Daniel Segrè

Bio: Daniel Segrè is an academic researcher from Boston University. The author has contributed to research in topics: Flux balance analysis & Metabolic network. The author has an hindex of 37, co-authored 126 publications receiving 7883 citations. Previous affiliations of Daniel Segrè include Harvard University & Weizmann Institute of Science.

Analysis of optimality in natural and perturbed metabolic networks

Abstract: An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism.

Modular epistasis in yeast metabolism.

Abstract: Epistatic interactions, manifested in the effects of mutations on the phenotypes caused by other mutations, may help uncover the functional organization of complex biological networks. Here, we studied system-level epistatic interactions by computing growth phenotypes of all single and double knockouts of 890 metabolic genes in Saccharomyces cerevisiae, using the framework of flux balance analysis. A new scale for epistasis identified a distinctive trimodal distribution of these epistatic effects, allowing gene pairs to be classified as buffering, aggravating or noninteracting. We found that the ensuing epistatic interaction network could be organized hierarchically into function-enriched modules that interact with each other 'monochromatically' (i.e., with purely aggravating or purely buffering epistatic links). This property extends the concept of epistasis from single genes to functional units and provides a new definition of biological modularity, which emphasizes interactions between, rather than within, functional modules. Our approach can be used to infer functional gene modules from purely phenotypic epistasis measurements.

Emergent simplicity in microbial community assembly.

Abstract: A major unresolved question in microbiome research is whether the complex taxonomic architectures observed in surveys of natural communities can be explained and predicted by fundamental, quantitative principles. Bridging theory and experiment is hampered by the multiplicity of ecological processes that simultaneously affect community assembly in natural ecosystems. We addressed this challenge by monitoring the assembly of hundreds of soil- and plant-derived microbiomes in well-controlled minimal synthetic media. Both the community-level function and the coarse-grained taxonomy of the resulting communities are highly predictable and governed by nutrient availability, despite substantial species variability. By generalizing classical ecological models to include widespread nonspecific cross-feeding, we show that these features are all emergent properties of the assembly of large microbial communities, explaining their ubiquity in natural microbiomes.

The lipid world.

Abstract: The continuity of abiotically formed bilayer membraneswith similar structures in contemporary cellular life,and the requirement for microenvironments in whichlarge and small molecules could be compartmentalized, support the idea that amphiphilic boundary structurescontributed to the emergence of life. As an extensionof this notion, we propose here a `Lipid World'scenario as an early evolutionary step in theemergence of cellular life on Earth. This conceptcombines the potential chemical activities of lipidsand other amphiphiles, with their capacity to undergospontaneous self-organization into supramolecularstructures such as micelles and bilayers. Inparticular, the documented chemical rate enhancementswithin lipid assemblies suggest that energy-dependentsynthetic reactions could lead to the growth andincreased abundance of certain amphiphilic assemblies.We further propose that selective processes might acton such assemblies, as suggested by our computersimulations of mutual catalysis among amphiphiles. Asdemonstrated also by other researchers, such mutualcatalysis within random molecular assemblies couldhave led to a primordial homeostatic system displayingrudimentary life-like properties. Taken together,these concepts provide a theoretical framework, andsuggest experimental tests for a Lipid World model forthe origin of life.

Diminishing returns epistasis among beneficial mutations decelerates adaptation

Abstract: Epistasis has substantial impacts on evolution, in particular, the rate of adaptation We generated combinations of beneficial mutations that arose in a lineage during rapid adaptation of a bacterium whose growth depended on a newly introduced metabolic pathway The proportional selective benefit for three of the four loci consistently decreased when they were introduced onto more fit backgrounds These three alleles all reduced morphological defects caused by expression of the foreign pathway A simple theoretical model segregating the apparent contribution of individual alleles to benefits and costs effectively predicted the interactions between them These results provide the first evidence that patterns of epistasis may differ for within- and between-gene interactions during adaptation and that diminishing returns epistasis contributes to the consistent observation of decelerating fitness gains during adaptation

Initial sequencing and analysis of the human genome.

Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Network biology: understanding the cell's functional organization

Abstract: A key aim of postgenomic biomedical research is to systematically catalogue all molecules and their interactions within a living cell. There is a clear need to understand how these molecules and the interactions between them determine the function of this enormously complex machinery, both in isolation and when surrounded by other cells. Rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize our view of biology and disease pathologies in the twenty-first century.

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