bluuebunny/crossref_metadata_2025_split huggingface dataset:
Independent de novo 22q11.2 deletions in first cousins with DiGeorge/velocardiofacial syndrome
Authors: Saitta Sulagna C. , Harris Stacy E. , McDonald‐McGinn Donna M. , Emanuel Beverly S. , Tonnesen Melissa K. , Zackai Elaine H. , Seitz Suzanne C. , Driscoll Deborah A. 
Published: January 2004

AbstractDeletions of chromosome 22q11.2 are found in the vast majority of patients with DiGeorge/velocardiofacial syndrome (DGS/VCFS). This most frequent microdeletion syndrome is estimated to occur in 1 in 4,000 live births. The majority of deletions are de novo, with 10% or less inherited from an affected parent. Here, we report two separate families with recurrence of a 22q11.2 deletion in first cousins. In each family, unaffected siblings (brother and sister) had an affected child. Fluorescence in situ hybridization (FISH) studies of the parents of each affected child were normal and hence, relatives were not considered at an increased risk for recurrence in another pregnancy. We used highly polymorphic microsatellite repeat markers from within 22q11.2 to determine the parental origin of each cousin's deletion and to assess whether parental germline mosaicism for the 22q11.2 deletion might be a factor in these cases. This analysis confirmed that in each case, the deletion occurred on a chromosome 22 derived from unrelated parents, consistent with independent de novo deletion events. Thus, we concluded that germline mosaicism as the underlying mechanism for affected cousins in these families was unlikely. Our findings underscore the high frequency with which the 22q11.2 deletion occurs in the general population and demonstrate the important role that PCR‐based parental origin determination can have in recurrence risk counselling. Furthermore, relatives of affected individuals may benefit from genetic counselling and consider prenatal testing for the 22q11.2 deletion in future pregnancies, despite a low recurrence risk. © 2003 Wiley‐Liss, Inc.
Mosaic paternal uniparental (iso)disomy for chromosome 20 associated with multiple anomalies
Authors: Venditti Charles P. , Hunt Piper , Donnenfeld Alan , Zackai Elaine , Spinner Nancy B. 
Published: January 2004

AbstractUniparental disomy for a number of human chromosomes is associated with clinical abnormalities. We report a child with a complex chromosomal rearrangement involving chromosome 20 (45,XY,psu dic (20;20)(p13;p13)) and paternal uniparental isodisomy for chromosome 20 in peripheral blood and bone marrow. This patient had multiple congenital abnormalities including microtia/anotia, micrencephaly, congenital heart disease, neuronal subependymal heterotopias, and colonic agangliosis. Molecular studies on DNA from peripheral blood demonstrated paternal uniparental inheritance of chromosome 20. However, fibroblasts demonstrated a mosaic karyotype, with one cell line having 45 chromosomes, including the pseudodicentric chromosome 20 (75% of cells), and a second cell line having 46 chromosomes, including the pseudodicentric chromosome 20, and a normal chromosome 20 (trisomy 20) (25% of cells). FISH experiments using a sub‐telomeric probe that maps ∼120 kb from the 20p telomere, showed that both copies of these sequences were present on the rearranged chromosome, consistent with deletion of a very small interval. This leads us to suggest that in addition to trisomy 20 mosaicism, paternal uniparental disomy for chromosome 20 could contribute to his clinical phenotype. © 2003 Wiley‐Liss, Inc.
Insights into the relation between mrna and protein expression patterns: ii. Experimental observations in Escherichia coli1
Authors: Lee Pat S. , Shaw Leah B. , Choe Leila H. , Mehra Amit , Hatzimanikatis Vassily , Lee Kelvin H. 
Published: January 2004

AbstractThere is a need for improved appreciation of the importance of genome‐wide mRNA and protein expression measurements and their role in understanding translation and in relation to genome‐wide mathematical frameworks for gene expression regulation. We investigated the use of a high‐density microarray technique for mRNA expression analysis and a two‐dimensional protein electrophoresis–tandem mass spectrometry method for protein analysis to monitor changes in gene expression. We applied these analytical tools in the context of an environmental perturbation of Escherichia coli cells—the addition of varying amounts of IPTG. We also tested the application of these tools to the study of a genetic perturbation of Escherichia coli cells—the ability of certain strains to hypersecrete the hemolysin protein. We observed a lack of correspondence between mRNA and protein expression profiles. Although our data do not include measurements on all expressed genes (because the ability to measure protein expression profiles is limiting), we observed that the qualitative and quantitative behavior of the measurements of a subset of expressed genes is similar to the behavior of the entire system. The change in observed average mRNA and protein amplification factors for 77 and 52 genes coincided with the observed change in mRNA amplification factor for the entire system. Furthermore, we found that the use of relative changes in expression could be used to elucidate mechanisms of gene expression regulation for the system studied, even when measurements were made on a small subset of the system. © 2003 Wiley Periodicals, Inc.
The complexity of complexes in signal transduction
Authors: Hlavacek William S. , Faeder James R. , Blinov Michael L. , Perelson Alan S. , Goldstein Byron 
Published: January 2004

AbstractMany activities of cells are controlled by cell‐surface receptors, which in response to ligands, trigger intracellular signaling reactions that elicit cellular responses. A hallmark of these signaling reactions is the reversible nucleation of multicomponent complexes, which typically begin to assemble when ligand‐receptor binding allows an enzyme, often a kinase, to create docking sites for signaling molecules through chemical modifications, such as tyrosine phosphorylation. One function of such docking sites is the co‐localization of enzymes with their substrates, which can enhance both enzyme activity and specificity. The directed assembly of complexes can also influence the sensitivity of cellular responses to ligand‐receptor binding kinetics and determine whether a cellular response is up‐ or downregulated in response to a ligand stimulus. The full functional implications of ligand‐stimulated complex formation are difficult to discern intuitively. Complex formation is governed by conditional interactions among multivalent signaling molecules and influenced by quantitative properties of both the components in a system and the system itself. Even a simple list of the complexes that can potentially form in response to a ligand stimulus is problematic because of the number of ways signaling molecules can be modified and combined. Here, we review the role of multicomponent complexes in signal transduction and advocate the use of mathematical models that incorporate detail at the level of molecular domains to study this important aspect of cellular signaling. © 2003 Wiley Periodicals, Inc.
Prediction of transcriptional profiles of Synechocystis PCC6803 by dynamic autoregressive modeling of DNA microarray data
Authors: Schmitt William A. , Stephanopoulos Gregory 
Published: January 2004

AbstractTime‐series profiles of gene expression generated by DNA microarrays possess sufficient information for building dynamic models of transcriptional behavior. This, however, requires properly designed experiments and sufficient independent data to validate such models. Here we report the use of AutoRegressive with eXogenous input (ARX) models to fit dynamic gene expression data obtained by subjecting cultures of the photosynthetic bacterium Synechocystis PCC6803 to consecutive light‐to‐dark transitions. Autoregressive with exogenous input models of appropriate complexity were selected by applying Akaike's information criterion (AIC) such as to maximize agreement between model predictions with experimental data without overfitting. These models were subsequently used to design the experimental profile of an optimal validating data set. Predictions from these models were tested in a second experiment and were found to match well with the validation data. Additionally, the models with the least error in predicting the expression profiles of the validation data set exactly match the model complexity predicted by AIC. Such models offer insights into cellular responses to environmental conditions and form the basis for hypothesizing and quantifying relationships that are presently poorly understood at the level of fundamental mechanisms. © 2003 Wiley Periodicals, Inc.
Theoretical and computational studies of the glucose signaling pathways in yeast using global gene expression data
Authors: Lin Xiaoxia , Floudas Christodoulos A. , Wang Ying , Broach James R. 
Published: January 2004

AbstractWe have combined DNA microarray experiments with novel computational methods as a means of defining the topology of a biological signal transduction pathway. By DNA microarray techniques, we previously acquired data on expression over time of all genes in the yeast Saccharomyces following addition of glucose to wild‐type cells and to cells mutated in one or more components of the Ras signaling network. In addition, we examined the time course of expression following activation of components of the Ras signaling network in the absence of glucose addition. In this current study, we have applied a novel theoretical and computational framework to these data to identify the network topology of the glucose signaling pathway in yeast and the role of Ras components in that network. The computational approach involves clustering genes by expression pattern, postulating a signaling network topology superstructure that includes all possible component interconnections and then evaluating the feasibility of the superstructure interconnections by optimization methods using Mixed Integer Linear Programming techniques. This approach is the first rigorous mathematical framework for addressing the biological network topology issue, and the novel formulation features the introduction of discrete variables for the connectivity and logical expressions that connect the experimental observations to the network structure. This analysis yields a topology for the glucose signaling pathway that is consistent with, and an extension of, known biological interactions in glucose signaling. © 2003 Wiley Periodicals, Inc.
A perspective of metabolic engineering strategies: moving up the systems hierarchy
Authors: Bulter Thomas , Bernstein Jeffrey R. , Liao James C. 
Published: January 2004

AbstractMetabolic engineering has been established as an important field in biotechnology. It involves the analysis, design, and alteration of the stoichiometric network using sophisticated mathematical and molecular biology techniques. It allows for improvement of pathway kinetics by removing flux bottlenecks, balancing precursors, and recycling cofactors used to increase product formation. The next step in the systems hierarchy is the constructive manipulation of regulatory networks. As our understanding of regulation continues to expand rapidly, engineering of intracellular regulation will become an integral aspect of metabolic engineering. © 2003 Wiley Periodicals, Inc.
Environmental conditions and transcriptional regulation in Escherichia coli: a physiological integrative approach
Authors: Martínez‐Antonio Agustino , Salgado Heladia , Gama‐Castro Socorro , Gutiérrez‐Ríos Rosa María , Jiménez‐Jacinto Verónica , Collado‐Vides Julio 
Published: January 2004

AbstractBacteria develop a number of devices for sensing, responding, and adapting to different environmental conditions. Understanding within a genomic perspective how the transcriptional machinery of bacteria is modulated, as a response for changing conditions, is a major challenge for biologists. Knowledge of which genes are turned on or turned off under specific conditions is essential for our understanding of cell behavior. In this study we describe how the information pertaining to gene expression and associated growth conditions (even with very little knowledge of the associated regulatory mechanisms) is gathered from the literature and incorporated into RegulonDB, a database on transcriptional regulation and operon organization in E. coli. The link between growth conditions, signal transduction, and transcriptional regulation is modeled in the database in a simple format that highlights biological relevant information. As far as we know, there is no other database that explicitly clarifies the effect of environmental conditions on gene transcription. We discuss how this knowledge constitutes a benchmark that will impact future research aimed at integration of regulatory responses in the cell; for instance, analysis of microarrays, predicting culture behavior in biotechnological processes, and comprehension of dynamics of regulatory networks. This integrated knowledge will contribute to the future goal of modeling the behavior of E. coli as an entire cell. The RegulonDB database can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/regulondb/. © 2003 Wiley Periodicals, Inc.
Maintaining data integrity in microarray data management
Authors: Grant G. R. , Manduchi E. , Pizarro A. , Stoeckert C. J. 
Published: January 2004

AbstractGene expression microarrays are a relatively new technology, dating back just a few years, yet they have already become a very widely used tool in biology, and have evolved to a wide range of applications well beyond their original design intent. However, while the use of microarrays has expanded, and the issues of performance optimization have been intensively studied, the fundamental issue of data integrity management has largely been ignored. Now that performance has improved so greatly, the shortcomings of data integrity control methods constitute a greater percent of the stumbling blocks for investigators. Microarray data are cumbersome, and the rule up to this point has mostly been one of hands‐on transformations, leading to human errors which often have dramatic consequences. We show in this review that the time lost on such mistakes is enormous and dramatically affects results; therefore, mistakes should be mitigated in any way possible. We outline the scope of the data integrity issue, to survey some of the most common and dangerous data transformations, and their shortcomings. To illustrate, we review some case studies. We then look at the work done by the research community on this issue (which admittedly is meager up to this point). Some data integrity issues are always going to be difficult, while others will become easier—one of our goals is to expedite the use of integrity control methods. Finally, we present some preliminary guidelines and some specific approaches that we believe should be the focus of future research. © 2003 Wiley Periodicals, Inc.
Escherichia coli—a model system that benefits from and contributes to the evolution of proteomics
Authors: Lee Pat S. , Lee Kelvin H. 
Published: January 2004

AbstractThe large body of knowledge about Escherichia coli makes it a useful model organism for the expression of heterologous proteins. Proteomic studies have helped to elucidate the complex cellular responses of E. coli and facilitated its use in a variety of biotechnology applications. Knowledge of basic cellular processes provides the means for better control of heterologous protein expression. Beyond such important applications, E. coli is an ideal organism for testing new analytical technologies because of the extensive knowledge base available about the organism. For example, improved technology for characterization of unknown proteins using mass spectrometry has made two‐dimensional electrophoresis (2DE) studies more useful and more rewarding, and much of the initial testing of novel protocols is based on well‐studied samples derived from E. coli. These techniques have facilitated the construction of more accurate 2DE maps. In this review, we present work that led to the 2DE databases, including a new map based on tandem time‐of‐flight (TOF) mass spectrometry (MS); describe cellular responses relevant to biotechnology applications; and discuss some emerging proteomic techniques. © 2003 Wiley Periodicals, Inc.
Identifying constraints that govern cell behavior: a key to converting conceptual to computational models in biology?
Authors: Covert Markus W. , Famili Iman , Palsson Bernhard O. 
Published: January 2004

AbstractCells must abide by a number of constraints. The environmental constrains of cellular behavior and physicochemical limitations affect cellular processes. To regulate and adapt their functions, cells impose constraints on themselves. Enumerating, understanding, and applying these constraints leads to a constraints‐based modeling formalism that has been helpful in converting conceptual models to computational models in biology. The continued success of the constraints‐based approach depends upon identification and incorporation of new constraints to more accurately define cellular capabilities. This review considers constraints in terms of environmental, physicochemical, and self‐imposed regulatory and evolutionary constraints with the purpose of refining current constraints‐based models of cell phenotype. © 2003 Wiley Periodicals, Inc.
Exploiting evolutionary relationships for predicting protein structures
Authors: Tramontano Anna , Morea Veronica 
Published: January 2004

AbstractIn the last few years there have been many developments in computational biology, particularly with regard to novel, imaginative exploitation of genomic data. Disappointingly, there has been a lack of progress in the methodology for prediction of protein structures. In the last several years, however, promising new methods have finally begun to emerge. These methods are increasing the power and scope of the methodology, but, most importantly, they are generating new areas of investigation that we believe will accelerate progress in the field. In this review we describe recent developments and highlight the implications of their success as well as areas where efforts should be focused. © 2003 Wiley Periodicals, Inc.
Transcriptional analysis of product‐concentration driven changes in cellular programs of recombinant Clostridium acetobutylicumstrains
Authors: Tummala Seshu B. , Junne Stefan G. , Paredes Carlos J. , Papoutsakis Eleftherios T. 
Published: January 2004

AbstractAntisense RNA (asRNA) downregulation alters protein expression without changing the regulation of gene expression. Downregulation of primary metabolic enzymes possibly combined with overexpression of other metabolic enzymes may result in profound changes in product formation, and this may alter the large‐scale transcriptional program of the cells. DNA‐array based large‐scale transcriptional analysis has the potential to elucidate factors that control cellular fluxes even in the absence of proteome data. These themes are explored in the study of large‐scale transcriptional analysis programs and the in vivo primary‐metabolism fluxes of several related recombinant C. acetobutylicum strains: C. acetobutylicum ATCC 824(pSOS95del) (plasmid control; produces high levels of butanol snd acetone), 824(pCTFB1AS) (expresses antisense RNA against CoA transferase (ctfb1‐asRNA); produces very low levels of butanol and acetone), and 824(pAADB1) (expresses ctfb1‐asRNA and the alcohol‐aldehyde dahydrogenase gene (aad); produce high alcohol and low acetone levels). DNA‐array based transcriptional analysis revealed that the large changes in product concentrations (snd notably butanol concentration) due to ctfb1‐asRNA expression alone and in combination with aad overexpression resulted in dramatic changes of the cellular transcriptome. Cluster analysis and gene expression patterns of established and putative operons involved in stress response, motility, sporulation, and fatty‐acid biosynthesis indicate that these simple genetic changes dramatically alter the cellular programs of C. acetobutylicum. Comparison of gene expression and flux analysis data may point to possible flux‐controling steps and suggest unknown regulatory mechanisms. © 2003; Wiley Periodicals, Inc.
Dynamical and integrative cell signaling: challenges for the new biology
Authors: Levchenko Andre 
Published: January 2004

AbstractYears of careful experimental analysis have revealed that signaling molecules are organized into complex networks of biochemical reactions exquisitely regulated in time and space to provide a cell with high‐fidelity information about an extremely noisy and volatile environment. A new view of signaling networks as systems consisting of multiple complex elements interacting in a multifarious fashion is emerging, a view that conflicts with the single‐gene or protein‐centric approach common in biological research. The postgenomic era has brought about a different, network‐centric methodology of analysis, suddenly forcing researchers toward the opposite extreme of complexity, where the networks being explored are, to a certain extent, intractable and uninterpretable. Both the cartoons of simple pathways and the very large “hair‐ball” diagrams of large intracellular networks are also representations of static worlds, superficially devoid of dynamics and chemistry. These representations are often viewed as being analogous to stably linked computer and neural networks rather than dynamically changing networks of chemical interactions, where the notions of concentration, compartmentalization, and diffusion may be the primary determinants of connectivity. Arguably, the systems biology approach, relying on computational modeling coupled with various experimental techniques and methodologies, will be an essential component of analysis of the behavior of signal transduction pathways. Combining the dynamical view of rapidly evolving responses and the structural view arising from high‐throughput analyses of the interacting species will be the best approach toward efforts toward greater understanding of intracellular signaling processes. © 2003 Wiley Periodicals, Inc.
Exploring the overproduction of amino acids using the bilevel optimization framework OptKnock
Authors: Pharkya Priti , Burgard Anthony P. , Maranas Costas D. 
Published: January 2004

AbstractIn this study, we modify and extend the bilevel optimization framework OptKnock for identifying gene knockout strategies in the Escherichia coli metabolic network, leading to the overproduction of representative amino acids and key precursors for all five families. These strategies span not only the central metabolic network genes but also the amino acid biosynthetic and degradation pathways. In addition to gene deletions, the transport rates of carbon dioxide, ammonia, and oxygen, as well as the secretion pathways for key metabolites, are introduced as optimization variables in the framework. Computational results demonstrate the importance of manipulating energy‐producing/consuming pathways, controlling the uptake of nitrogen and oxygen, and blocking the secretion pathways of key competing metabolites. The identified pathway modifications include not only straightforward elimination of competing reactions but also a number of nonintuitive knockouts quite distant from the amino acid‐producing pathways. Specifically, OptKnock suggests three reactions (i.e., pyruvate kinase, phosphotransacetylase, and ATPase) for deletion, in addition to the straightforward elimination of 2‐ketoglutarate dehydrogenase, to generate a glutamate‐overproducing mutant. Similarly, phosphofructokinase and ATPase are identified as promising knockout targets to complement the removal of pyruvate formate lyase and pyruvate dehydrogenase for enhancing the yield of alanine. Although OptKnock in its present form does not consider regulatory constraints, it does provide useful suggestions largely in agreement with existing practices and, more importantly, introduces a framework for incorporating additional modeling refinements as they become available. © 2003 Wiley Periodicals, Inc.