Genome‐scale gene/reaction essentiality and synthetic lethality analysis

Suthers, Patrick F.; Zomorrodi, Alireza; Maranas, Costas D.

doi:10.1038/msb.2009.56

Cited by 150 publications

(164 citation statements)

References 73 publications

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“…As conjugation occurs in other bacteria, it is expected that it will be applied to other organisms (123). Metabolic modeling has already been performed to predict synthetic lethal genes for E. coli on a genome scale, not only for pairs of genes but also for triplets, some quadruplets, and higher-order lethal combinations (124).…”

Section: Top-down Approachmentioning

confidence: 99%

Systems Biology Perspectives on Minimal and Simpler Cells

Xavier

Patil

Rocha

2014

Microbiol Mol Biol Rev

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SUMMARY The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells.

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Section: Top-down Approachmentioning

confidence: 99%

Systems Biology Perspectives on Minimal and Simpler Cells

Xavier

Patil

Rocha

2014

Microbiol Mol Biol Rev

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“…This is in contrast to brute-force optimization and bilevel optimization approaches, which have shown efficacy in deriving complete MCS collections for a given cardinality but have only been applied to yield low-order buffering interactions ͑i.e., k Յ 5͒. 20 The completeness of our results is limited by the ability of the pathway fragment collection to connect specific objectives to sets of reactions that provide their flux. Algorithmic improvements that yield a more complete collection of MCSs may be useful in perturbational experiment design or statistical analysis of genetic variation.…”

Section: Computational Directionsmentioning

confidence: 99%

“…The role of genes and enzymes in such robust functions can only be revealed through the knockout of multiple genes or reactions. [16][17][18][19][20][21] We refer to a set of reactions whose knockout abolishes a given function as a cut set for that function. A cut set is minimal for a given function if its knockout abolishes that function, while the knockout of none of its subsets abolishes that function.…”

Section: Introductionmentioning

confidence: 99%

Deep epistasis in human metabolism

Imieliński

Belta

2010

Chaos

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We extend and apply a method that we have developed for deriving high-order epistatic relationships in large biochemical networks to a published genome-scale model of human metabolism. In our analysis we compute 33 328 reaction sets whose knockout synergistically disables one or more of 43 important metabolic functions. We also design minimal knockouts that remove flux through fumarase, an enzyme that has previously been shown to play an important role in human cancer. Most of these knockout sets employ more than eight mutually buffering reactions, spanning multiple cellular compartments and metabolic subsystems. These reaction sets suggest that human metabolic pathways possess a striking degree of parallelism, inducing "deep" epistasis between diversely annotated genes. Our results prompt specific chemical and genetic perturbation follow-up experiments that could be used to query in vivo pathway redundancy. They also suggest directions for future statistical studies of epistasis in genetic variation data sets. © 2010 American Institute of Physics. ͓doi:10.1063/1.3456056͔Small molecule metabolism mediates the most basic biochemical function of living matter: to derive energy and macromolecules from nutrients in the environment. Metabolic pathways are tied in intricate networks which in E. coli and S. cereviseae have been shown to display a great degree of buffering and epistasis. Epistasis has not been previously been examined on a genome-scale in human metabolism. We apply a novel in silico approach to sample the depth of epistasis in the human metabolic network with respect to a variety of metabolic objectives.

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“…• Synthetically lethal gene pairs: Gene pairs whose simultaneous low-or non-expression can cause the organism to die are called synthetically lethal pairs [31,32]. The presence of synthetically lethal pairs of genes across two pathways is a possible sign of pathway crosstalks.…”

mentioning

confidence: 99%

Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach

et al. 2017

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Alzheimer's disease (AD) is a major public health threat; however, despite decades of research, the disease mechanisms are not completely understood, and there is a significant dearth of predictive biomarkers. The availability of systems biology approaches has opened new avenues for understanding disease mechanisms at a pathway level. However, to the best of our knowledge, no prior study has characterized the nature of pathway crosstalks in AD, or examined their utility as biomarkers for diagnosis or prognosis. In this paper, we build the first computational crosstalk model of AD incorporating genetics, antecedent knowledge, and biomarkers from a national study to create a generic pathway crosstalk reference map and to characterize the nature of genetic and protein pathway crosstalks in mild cognitive impairment (MCI) subjects. We perform initial studies of the utility of incorporating these crosstalks as biomarkers for assessing the risk of MCI progression to AD dementia. Our analysis identified Single Nucleotide Polymorphism-enriched pathways representing six of the seven Kyoto Encyclopedia of Genes and Genomes pathway categories. Integrating pathway crosstalks as a predictor improved the accuracy by 11.7% compared to standard clinical parameters and apolipoprotein E ε4 status alone. Our findings highlight the importance of moving beyond discrete biomarkers to studying interactions among complex biological pathways.

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Genome‐scale gene/reaction essentiality and synthetic lethality analysis

Cited by 150 publications

References 73 publications

Systems Biology Perspectives on Minimal and Simpler Cells

Systems Biology Perspectives on Minimal and Simpler Cells

Deep epistasis in human metabolism

Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach

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