Publications by authors named "Sara Sharifpoor"

Gram-negative bacterial pathogens inject type III secreted effectors (T3SEs) directly into host cells to promote pathogen fitness by manipulating host cellular processes. Despite their crucial role in promoting virulence, relatively few T3SEs have well-characterized enzymatic activities or host targets. This is in part due to functional redundancy within pathogen T3SE repertoires as well as the promiscuity of individual T3SEs that can have multiple host targets.

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To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network.

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Article Synopsis
  • The researchers created a global genetic interaction network for yeast, generating over 23 million double mutants to identify around 550,000 negative and 350,000 positive genetic interactions.
  • The network highlights essential genes as key connectors and allows for the assembly of a hierarchical model that represents various aspects of cell function, including protein complexes and biological processes.
  • Negative interactions link related genes and core biological processes, while positive interactions reflect broader regulatory connections, ultimately forming a functional wiring diagram of the cell.
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Genetic interactions occur when mutant alleles of two or more genes collaborate to generate an unusual composite phenotype, one that would not be predicted based on the expected combined effects of the individual mutant alleles. Synthetic Genetic Array (SGA) methodology was developed to automate yeast genetic analysis and enable systematic genetic interaction studies. In its simplest form, SGA consists of a series of replica pinning steps, which enable the construction of haploid double mutants through mating and meiotic recombination.

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Regulation of cell growth is a fundamental process in development and disease that integrates a vast array of extra- and intracellular information. A central player in this process is RNA polymerase I (Pol I), which transcribes ribosomal RNA (rRNA) genes in the nucleolus. Rapidly growing cancer cells are characterized by increased Pol I-mediated transcription and, consequently, nucleolar hypertrophy.

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Article Synopsis
  • Scientists are studying genes by looking at what happens when certain genes are overexpressed, which helps them understand gene function and biological processes.
  • They created a new tool using yeast, with about 5100 different strains, each containing a unique code (or barcode) that helps track how well they grow when specific genes are overexpressed.
  • This new method, called "barFLEX," allows researchers to combine these strains with different genetic backgrounds and test how they react in various environments, helping them learn more about gene interactions.
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A combinatorial genetic perturbation strategy was applied to interrogate the yeast kinome on a genome-wide scale. We assessed the global effects of gene overexpression or gene deletion to map an integrated genetic interaction network of synthetic dosage lethal (SDL) and loss-of-function genetic interactions (GIs) for 92 kinases, producing a meta-network of 8700 GIs enriched for pathways known to be regulated by cognate kinases. Kinases most sensitive to dosage perturbations had constitutive cell cycle or cell polarity functions under standard growth conditions.

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