Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting

Abstract

Ubiquitin is essential for eukaryotic life and varies in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies indicate that ubiquitin is highly tolerant to single mutations. We hypothesized that this tolerance would be reduced by chemically induced physiologic perturbations. To test this hypothesis, a class of first year UCSF graduate students employed deep mutational scanning to determine the fitness landscape of all possible single residue mutations in the presence of five different small molecule perturbations. These perturbations uncover 'shared sensitized positions' localized to areas around the hydrophobic patch and the C-terminus. In addition, we identified perturbation specific effects such as a sensitization of His68 in HU and a tolerance to mutation at Lys63 in DTT. Our data show how chemical stresses can reduce buffering effects in the ubiquitin proteasome system. Finally, this study demonstrates the potential of lab-based interdisciplinary graduate curriculum.DOI: http://dx.doi.org/10.7554/eLife.15802.001

RheoScale: A tool to aggregate and quantify experimentally determined substitution outcomes for multiple variants at individual protein positions

“…In combination with biological competition assays, recent advances in gene sequencing have enabled "deep mutational scanning" of structure/function outcomes for large libraries of amino acid variants (Fowler & Fields, 2014;Gray, Hause, & Fowler, 2017;Roscoe, Thayer, Zeldovich, Fushman, & Bolon, 2013). Although the assay output is (i) a combination of all possible changes in stability and function, and (ii) sensitive to the threshold of the biological competition assay (Mavor et al, 2016), data for a given position usually report results for all The substituted regions (Chan et al, 2017) are colored with alternating green and magenta. Each of these regions comprise a strand and parts of the flanking N-and C-loops; these eight strands form the central beta barrel of the protein.…”

Experimental Estimation of the Effects of All Amino-Acid Mutations to HIV’s Envelope Protein on Viral Replication in Cell Culture

“…These experiments involve creating large libraries of mutants of a gene, subjecting them to bulk functional selections, and quantifying the effect of each mutation by using deep sequencing to assess its frequency pre- and post-selection. Over the last few years, deep mutational scanning has been used to estimate the effects of all single amino-acid mutations to a variety of proteins or protein domains [26–39], as well as to estimate the effects of a fraction of the amino-acid mutations to many additional proteins (e.g., [40–42]). When these experiments examine all amino-acid mutations, they can be used to compute the mutational tolerance of each protein site, thereby shedding light on a protein’s inherent evolutionary capacity.…”

Inference of epistatic effects leading to entrenchment and drug resistance in HIV-1 protease

“…With the increase in available sequence data and the rise in high-throughput fitness measurements (Hinkley et al 2011;Haddox et al 2016;Mavor et al 2016;Wu et al 2016), it should be possible to verify whether the Potts model correctly predicts the trends shown in figure 4 and supplementary figure S6, Supplementary Material online, and the relative fitness cost upon reverting the primary mutation to wildtype for the selected sequences pairs listed in table 1.…”