Leandra M. Brettner
University of Washington
9 Papers
7 Citations
Leandra M. Brettner is an academic researcher from University of Washington. The author has contributed to research in topics: Biology & RNA. The author has an hindex of 4, co-authored 5 publications. Previous affiliations of Leandra M. Brettner include University of Arizona.
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Papers
Microbial single-cell RNA sequencing by split-pool barcoding
Anna Kuchina,Leandra M. Brettner,Luana Paleologu,Charles M. Roco,Alexander B. Rosenberg,Alberto Carignano,Ryan Kibler,Matthew Hirano,R. William DePaolo,Georg Seelig +9 more
TL;DR: Examining B. subtilis transcriptional patterns revealed that a small fraction of cells grown in laboratory medium express a myo-inositol catabolism pathway, thus highlighting how microSPLiT can identify rare cellular states.
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Microbial single-cell RNA sequencing by split-pool barcoding
Anna Kuchina,Leandra M. Brettner,Luana Paleologu,Charles M. Roco,Alexander B. Rosenberg,Alberto Carignano,Ryan Kibler,Matthew Hirano,R. William DePaolo,Georg Seelig +9 more
TL;DR: This work introduces microSPLiT, a low cost and high-throughput scRNA-seq method that works for gram-negative and gram-positive bacteria and can resolve transcriptional states that remain hidden at a population level.
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Protein stickiness, rather than number of functional protein-protein interactions, predicts expression noise and plasticity in yeast
TL;DR: It is found that protein “stickiness”, measured as network degree in ostensibly low quality yeast two-hybrid data, is a more predictive genomic metric than the number of functional protein-protein interactions, as assessed by supposedly higher quality high throughput affinity capture mass spectrometry data.
Challenges and potential solutions for studying the genetic and phenotypic architecture of adaptation in microbes.
Leandra M. Brettner,Wei-Chin Ho,Kara Schmidlin,Sam Apodaca,Rachel Eder,Kerry Geiler-Samerotte +5 more
TL;DR: In this article , the authors present a review of recent literature in yeast and identify three emerging synergistic solutions: higher-throughput evolution experiments combined with updated genotype-phenotype mapping strategies and physiological models.
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Self-destructive altruism in a synthetic developmental program enables complex feedstock utilization
TL;DR: This work introduces the altruistic developmental program as a tool for synthetic biology, demonstrates the utility of population dynamics models to engineer multicellular behaviors and provides a testbed for probing the evolutionary biology of self-destructive altruism.
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