PubMed Health⌕ Search

Biomedical subjects

Gregory Stephanopoulos

Publications and source records attributed to Gregory Stephanopoulos.

8 recordsLinked to original sources
PubMed2002

Optimizing bioconversion pathways through systems analysis and metabolic engineering.

We demonstrate a general approach for metabolic engineering of biocatalytic systems comprising the uses of a chemostat for strain improvement and radioisotopic tracers for the quantification of pathway fluxes. Flux determination allows the identification of target pathways for modification as validated by subsequent overexpression of the corresponding gene. We demonstrate this method in the indene bioconversion network of Rhodococcus modified for the overproduction of 1,2-indandiol, a key precursor for the AIDS drug Crixivan.

Biomedical Engineering↗
PubMed2002

Mapping physiological states from microarray expression measurements.

MOTIVATION: The increasing use of DNA microarrays to probe cell physiology requires methods for visualizing different expression phenotypes and explicitly connecting individual genes to discriminating expression features. Such methods should be robust and maintain biological interpretability. RESULTS: We propose a method for the mapping of the physiological state of cells and tissues from multidimensional expression data such as those obtained with DNA microarrays. The method uses Fisher discriminant analysis to create a linear projection of gene expression measurements that maximizes the separation of different sample classes. Relative to other typical classification methods, this method provides insights into the discriminating characteristics of expression measurements in terms of the contribution of individual genes to the definition of distinct physiological states. This projection method also facilitates visualization of classification results in a reduced dimensional space. Examples from four different cases demonstrate the ability of the method to produce well-separated groups in the projection space and to identify important genes for defining physiological states. The method can be augmented to also include data from the proteomic and metabolic phenotypes and can be useful in disease diagnosis, drug screening and bioprocessing applications.

Algorithms↗
PubMed2002

Determination of minimum sample size and discriminatory expression patterns in microarray data.

MOTIVATION: Transcriptional profiling using microarrays can reveal important information about cellular and tissue expression phenotypes, but these measurements are costly and time consuming. Additionally, tissue sample availability poses further constraints on the number of arrays that can be analyzed in connection with a particular disease or state of interest. It is therefore important to provide a method for the determination of the minimum number of microarrays required to separate, with statistical reliability, distinct disease states or other physiological differences. RESULTS: Power analysis was applied to estimate the minimum sample size required for two-class and multi-class discrimination. The power analysis algorithm calculates the appropriate sample size for discrimination of phenotypic subtypes in a reduced dimensional space obtained by Fisher discriminant analysis (FDA). This approach was tested by applying the algorithm to existing data sets for estimation of the minimum sample size required for drawing certain conclusions on multi-class distinction with statistical reliability. It was confirmed that when the minimum number of samples estimated from power analysis is used, group means in the FDA discrimination space are statistically different. CONTACT: gregstep@mit.edu

Acute Disease↗
PubMed2002

Interactive exploration of microarray gene expression patterns in a reduced dimensional space.

The very high dimensional space of gene expression measurements obtained by DNA microarrays impedes the detection of underlying patterns in gene expression data and the identification of discriminatory genes. In this paper we show the use of projection methods such as principal components analysis (PCA) to obtain a direct link between patterns in the genes and patterns in samples. This feature is useful in the initial interactive pattern exploration of gene expression data and data-driven learning of the nature and types of samples. Using oligonucleotide microarray measurements of 40 samples from different normal human tissues, we show that distinct patterns are obtained when the genes are projected on a two-dimensional plane spanned by the loadings of the two major principal components. These patterns define the particular genes associated with a sample class (i.e., tissue). When used separately from the other genes, these class-specific (i.e., tissue-specific) genes in turn define distinct tissue patterns in the projection space spanned by the scores of the two major principal components. In this study, PCA projection facilitated discriminatory gene selection for different tissues and identified tissue-specific gene expression signatures for liver, skeletal muscle, and brain samples. Furthermore, it allowed the classification of nine new samples belonging to these three types using the linear combination of the expression levels of the tissue-specific genes determined from the first set of samples. The application of the technique to other published data sets is also discussed.

Gene Expression Profiling↗
PubMed2002

Effect of pyruvate carboxylase overexpression on the physiology of Corynebacterium glutamicum.

Pyruvate carboxylase was recently sequenced in Corynebacterium glutamicum and shown to play an important role of anaplerosis in the central carbon metabolism and amino acid synthesis of these bacteria. In this study we investigate the effect of the overexpression of the gene for pyruvate carboxylase (pyc) on the physiology of C. glutamicum ATCC 21253 and ATCC 21799 grown on defined media with two different carbon sources, glucose and lactate. In general, the physiological effects of pyc overexpression in Corynebacteria depend on the genetic background of the particular strain studied and are determined to a large extent by the interplay between pyruvate carboxylase and aspartate kinase activities. If the pyruvate carboxylase activity is not properly matched by the aspartate kinase activity, pyc overexpression results in growth enhancement instead of greater lysine production, despite its central role in anaplerosis and aspartic acid biosynthesis. Aspartate kinase regulation by lysine and threonine, pyruvate carboxylase inhibition by aspartate (shown in this study using permeabilized cells), as well as well-established activation of pyruvate carboxylase by lactate and acetyl coenzyme A are the key factors in determining the effect of pyc overexpression on Corynebacteria physiology.

Aspartic Acid↗
PubMed2002

Genome-wide dynamic transcriptional profiling of the light-to-dark transition in Synechocystis sp. strain PCC 6803.

We report the results of whole-genome transcriptional profiling of the light-to-dark transition with the model photosynthetic prokaryote Synechocystis sp. strain PCC 6803 (Synechocystis). Experiments were conducted by growing Synechocystis cultures to mid-exponential phase and then exposing them to two cycles of light/dark conditions, during which RNA samples were obtained. These samples were probed with a full-genome DNA microarray (3,169 genes, 20 samples) as well as a partial-genome microarray (88 genes, 29 samples). We concluded that (i) 30-min sampling intervals accurately captured transcriptional dynamics throughout the light/dark transition, (ii) 25% of the Synechocystis genes (783 genes) responded positively to the presence of light, and (iii) the response dynamics varied greatly for individual genes, with a delay of up to 120 to 150 min for some genes. Four classes of genes were identified on the basis of their dynamic gene expression profiles: class I (108 genes, 30-min response time), class II (279 genes, 60 to 90 min), class III (258 genes, 120 to 150 min), and class IV (138 genes, 180 min). The dynamics of several transcripts from genes involved in photosynthesis and primary energy generation are discussed. Finally, we applied Fisher discriminant analysis to better visualize the progression of the overall transcriptional program throughout the light/dark transition and to determine those genes most indicative of the lighting conditions during growth.

Cyanobacteria↗
PubMedDate not supplied

Mitochondrial membrane potential selects hybridomas yielding high viability in fed-batch cultures.

Prior research (Follstad, B. D.; Wang, D. I. C.; Stephanopoulos, G. Mitochondrial membrane potential differentiates cells resistant to apoptosis in hybridoma cultures. Eur. J. Biochem. 2000, 267, 6534-6540.) identified mitochondrial membrane potential (MMP) as a marker of hybridoma subpopulations resistant to apoptosis caused by a variety of apoptosis inducers. In this study, we investigated the viability of hybridoma cell cultures inoculated with cells of varying MMP in regular fed-batch operation. A hybridoma cell population was separated using FACS into subpopulations based on their mean mitochondrial membrane potential (MMP) as measured using the common mitochondrial stain, Rhodamine 123 (Rh123). These subpopulations showed dramatic differences in their apoptotic death kinetics. Fed-batches inoculated with a high MMP subpopulation reached higher viable cell concentrations and viabilities that were maintained for prolonged periods of time relative to fed-batches inoculated with low MMP subpopulations. These results underline the heterogeneous nature of hybridoma cell cultures and suggest that mitochondrial physiology is a critical parameter determining culture performance.

Animals↗