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Academic Appointments


Research & Scholarship

Current Research and Scholarly Interests


The Brandman Lab studies how cells ensure protein quality and how they signal stress. To achieve this, we employ an integrated set of techniques including single cell anaysis of stress pathways, structural studies, in vitro translation, and full genome screens in yeast and mammalian cells.

Teaching

2013-14 Courses


Graduate and Fellowship Programs


Publications

Journal Articles


  • A Ribosome-Bound Quality Control Complex Triggers Degradation of Nascent Peptides and Signals Translation Stress CELL Brandman, O., Stewart-Ornstein, J., Wong, D., Larson, A., Williams, C. C., Li, G., Zhou, S., King, D., Shen, P. S., Weibezahn, J., Dunn, J. G., Rouskin, S., Inada, T., Frost, A., Weissman, J. S. 2012; 151 (5): 1042-1054

    Abstract

    The conserved transcriptional regulator heat shock factor 1 (Hsf1) is a key sensor of proteotoxic and other stress in the eukaryotic cytosol. We surveyed Hsf1 activity in a genome-wide loss-of-function library in Saccaromyces cerevisiae as well as ~78,000 double mutants and found Hsf1 activity to be modulated by highly diverse stresses. These included disruption of a ribosome-bound complex we named the Ribosome Quality Control Complex (RQC) comprising the Ltn1 E3 ubiquitin ligase, two highly conserved but poorly characterized proteins (Tae2 and Rqc1), and Cdc48 and its cofactors. Electron microscopy and biochemical analyses revealed that the RQC forms a stable complex with 60S ribosomal subunits containing stalled polypeptides and triggers their degradation. A negative feedback loop regulates the RQC, and Hsf1 senses an RQC-mediated translation-stress signal distinctly from other stresses. Our work reveals the range of stresses Hsf1 monitors and elucidates a conserved cotranslational protein quality control mechanism.

    View details for DOI 10.1016/j.cell.2012.10.044

    View details for Web of Science ID 000311423500017

    View details for PubMedID 23178123

  • Feedback loops shape cellular signals in space and time SCIENCE Brandman, O., Meyer, T. 2008; 322 (5900): 390-395

    Abstract

    Positive and negative feedback loops are common regulatory elements in biological signaling systems. We discuss core feedback motifs that have distinct roles in shaping signaling responses in space and time. We also discuss approaches to experimentally investigate feedback loops in signaling systems.

    View details for DOI 10.1126/science.1160617

    View details for Web of Science ID 000260094500033

    View details for PubMedID 18927383

  • STIM2 is a feedback regulator that stabilizes basal cytosolic and endoplasmic reticulum Ca2+ levels CELL Brandman, O., Liou, J., Park, W. S., Meyer, T. 2007; 131 (7): 1327-1339

    Abstract

    Deviations in basal Ca2+ levels interfere with receptor-mediated Ca2+ signaling as well as endoplasmic reticulum (ER) and mitochondrial function. While defective basal Ca2+ regulation has been linked to various diseases, the regulatory mechanism that controls basal Ca2+ is poorly understood. Here we performed an siRNA screen of the human signaling proteome to identify regulators of basal Ca2+ concentration and found STIM2 as the strongest positive regulator. In contrast to STIM1, a recently discovered signal transducer that triggers Ca2+ influx in response to receptor-mediated depletion of ER Ca2+ stores, STIM2 activated Ca2+ influx upon smaller decreases in ER Ca2+. STIM2, like STIM1, caused Ca2+ influx via activation of the plasma membrane Ca2+ channel Orai1. Our study places STIM2 at the center of a feedback module that keeps basal cytosolic and ER Ca2+ concentrations within tight limits.

    View details for DOI 10.1016/j.cell.2007.11.039

    View details for Web of Science ID 000252217200021

    View details for PubMedID 18160041

  • Interlinked fast and slow positive feedback loops drive reliable cell decisions SCIENCE Brandman, O., Ferrett, J. E., Li, R., Meyer, T. 2005; 310 (5747): 496-498

    Abstract

    Positive feedback is a ubiquitous signal transduction motif that allows systems to convert graded inputs into decisive, all-or-none outputs. Here we investigate why the positive feedback switches that regulate polarization of budding yeast, calcium signaling, Xenopus oocyte maturation, and various other processes use multiple interlinked loops rather than single positive feedback loops. Mathematical simulations revealed that linking fast and slow positive feedback loops creates a "dual-time" switch that is both rapidly inducible and resistant to noise in the upstream signaling system.

    View details for DOI 10.1126/science.1113834

    View details for Web of Science ID 000232786000048

    View details for PubMedID 16239477

  • Protein evolution in the context of Drosophila development JOURNAL OF MOLECULAR EVOLUTION Davis, J. C., Brandman, O., Petrov, D. A. 2005; 60 (6): 774-U42

    Abstract

    The tempo at which a protein evolves depends not only on the rate at which mutations arise but also on the selective effects that those mutations have at the organismal level. It is intuitive that proteins functioning during different stages of development may be predisposed to having mutations of different selective effects. For example, it has been hypothesized that changes to proteins expressed during early development should have larger phenotypic consequences because later stages depend on them. Conversely, changes to proteins expressed much later in development should have smaller consequences at the organismal level. Here we assess whether proteins expressed at different times during Drosophila development vary systematically in their rates of evolution. We find that proteins expressed early in development and particularly during mid-late embryonic development evolve unusually slowly. In addition, proteins expressed in adult males show an elevated evolutionary rate. These two trends are independent of each other and cannot be explained by peculiar rates of mutation or levels of codon bias. Moreover, the observed patterns appear to hold across several functional classes of genes, although the exact developmental time of the slowest protein evolution differs among each class. We discuss our results in connection with data on the evolution of development.

    View details for DOI 10.1007/s00239-004-0241-2

    View details for Web of Science ID 000230077700008

    View details for PubMedID 15909223

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