MCR method is based on an alternating least-squares (ALS) algorithm implemented with a weighted least squares approach. The new method, MCR-WALS, extracts a small number of basis functions from untransformed microarray data using only non-negativity constraints. Measurement error information can be incorporated into the modeling process and missing data can be imputed. The utility of the method is demonstrated through its application to yeast cell cycle data. CONCLUSION: Profiles extracted by MCR-WALS exhibit a strong correlation with cell cycle-associated genes, but also suggest new insights into the regulation of those genes. The unique features of the MCR-WALS algorithm are its freedom from assumptions about the underlying linear model other than the non-negativity of gene expression, its ability to analyze non-log-transformed data, and its use of measurement error information to obtain a weighted model and accommodate missing measurements.

Algorithms↗
PubMed2006

Isolation of quiescent and nonquiescent cells from yeast stationary-phase cultures.

Quiescence is the most common and, arguably, most poorly understood cell cycle state. This is in part because pure populations of quiescent cells are typically difficult to isolate. We report the isolation and characterization of quiescent and nonquiescent cells from stationary-phase (SP) yeast cultures by density-gradient centrifugation. Quiescent cells are dense, unbudded daughter cells formed after glucose exhaustion. They synchronously reenter the mitotic cell cycle, suggesting that they are in a G(0) state. Nonquiescent cells are less dense, heterogeneous, and composed of replicatively older, asynchronous cells that rapidly lose the ability to reproduce. Microscopic and flow cytometric analysis revealed that nonquiescent cells accumulate more reactive oxygen species than quiescent cells, and over 21 d, about half exhibit signs of apoptosis and necrosis. The ability to isolate both quiescent and nonquiescent yeast cells from SP cultures provides a novel, tractable experimental system for studies of quiescence, chronological and replicative aging, apoptosis, and the cell cycle.

Apoptosis↗
PubMed2006

Release of extraction-resistant mRNA in stationary phase Saccharomyces cerevisiae produces a massive increase in transcript abundance in response to stress.

BACKGROUND: As carbon sources are exhausted, Saccharomyces cerevisiae cells exhibit reduced metabolic activity and cultures enter the stationary phase. We asked whether cells in stationary phase cultures respond to additional stress at the level of transcript abundance. RESULTS: Microarrays were used to quantify changes in transcript abundance in cells from stationary phase cultures in response to stress. More than 800 mRNAs increased in abundance by one minute after oxidative stress. A significant number of these mRNAs encode proteins involved in stress responses. We tested whether mRNA increases were due to new transcription, rapid poly-adenylation of message (which would not be detected by microarrays), or potential release of mature mRNA present in the cell but resistant to extraction during RNA isolation. Examination of the response to oxidative stress in an RNA polymerase II mutant, rpb1-1, suggested that new transcription was not required. Quantitative RT-PCR analysis of a subset of these transcripts further suggested that the transcripts present in isolated total RNA from stationary phase cultures were polyadenylated. In contrast, over 2,000 transcripts increased after protease treatment of cell-free lysates from stationary phase but not exponentially growing cultures. Different subsets of transcripts were released by oxidative stress and temperature upshift, suggesting that mRNA release is stress-specific. CONCLUSIONS: Cells in stationary phase cultures contain a large number of extraction-resistant mRNAs in a protease-labile, rapidly releasable form. The transcript release appears to be stress-specific. We hypothesize that these transcripts are associated with P-bodies.

Cell-Free System↗
PubMed2005

Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data.

BACKGROUND: Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. RESULTS: Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. CONCLUSION: Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring.

Algorithms↗
PubMed2004

Genomic analysis of stationary-phase and exit in Saccharomyces cerevisiae: gene expression and identification of novel essential genes.

Most cells on earth exist in a quiescent state. In yeast, quiescence is induced by carbon starvation, and exit occurs when a carbon source becomes available. To understand how cells survive in, and exit from this state, mRNA abundance was examined using oligonucleotide-based microarrays and quantitative reverse transcription-polymerase chain reaction. Cells in stationary-phase cultures exhibited a coordinated response within 5-10 min of refeeding. Levels of >1800 mRNAs increased dramatically (>or=64-fold), and a smaller group of stationary-phase mRNAs decreased in abundance. Motif analysis of sequences upstream of genes clustered by VxInsight identified an overrepresentation of Rap1p and BUF (RPA) binding sites in genes whose mRNA levels rapidly increased during exit. Examination of 95 strains carrying deletions in stationary-phase genes induced identified 32 genes essential for survival in stationary-phase at 37 degrees C. Analysis of these genes suggests that mitochondrial function is critical for entry into stationary-phase and that posttranslational modifications and protection from oxidative stress become important later. The phylogenetic conservation of stationary-phase genes, and our findings that two-thirds of the essential stationary-phase genes have human homologues and of these, many have human homologues that are disease related, demonstrate that yeast is a bona fide model system for studying the quiescent state of eukaryotic cells.

Base Sequence↗
PubMed2004

Design, construction, characterization, and application of a hyperspectral microarray scanner.

We describe the design, construction, and operation of a hyperspectral microarray scanner for functional genomic research. The hyperspectral instrument operates with spatial resolutions ranging from 3 to 30 microm and records the emission spectrum between 490 and 900 nm with a spectral resolution of 3 nm for each pixel of the microarray. This spectral information, when coupled with multivariate data analysis techniques, allows for identification and elimination of unwanted artifacts and greatly improves the accuracy of microarray experiments. Microarray results presented in this study clearly demonstrate the separation of fluorescent label emission from the spectrally overlapping emission due to the underlying glass substrate. We also demonstrate separation of the emission due to green fluorescent protein expressed by yeast cells from the spectrally overlapping autofluorescence of the yeast cells and the growth media.

Equipment Design↗
PubMed2004

"Sleeping beauty": quiescence in Saccharomyces cerevisiae.

The cells of organisms as diverse as bacteria and humans can enter stable, nonproliferating quiescent states. Quiescent cells of eukaryotic and prokaryotic microorganisms can survive for long periods without nutrients. This alternative state of cells is still poorly understood, yet much benefit is to be gained by understanding it both scientifically and with reference to human health. Here, we review our knowledge of one "model" quiescent cell population, in cultures of yeast grown to stationary phase in rich media. We outline the importance of understanding quiescence, summarize the properties of quiescent yeast cells, and clarify some definitions of the state. We propose that the processes by which a cell enters into, maintains viability in, and exits from quiescence are best viewed as an environmentally triggered cycle: the cell quiescence cycle. We synthesize what is known about the mechanisms by which yeast cells enter into quiescence, including the possible roles of the protein kinase A, TOR, protein kinase C, and Snf1p pathways. We also discuss selected mechanisms by which quiescent cells maintain viability, including metabolism, protein modification, and redox homeostasis. Finally, we outline what is known about the process by which cells exit from quiescence when nutrients again become available.

Cell Survival↗
PubMed2003

The genome sequence of the filamentous fungus Neurospora crassa.

Neurospora crassa is a central organism in the history of twentieth-century genetics, biochemistry and molecular biology. Here, we report a high-quality draft sequence of the N. crassa genome. The approximately 40-megabase genome encodes about 10,000 protein-coding genes--more than twice as many as in the fission yeast Schizosaccharomyces pombe and only about 25% fewer than in the fruitfly Drosophila melanogaster. Analysis of the gene set yields insights into unexpected aspects of Neurospora biology including the identification of genes potentially associated with red light photobiology, genes implicated in secondary metabolism, and important differences in Ca2+ signalling as compared with plants and animals. Neurospora possesses the widest array of genome defence mechanisms known for any eukaryotic organism, including a process unique to fungi called repeat-induced point mutation (RIP). Genome analysis suggests that RIP has had a profound impact on genome evolution, greatly slowing the creation of new genes through genomic duplication and resulting in a genome with an unusually low proportion of closely related genes.

Calcium Signaling↗
PubMed2003

Identification and removal of contaminating fluorescence from commercial and in-house printed DNA microarrays.

Microarray analysis is a critically important technology for genome-enabled biology, therefore it is essential that the data obtained be reliable. Current software and normalization techniques for microarray analysis rely on the assumption that fluorescent background within spots is essentially the same throughout the glass slide and can be measured by fluorescence surrounding the spots. This assumption is not valid if background fluorescence is spot-localized. Inaccurate estimates of background fluorescence under the spot create a source of error, especially for low expressed genes. We have identified spot-localized, contaminating fluorescence in the Cy3 channel on several commercial and in-house printed microarray slides. We determined through mock hybridizations (without labeled target) that pre-hybridization scans could not be used to predict the contribution of this contaminating fluorescence after hybridization because the change in spot-to-spot fluorescence after hybridization was too variable. Two solutions to this problem were identified. First, allowing 4 h of exposure to air prior to printing on to Corning UltraGAPS slides significantly reduced contaminating fluorescence intensities to approximately the value of the surrounding glass. Alternatively, application of a novel, hyperspectral imaging scanner and multivariate curve resolution algorithms, allowed the spectral contributions of Cy3 signal, glass, and contaminating fluorescence to be distinguished and quantified after hybridization.

Artifacts↗
PubMed2002

The genomics of yeast responses to environmental stress and starvation.

Unicellular organisms such as yeast have evolved to survive constant fluctuations in their external surroundings by rapidly adapting their internal systems to meet the challenges of each new environment. One aspect of this cellular adaptation is the reorganization of genomic expression to the program required for growth in each environment. The reprogramming of genomic expression can be unveiled using DNA microarrays, which measure the relative transcript abundance of essentially every gene in an organism's genome. Characterizing environmentally triggered gene expression changes provides insights into when, where, and how each gene is expressed and offers a glimpse at the physiological response of the cells to changes in their surroundings. This review will focus on the genomic expression responses of the budding yeast Saccharomyces cerevisiae to diverse environmental changes, highlighting some of the themes that have emerged from the collection of published yeast genomic expression studies. The results of these studies present insights as to how yeast cells sense and respond to each new environment, and suggest mechanisms that this organism uses to survive stressful environmental changes.

Culture Media↗
PubMed2002

Comparative analysis of multiple genome-scale data sets.

The ongoing analyses of published genome-scale data sets is evidence that different approaches are required to completely mine this data. We report the use of novel tools for both visualization and data set comparison to analyze yeast gene-expression (cell cycle and exit from stationary phase/G(0)) and protein-interaction studies. This analysis led to new insights about each data set. For example, G(1)-regulated genes are not co-regulated during exit from stationary phase, indicating that the cells are not synchronized. The tight clustering of other genes during exit from stationary-phase data set further indicates the physiological responses during G(0) exit are separable from cell-cycle events. Comparison of the two data sets showed that ribosomal-protein genes cluster tightly during exit from stationary phase, but are found in three significantly different clusters in the cell-cycle data set. Two protein-interaction data sets were also compared with the gene-expression data. Visual analysis of the complete data sets showed no clear correlation between co-expression of genes and protein interactions, in contrast to published reports examining subsets of the protein-interaction data. Neither two-hybrid study identified a large number of interactions between ribosomal proteins, consistent with recent structural data, indicating that for both data sets, the identification of false-positive interactions may be lower than previously thought.

Cell Cycle↗