Publications by authors named "Stanley Fields"

117 Publications

MaveRegistry: a collaboration platform for multiplexed assays of variant effect.

Bioinformatics 2021 Mar 27. Epub 2021 Mar 27.

Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada.

Summary: Multiplexed assays of variant effect (MAVEs) are capable of experimentally testing all possible single nucleotide or amino acid variants in selected genomic regions, generating 'variant effect maps', which provide biochemical insight and functional evidence to enable more rapid and accurate clinical interpretation of human variation. Because the international community applying MAVE approaches is growing rapidly, we developed the online MaveRegistry platform to catalyze collaboration, reduce redundant efforts, allow stakeholders to nominate targets, and enable tracking and sharing of progress on ongoing MAVE projects.

Availability And Implementation: MaveRegistry service: https://registry.varianteffect.org. MaveRegistry source code: https://github.com/kvnkuang/maveregistry-front-end.

Supplementary Information: no Supplementary data.
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http://dx.doi.org/10.1093/bioinformatics/btab215DOI Listing
March 2021

Balance between promiscuity and specificity in phage λ host range.

ISME J 2021 Feb 15. Epub 2021 Feb 15.

Department of Genome Sciences, University of Washington, Seattle, WA, USA.

As hosts acquire resistance to viruses, viruses must overcome that resistance to re-establish infectivity, or go extinct. Despite the significant hurdles associated with adapting to a resistant host, viruses are evolutionarily successful and maintain stable coevolutionary relationships with their hosts. To investigate the factors underlying how pathogens adapt to their hosts, we performed a deep mutational scan of the region of the λ tail fiber tip protein that mediates contact with the receptor on λ's host, Escherichia coli. Phages harboring amino acid substitutions were subjected to selection for infectivity on wild type E. coli, revealing a highly restrictive fitness landscape, in which most substitutions completely abrogate function. A subset of positions that are tolerant of mutation in this assay, but diverse over evolutionary time, are associated with host range expansion. Imposing selection for phage infectivity on three λ-resistant hosts, each harboring a different missense mutation in the λ receptor, reveals hundreds of adaptive variants in λ. We distinguish λ variants that confer promiscuity, a general ability to overcome host resistance, from those that drive host-specific infectivity. Both processes may be important in driving adaptation to a novel host.
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http://dx.doi.org/10.1038/s41396-021-00912-2DOI Listing
February 2021

Identification of Plant Enhancers and Their Constituent Elements by STARR-seq in Tobacco Leaves.

Plant Cell 2020 07 14;32(7):2120-2131. Epub 2020 May 14.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195

Genetic engineering of -regulatory elements in crop plants is a promising strategy to ensure food security. However, such engineering is currently hindered by our limited knowledge of plant -regulatory elements. Here, we adapted self-transcribing active regulatory region sequencing (STARR-seq)-a technology for the high-throughput identification of enhancers-for its use in transiently transformed tobacco () leaves. We demonstrate that the optimal placement in the reporter construct of enhancer sequences from a plant virus, pea () and wheat (), was just upstream of a minimal promoter and that none of these four known enhancers was active in the 3' untranslated region of the reporter gene. The optimized assay sensitively identified small DNA regions containing each of the four enhancers, including two whose activity was stimulated by light. Furthermore, we coupled the assay to saturation mutagenesis to pinpoint functional regions within an enhancer, which we recombined to create synthetic enhancers. Our results describe an approach to define enhancer properties that can be performed in potentially any plant species or tissue transformable by and that can use regulatory DNA derived from any plant genome.
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http://dx.doi.org/10.1105/tpc.20.00155DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346570PMC
July 2020

Distinct patterns of mutational sensitivity for resistance and maltodextrin transport in LamB.

Microb Genom 2020 04 2;6(4). Epub 2020 Apr 2.

Department of Genome Sciences, University of Washington, Seattle WA, USA.

Bacteria can evade cohabiting phages through mutations in phage receptors, but these mutations may come at a cost if they disrupt the receptor's native cellular function. To investigate the relationship between these two conflicting activities, we generated sequence-function maps of LamB with respect to sensitivity to phage and transport of maltodextrin. By comparing 413 missense mutations whose effect on both traits could be analysed, we find that these two phenotypes were correlated, implying that most mutations affect these phenotypes through a common mechanism such as loss of protein stability. However, individual mutations could be found that specifically disrupt -sensitivity without affecting maltodextrin transport. We identify and individually assay nine such mutations, whose spatial positions implicate loop L6 of LamB in binding. Although missense mutations that lead to -resistance are rare, they were approximately as likely to be maltodextrin-utilizing (Mal) as not (Mal), implying that can adapt to while conserving the receptor's native function. We propose that in order for and to stably cohabitate, selection for -resistance and maltose transport must be spatially or temporally separated.
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http://dx.doi.org/10.1099/mgen.0.000364DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276705PMC
April 2020

Dimensionality reduction by UMAP to visualize physical and genetic interactions.

Nat Commun 2020 03 24;11(1):1537. Epub 2020 Mar 24.

Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.

Dimensionality reduction is often used to visualize complex expression profiling data. Here, we use the Uniform Manifold Approximation and Projection (UMAP) method on published transcript profiles of 1484 single gene deletions of Saccharomyces cerevisiae. Proximity in low-dimensional UMAP space identifies groups of genes that correspond to protein complexes and pathways, and finds novel protein interactions, even within well-characterized complexes. This approach is more sensitive than previous methods and should be broadly useful as additional transcriptome datasets become available for other organisms.
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http://dx.doi.org/10.1038/s41467-020-15351-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093466PMC
March 2020

Binding and Regulation of Transcription by Yeast Ste12 Variants To Drive Mating and Invasion Phenotypes.

Genetics 2020 02 6;214(2):397-407. Epub 2019 Dec 6.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195

Amino acid substitutions are commonly found in human transcription factors, yet the functional consequences of much of this variation remain unknown, even in well-characterized DNA-binding domains. Here, we examine how six single-amino acid variants in the DNA-binding domain of Ste12-a yeast transcription factor regulating mating and invasion-alter Ste12 genome binding, motif recognition, and gene expression to yield markedly different phenotypes. Using a combination of the "calling-card" method, RNA sequencing, and HT-SELEX (high throughput systematic evolution of ligands by exponential enrichment), we find that variants with dissimilar binding and expression profiles can converge onto similar cellular behaviors. Mating-defective variants led to decreased expression of distinct subsets of genes necessary for mating. Hyper-invasive variants also decreased expression of subsets of genes involved in mating, but increased the expression of other subsets of genes associated with the cellular response to osmotic stress. While single-amino acid changes in the coding region of this transcription factor result in complex regulatory reconfiguration, the major phenotypic consequences for the cell appear to depend on changes in the expression of a small number of genes with related functions.
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http://dx.doi.org/10.1534/genetics.119.302929DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7017024PMC
February 2020

High-throughput identification of dominant negative polypeptides in yeast.

Nat Methods 2019 05 8;16(5):413-416. Epub 2019 Apr 8.

Department of Genome Sciences, University of Washington, Seattle, WA, USA.

Dominant negative polypeptides can inhibit protein function by binding to a wild-type subunit or by titrating a ligand. Here we use high-throughput sequencing of libraries composed of fragments of yeast genes to identify polypeptides that act in a dominant negative manner, in that they are depleted during cell growth. The method can uncover numerous inhibitory polypeptides for a protein and thereby define small inhibitory regions, even pinpointing individual residues with critical functional roles.
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http://dx.doi.org/10.1038/s41592-019-0368-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555411PMC
May 2019

Dynamics of Gene Expression in Single Root Cells of .

Plant Cell 2019 05 28;31(5):993-1011. Epub 2019 Mar 28.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195

Single cell RNA sequencing can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach to Arabidopsis () root cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat-shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.
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http://dx.doi.org/10.1105/tpc.18.00785DOI Listing
May 2019

A Multiplex Homology-Directed DNA Repair Assay Reveals the Impact of More Than 1,000 BRCA1 Missense Substitution Variants on Protein Function.

Am J Hum Genet 2018 10 12;103(4):498-508. Epub 2018 Sep 12.

Department of Biomedical Informatics, Ohio State University, Columbus, OH 43210, USA; Comprehensive Cancer Center, Ohio State University, Columbus, OH 43210, USA. Electronic address:

Loss-of-function pathogenic variants in BRCA1 confer a predisposition to breast and ovarian cancer. Genetic testing for sequence changes in BRCA1 frequently reveals a missense variant for which the impact on cancer risk and on the molecular function of BRCA1 is unknown. Functional BRCA1 is required for the homology-directed repair (HDR) of double-strand DNA breaks, a critical activity for maintaining genome integrity and tumor suppression. Here, we describe a multiplex HDR reporter assay for concurrently measuring the effects of hundreds of variants of BRCA1 for their role in DNA repair. Using this assay, we characterized the effects of 1,056 amino acid substitutions in the first 192 residues of BRCA1. Benchmarking these results against variants with known effects on DNA repair function or on cancer predisposition, we demonstrate accurate discrimination of loss-of-function versus benign missense variants. We anticipate that this assay can be used to functionally characterize BRCA1 missense variants at scale, even before the variants are observed in results from genetic testing.
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http://dx.doi.org/10.1016/j.ajhg.2018.07.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174279PMC
October 2018

Engineered Biosensors from Dimeric Ligand-Binding Domains.

ACS Synth Biol 2018 10 25;7(10):2457-2467. Epub 2018 Sep 25.

Howard Hughes Medical Institute , University of Washington , Seattle , Washington 98195 , United States.

Biosensors are important components of many synthetic biology and metabolic engineering applications. Here, we report a second generation of Saccharomyces cerevisiae digoxigenin and progesterone biosensors based on destabilized dimeric ligand-binding domains that undergo ligand-induced stabilization. The biosensors, comprising one ligand-binding domain monomer fused to a DNA-binding domain and another fused to a transcriptional activation domain, activate reporter gene expression in response to steroid binding and receptor dimerization. The introduction of a destabilizing mutation to the dimer interface increased biosensor dynamic range by an order of magnitude. Computational redesign of the dimer interface and functional selections were used to create heterodimeric pairs with further improved dynamic range. A heterodimeric biosensor built from the digoxigenin and progesterone ligand-binding domains functioned as a synthetic "AND"-gate, with 20-fold stronger response to the two ligands in combination than to either one alone. We also identified mutations that increase the sensitivity or selectivity of the biosensors to chemically similar ligands. These dimerizing biosensors provide additional flexibility for the construction of logic gates and other applications.
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http://dx.doi.org/10.1021/acssynbio.8b00242DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6317713PMC
October 2018

Preferences in a trait decision determined by transcription factor variants.

Proc Natl Acad Sci U S A 2018 08 1;115(34):E7997-E8006. Epub 2018 Aug 1.

Department of Genome Sciences, University of Washington, Seattle, WA 98195;

Few mechanisms are known that explain how transcription factors can adjust phenotypic outputs to accommodate differing environments. In , the decision to mate or invade relies on environmental cues that converge on a shared transcription factor, Ste12. Specificity toward invasion occurs via Ste12 binding cooperatively with the cofactor Tec1. Here, we determine the range of phenotypic outputs (mating vs. invasion) of thousands of DNA-binding domain variants in Ste12 to understand how preference for invasion may arise. We find that single amino acid changes in the DNA-binding domain can shift the preference of yeast toward either mating or invasion. These mutations define two distinct regions of this domain, suggesting alternative modes of DNA binding for each trait. We characterize the DNA-binding specificity of wild-type Ste12 to identify a strong preference for spacing and orientation of both homodimeric and heterodimeric sites. Ste12 mutants that promote hyperinvasion in a Tec1-independent manner fail to bind cooperative sites with Tec1 and bind to unusual dimeric Ste12 sites composed of one near-perfect and one highly degenerate site. We propose a model in which Ste12 alone may have evolved to activate invasion genes, which could explain how preference for invasion arose in the many fungal pathogens that lack Tec1.
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http://dx.doi.org/10.1073/pnas.1805882115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6112720PMC
August 2018

A Biosensor Strategy for E. coli Based on Ligand-Dependent Stabilization.

ACS Synth Biol 2018 09 14;7(9):1990-1999. Epub 2018 Aug 14.

The engineering of microorganisms to monitor environmental chemicals or to produce desirable bioproducts is often reliant on the availability of a suitable biosensor. However, the conversion of a ligand-binding protein into a biosensor has been difficult. Here, we report a general strategy for generating biosensors in Escherichia coli that act by ligand-dependent stabilization of a transcriptional activator and mediate ligand concentration-dependent expression of a reporter gene. We constructed such a biosensor by using the lac repressor, LacI, as the ligand-binding domain and fusing it to the Zif268 DNA-binding domain and RNA polymerase omega subunit transcription-activating domain. Using error-prone PCR mutagenesis of lacI and selection, we identified a biosensor with multiple mutations, only one of which was essential for biosensor behavior. By tuning parameters of the assay, we obtained a response dependent on the ligand isopropyl β-d-1-thiogalactopyranoside (IPTG) of up to a 7-fold increase in the growth rate of E. coli. The single destabilizing mutation combined with a lacI mutation that expands ligand specificity to d-fucose generated a biosensor with improved response both to d-fucose and to IPTG. However, a mutation equivalent to the one that destabilized LacI in either of two structurally similar periplasmic binding proteins did not confer ligand-dependent stabilization. Finally, we demonstrated the generality of this method by using mutagenesis and selection to engineer another ligand-binding domain, MphR, to function as a biosensor. This strategy may allow many natural proteins that recognize and bind to ligands to be converted into biosensors.
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http://dx.doi.org/10.1021/acssynbio.8b00052DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358018PMC
September 2018

Conditional accumulation of toxic tRNAs to cause amino acid misincorporation.

Nucleic Acids Res 2018 09;46(15):7831-7843

Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester School of Medicine, Rochester, NY 14642, USA.

To develop a system for conditional amino acid misincorporation, we engineered tRNAs in the yeast Saccharomyces cerevisiae to be substrates of the rapid tRNA decay (RTD) pathway, such that they accumulate when RTD is turned off. We used this system to test the effects on growth of a library of tRNASer variants with all possible anticodons, and show that many are lethal when RTD is inhibited and the tRNA accumulates. Using mass spectrometry, we measured serine misincorporation in yeast containing each of six tRNA variants, and for five of them identified hundreds of peptides with serine substitutions at the targeted amino acid sites. Unexpectedly, we found that there is not a simple correlation between toxicity and the level of serine misincorporation; in particular, high levels of serine misincorporation can occur at cysteine residues without obvious growth defects. We also showed that toxic tRNAs can be used as a tool to identify sequence variants that reduce tRNA function. Finally, we generalized this method to another tRNA species, and generated conditionally toxic tRNATyr variants in a similar manner. This method should facilitate the study of tRNA biology and provide a tool to probe the effects of amino acid misincorporation on cellular physiology.
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http://dx.doi.org/10.1093/nar/gky623DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125640PMC
September 2018

Widespread temperature sensitivity and tRNA decay due to mutations in a yeast tRNA.

RNA 2018 03 19;24(3):410-422. Epub 2017 Dec 19.

Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester School of Medicine, Rochester, New York 14642, USA.

Microorganisms have universally adapted their RNAs and proteins to survive at a broad range of temperatures and growth conditions. However, for RNAs, there is little quantitative understanding of the effects of mutations on function at high temperatures. To understand how variant tRNA function is affected by temperature change, we used the tRNA nonsense suppressor of the yeast to perform a high-throughput quantitative screen of tRNA function at two different growth temperatures. This screen yielded comparative values for 9243 single and double variants. Surprisingly, despite the ability of to grow at temperatures as low as 15°C and as high as 39°C, the vast majority of variants that could be scored lost half or more of their function when evaluated at 37°C relative to 28°C. Moreover, temperature sensitivity of a tRNA variant was highly associated with its susceptibility to the rapid tRNA decay (RTD) pathway, implying that RTD is responsible for most of the loss of function of variants at higher temperature. Furthermore, RTD may also operate in a Δ strain, which was previously thought to fully inhibit RTD. Consistent with RTD acting to degrade destabilized tRNAs, the stability of a tRNA molecule can be used to predict temperature sensitivity with high confidence. These findings offer a new perspective on the stability of tRNA molecules and their quality control at high temperature.
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http://dx.doi.org/10.1261/rna.064642.117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5824359PMC
March 2018

Deep learning of the regulatory grammar of yeast 5' untranslated regions from 500,000 random sequences.

Genome Res 2017 12 2;27(12):2015-2024. Epub 2017 Nov 2.

Department of Electrical Engineering, University of Washington, Seattle, Washington 98195, USA.

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of -regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the protein expression of the 5' untranslated region (UTR) of mRNAs in the yeast We constructed a library of half a million 50-nucleotide-long random 5' UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on protein expression of Kozak sequence composition, upstream open reading frames (uORFs), and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the protein expression of both a held-out set of the random 5' UTRs as well as native 5' UTRs. The model additionally was used to computationally evolve highly active 5' UTRs. We confirmed experimentally that the great majority of the evolved sequences led to higher protein expression rates than the starting sequences, demonstrating the predictive power of this model.
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http://dx.doi.org/10.1101/gr.224964.117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741052PMC
December 2017

A Massively Parallel Fluorescence Assay to Characterize the Effects of Synonymous Mutations on Expression.

Mol Cancer Res 2017 10 26;15(10):1301-1307. Epub 2017 Jun 26.

Department of Genome Sciences, University of Washington, Seattle, Washington.

Although synonymous mutations can affect gene expression, they have generally not been considered in genomic studies that focus on mutations that increase the risk of cancer. However, mounting evidence implicates some synonymous mutations as driver mutations in cancer. Here, a massively parallel assay, based on cell sorting of a reporter containing a segment of p53 fused to GFP, was used to measure the effects of nearly all synonymous mutations in exon 6 of In this reporter context, several mutations within the exon caused strong expression changes including mutations that may cause potential gain or loss of function. Further analysis indicates that these effects are largely attributed to errors in splicing, including exon skipping, intron inclusion, and exon truncation, resulting from mutations both at exon-intron junctions and within the body of the exon. These mutations are found at extremely low frequencies in healthy populations and are enriched a few-fold in cancer genomes, suggesting that some of them may be driver mutations in This assay provides a general framework to identify previously unknown detrimental synonymous mutations in cancer genes. Using a massively parallel assay, this study demonstrates that synonymous mutations in the gene affect protein expression, largely through their impact on splicing. http://mcr.aacrjournals.org/content/molcanres/15/10/1301/F1.large.jpg .
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http://dx.doi.org/10.1158/1541-7786.MCR-17-0245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5626615PMC
October 2017

Adjacent Codons Act in Concert to Modulate Translation Efficiency in Yeast.

Cell 2016 Jul 30;166(3):679-690. Epub 2016 Jun 30.

Department of Biochemistry and Biophysics, School of Medicine and Dentistry, University of Rochester, Rochester, NY 14642, USA; Center for RNA Biology, University of Rochester, Rochester, NY 14642, USA. Electronic address:

Translation elongation efficiency is largely thought of as the sum of decoding efficiencies for individual codons. Here, we find that adjacent codon pairs modulate translation efficiency. Deploying an approach in Saccharomyces cerevisiae that scored the expression of over 35,000 GFP variants in which three adjacent codons were randomized, we have identified 17 pairs of adjacent codons associated with reduced expression. For many pairs, codon order is obligatory for inhibition, implying a more complex interaction than a simple additive effect. Inhibition mediated by adjacent codons occurs during translation itself as GFP expression is restored by increased tRNA levels or by non-native tRNAs with exact-matching anticodons. Inhibition operates in endogenous genes, based on analysis of ribosome profiling data. Our findings suggest translation efficiency is modulated by an interplay between tRNAs at adjacent sites in the ribosome and that this concerted effect needs to be considered in predicting the functional consequences of codon choice.
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http://dx.doi.org/10.1016/j.cell.2016.05.070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967012PMC
July 2016

Massively Parallel Genetics.

Genetics 2016 06;203(2):617-9

Department of Genome Sciences and Department of Medicine , University of Washington, Seattle, Washington 98115

Human genetics has historically depended on the identification of individuals whose natural genetic variation underlies an observable trait or disease risk. Here we argue that new technologies now augment this historical approach by allowing the use of massively parallel assays in model systems to measure the functional effects of genetic variation in many human genes. These studies will help establish the disease risk of both observed and potential genetic variants and to overcome the problem of "variants of uncertain significance."
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http://dx.doi.org/10.1534/genetics.115.180562DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896180PMC
June 2016

Comprehensive Analysis of the SUL1 Promoter of Saccharomyces cerevisiae.

Genetics 2016 05 2;203(1):191-202. Epub 2016 Mar 2.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195 Department of Medicine, University of Washington, Seattle, Washington 98195 Howard Hughes Medical Institute, University of Washington Seattle, Washington 98195

In the yeast Saccharomyces cerevisiae, beneficial mutations selected during sulfate-limited growth are typically amplifications of the SUL1 gene, which encodes the high-affinity sulfate transporter, resulting in fitness increases of >35% . Cis-regulatory mutations have not been observed at this locus; however, it is not clear whether this absence is due to a low mutation rate such that these mutations do not arise, or they arise but have limited fitness effects relative to those of amplification. To address this question directly, we assayed the fitness effects of nearly all possible point mutations in a 493-base segment of the gene's promoter through mutagenesis and selection. While most mutations were either neutral or detrimental during sulfate-limited growth, eight mutations increased fitness >5% and as much as 9.4%. Combinations of these beneficial mutations increased fitness only up to 11%. Thus, in the case of SUL1, promoter mutations could not induce a fitness increase similar to that of gene amplification. Using these data, we identified functionally important regions of the SUL1 promoter and analyzed three sites that correspond to potential binding sites for the transcription factors Met32 and Cbf1 Mutations that create new Met32- or Cbf1-binding sites also increased fitness. Some mutations in the untranslated region of the SUL1 transcript decreased fitness, likely due to the formation of inhibitory upstream open reading frames. Our methodology-saturation mutagenesis, chemostat selection, and DNA sequencing to track variants-should be a broadly applicable approach.
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http://dx.doi.org/10.1534/genetics.116.188037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4858773PMC
May 2016

A general strategy to construct small molecule biosensors in eukaryotes.

Elife 2015 Dec 29;4. Epub 2015 Dec 29.

Howard Hughes Medical Institute, University of Washington, Seattle, United States.

Biosensors for small molecules can be used in applications that range from metabolic engineering to orthogonal control of transcription. Here, we produce biosensors based on a ligand-binding domain (LBD) by using a method that, in principle, can be applied to any target molecule. The LBD is fused to either a fluorescent protein or a transcriptional activator and is destabilized by mutation such that the fusion accumulates only in cells containing the target ligand. We illustrate the power of this method by developing biosensors for digoxin and progesterone. Addition of ligand to yeast, mammalian, or plant cells expressing a biosensor activates transcription with a dynamic range of up to ~100-fold. We use the biosensors to improve the biotransformation of pregnenolone to progesterone in yeast and to regulate CRISPR activity in mammalian cells. This work provides a general methodology to develop biosensors for a broad range of molecules in eukaryotes.
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http://dx.doi.org/10.7554/eLife.10606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739774PMC
December 2015

Engineering an allosteric transcription factor to respond to new ligands.

Nat Methods 2016 Feb 21;13(2):177-83. Epub 2015 Dec 21.

Wyss Institute for Biologically-Inspired Engineering, Harvard University, Boston, Massachusetts, USA.

Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl β-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits.
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http://dx.doi.org/10.1038/nmeth.3696DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4907361PMC
February 2016

The role of functional data in interpreting the effects of genetic variation.

Mol Biol Cell 2015 Nov;26(22):3904-8

Department of Genome Sciences, University of Washington, Seattle, WA 98195 Department of Medicine, University of Washington, Seattle, WA 98195 Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195

Progress in DNA-sequencing technologies has provided a catalogue of millions of DNA variants in the human population, but characterization of the functional effects of these variants has lagged far behind. For example, sequencing of tumor samples is driving an urgent need to classify whether or not mutations seen in cancers affect disease progression or treatment effectiveness or instead are benign. Furthermore, mutations can interact with genetic background and with environmental effects. A new approach, termed deep mutational scanning, has enabled the quantitative assessment of the effects of thousands of mutations in a protein. However, this type of experiment is carried out in model organisms, tissue culture, or in vitro; typically addresses only a single biochemical function of a protein; and is generally performed under a single condition. The current challenge lies in using these functional data to generate useful models for the phenotypic consequences of genetic variation in humans.
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http://dx.doi.org/10.1091/mbc.E15-03-0153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710221PMC
November 2015

Functional Analysis of BARD1 Missense Variants in Homology-Directed Repair of DNA Double Strand Breaks.

Hum Mutat 2015 Dec 22;36(12):1205-14. Epub 2015 Sep 22.

Department of Biomedical Informatics, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio.

Genes associated with hereditary breast and ovarian cancer (HBOC) are often sequenced in search of mutations that are predictive of susceptibility to these cancer types, but the sequence results are frequently ambiguous because of the detection of missense substitutions for which the clinical impact is unknown. The BARD1 protein is the heterodimeric partner of BRCA1 and is included on clinical gene panels for testing for susceptibility to HBOC. Like BRCA1, it is required for homology-directed DNA repair (HDR). We measured the HDR function of 29 BARD1 missense variants, 27 culled from clinical test results and two synthetic variants. Twenty-three of the assayed variants were functional for HDR; of these, four are known neutral variants. Three variants showed intermediate function, and three others were defective in HDR. When mapped to BARD1 domains, residues crucial for HDR were located in the N- and C- termini of BARD1. In the BARD1 RING domain, critical residues mapped to the zinc-coordinating amino acids and to the BRCA1-BARD1 binding interface, highlighting the importance of interaction between BRCA1 and BARD1 for HDR activity. Based on these results, we propose that the HDR assay is a useful complement to genetic analyses to classify BARD1 variants of unknown clinical significance.
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http://dx.doi.org/10.1002/humu.22902DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005381PMC
December 2015

Deep Mutational Scanning: A Highly Parallel Method to Measure the Effects of Mutation on Protein Function.

Cold Spring Harb Protoc 2015 Aug 3;2015(8):711-4. Epub 2015 Aug 3.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195; Department of Medicine, University of Washington, Seattle, Washington 98195; Howard Hughes Medical Institute, Seattle, Washington 98195.

Deep mutational scanning is a method that makes use of next-generation sequencing technology to measure in a single experiment the activity of 10(5) or more unique variants of a protein. Because of this depth of mutational coverage, this strategy provides data that can be analyzed to reveal many protein properties. Deep mutational scanning approaches are particularly amenable to being performed in Saccharomyces cerevisiae, given the extensive toolkit of reagents and technologies available for this organism.
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http://dx.doi.org/10.1101/pdb.top077503DOI Listing
August 2015

Deep Mutational Scanning: Calculating Enrichment Scores for Protein Variants from DNA Sequencing Output Files.

Cold Spring Harb Protoc 2015 Aug 3;2015(8):781-3. Epub 2015 Aug 3.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195; Department of Medicine, University of Washington, Seattle, Washington 98195; Howard Hughes Medical Institute, Seattle, Washington 98195.

During a deep mutational scanning experiment, a collection of variants of a given protein is subjected to high-throughput sequencing before and after selection. The variants that perform well during selection will increase in abundance, whereas those that perform poorly will decrease. Generating a sequence-function map of a protein from a deep mutational scan requires the calculation and comparison of the enrichment scores for each protein variant, based on the results of high-throughput DNA sequencing output files. Here we describe the use of the software program Enrich, which was written specifically for the data analysis phase of a deep mutational scanning experiment.
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http://dx.doi.org/10.1101/pdb.prot085233DOI Listing
August 2015

Deep Mutational Scanning: Library Construction, Functional Selection, and High-Throughput Sequencing.

Cold Spring Harb Protoc 2015 Aug 3;2015(8):777-80. Epub 2015 Aug 3.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195; Department of Medicine, University of Washington, Seattle, Washington 98195; Howard Hughes Medical Institute, Seattle, Washington 98195.

Deep mutational scanning is a highly parallel method that uses high-throughput sequencing to track changes in >10(5) protein variants before and after selection to measure the effects of mutations on protein function. Here we outline the stages of a deep mutational scanning experiment, focusing on the construction of libraries of protein sequence variants and the preparation of Illumina sequencing libraries.
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http://dx.doi.org/10.1101/pdb.prot085225DOI Listing
August 2015

Massively Parallel Functional Analysis of BRCA1 RING Domain Variants.

Genetics 2015 Jun 30;200(2):413-22. Epub 2015 Mar 30.

Department of Genome Sciences, University of Washington, Seattle, Washington 98195 Department of Medicine, University of Washington, Seattle, Washington 98195 Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195

Interpreting variants of uncertain significance (VUS) is a central challenge in medical genetics. One approach is to experimentally measure the functional consequences of VUS, but to date this approach has been post hoc and low throughput. Here we use massively parallel assays to measure the effects of nearly 2000 missense substitutions in the RING domain of BRCA1 on its E3 ubiquitin ligase activity and its binding to the BARD1 RING domain. From the resulting scores, we generate a model to predict the capacities of full-length BRCA1 variants to support homology-directed DNA repair, the essential role of BRCA1 in tumor suppression, and show that it outperforms widely used biological-effect prediction algorithms. We envision that massively parallel functional assays may facilitate the prospective interpretation of variants observed in clinical sequencing.
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http://dx.doi.org/10.1534/genetics.115.175802DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4492368PMC
June 2015

A tetO Toolkit To Alter Expression of Genes in Saccharomyces cerevisiae.

ACS Synth Biol 2015 Jul 17;4(7):842-52. Epub 2015 Mar 17.

†Howard Hughes Medical Institute, ‡Department of Genome Sciences, §Department of Medicine, University of Washington, Seattle, Washington 98195, United States.

Strategies to optimize a metabolic pathway often involve building a large collection of strains, each containing different versions of sequences that regulate the expression of pathway genes. Here, we develop reagents and methods to carry out this process at high efficiency in the yeast Saccharomyces cerevisiae. We identify variants of the Escherichia coli tet operator (tetO) sequence that bind a TetR-VP16 activator with differential affinity and therefore result in different TetR-VP16 activator-driven expression. By recombining these variants upstream of the genes of a pathway, we generate unique combinations of expression levels. Here, we built a tetO toolkit, which includes the I-OnuI homing endonuclease to create double-strand breaks, which increases homologous recombination by 10(5); a plasmid carrying six variant tetO sequences flanked by I-OnuI sites, uncoupling transformation and recombination steps; an S. cerevisiae-optimized TetR-VP16 activator; and a vector to integrate constructs into the yeast genome. We introduce into the S. cerevisiae genome the three crt genes from Erwinia herbicola required for yeast to synthesize lycopene and carry out the recombination process to produce a population of cells with permutations of tetO variants regulating the three genes. We identify 0.7% of this population as making detectable lycopene, of which the vast majority have undergone recombination at all three crt genes. We estimate a rate of ∼20% recombination per targeted site, much higher than that obtained in other studies. Application of this toolkit to medically or industrially important end products could reduce the time and labor required to optimize the expression of a set of metabolic genes.
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http://dx.doi.org/10.1021/sb500363yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4506738PMC
July 2015

Combining natural sequence variation with high throughput mutational data to reveal protein interaction sites.

PLoS Genet 2015 Feb 11;11(2):e1004918. Epub 2015 Feb 11.

Howard Hughes Medical Institute, University of Washington, Seattle, Washington, United States of America; Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America; Department of Medicine, University of Washington, Seattle, Washington, United States of America.

Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a homologue is substituted into a protein and tested for its ability to support function. Therefore, substitutions that inhibit function can identify interaction sites that changed over evolution. However, most of the sequence differences within a protein family remain unexplored because of the small-scale nature of these complementation approaches. Here we use existing high throughput mutational data on the in vivo function of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein, Pab1, to analyze its sites of interaction. Of 197 single amino acid differences in 52 Pab1 homologues, 17 reduce the function of Pab1 when substituted into the yeast protein. The majority of these deleterious mutations interfere with the binding of the RRM2 domain to eIF4G1 and eIF4G2, isoforms of a translation initiation factor. A large-scale mutational analysis of the RRM2 domain in a two-hybrid assay for eIF4G1 binding supports these findings and identifies peripheral residues that make a smaller contribution to eIF4G1 binding. Three single amino acid substitutions in yeast Pab1 corresponding to residues from the human orthologue are deleterious and eliminate binding to the yeast eIF4G isoforms. We create a triple mutant that carries these substitutions and other humanizing substitutions that collectively support a switch in binding specificity of RRM2 from the yeast eIF4G1 to its human orthologue. Finally, we map other deleterious substitutions in Pab1 to inter-domain (RRM2-RRM1) or protein-RNA (RRM2-poly(A)) interaction sites. Thus, the combined approach of large-scale mutational data and evolutionary conservation can be used to characterize interaction sites at single amino acid resolution.
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http://dx.doi.org/10.1371/journal.pgen.1004918DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335499PMC
February 2015