Massively parallel variant characterization identifies NUDT15 alleles associated with thiopurine toxicity

As a prototype of genomics-guided precision medicine, individualized thiopurine dosing based on pharmacogenetics is a highly effective way to mitigate hematopoietic toxicity of this class of drugs. Recently, NUDT15 deficiency was identified as a genetic cause of thiopurine toxicity, and NUDT15-informed preemptive dose reduction was quickly adopted in clinical settings. To exhaustively identify pharmacogenetic variants in this gene, we developed massively parallel NUDT15 function assays to determine the variants’ effect on protein abundance and thiopurine cytotoxicity. Of the 3,097 possible missense variants, we characterized the abundance of 2,922 variants and found 54 hotspot residues at which variants resulted in complete loss of protein stability. Analyzing 2,935 variants in the thiopurine cytotoxicity-based assay, we identified 17 additional residues where variants altered NUDT15 activity without affecting protein stability. We identified structural elements key to NUDT15 stability and/or catalytical activity with single amino acid resolution. Functional effects for NUDT15 variants accurately predicted toxicity risk alleles in patients treated with thiopurines with far superior sensitivity and specificity compared to bioinformatic prediction algorithms. In conclusion, our massively parallel variant function assays identified 1,152 deleterious NUDT15 variants, providing a comprehensive reference of variant function and vastly improving the ability to implement pharmacogenetics-guided thiopurine treatment individualization.

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Massive parallel variant characterization identifies NUDT15 alleles associated with thiopurine toxicity

10.1101/740837 ◽

2019 ◽

Cited By ~ 1

Author(s):

Chase C. Suiter ◽

Takaya Moriyama ◽

Kenneth A. Matreyek ◽

Wentao Yang ◽

Emma Rose Scaletti ◽

...

Keyword(s):

Protein Stability ◽

Poor Performance ◽

Massively Parallel ◽

Single Amino Acid ◽

Clinical Settings ◽

Structural Elements ◽

Risk Alleles ◽

Toxicity Risk ◽

Hematopoietic Toxicity ◽

Treatment Individualization

AbstractAs a prototype of genomics-guided precision medicine, individualized thiopurine dosing based on pharmacogenetics is a highly effective way to mitigate hematopoietic toxicity of this class of drugs. Recently, NUDT15 deficiency was identified as a novel genetic cause of thiopurine toxicity, and NUDT15-informed preemptive dose reduction is quickly adopted in clinical settings. To exhaustively identify pharmacogenetic variants in this gene, we developed massively parallel NUDT15 function assays to determine variants’ effect on protein abundance and thiopurine cytotoxicity. Of the 3,097 possible missense variants, we characterized the abundance of 2,922 variants and found 54 hotspot residues at which variants resulted in complete loss of protein stability. Analyzing 2,935 variants in the thiopurine cytotoxicity-based assay, we identified 17 additional residues where variants altered NUDT15 activity without affecting protein stability. We identified structural elements key to NUDT15 stability and/or catalytical activity with single amino-acid resolution. Functional effects for NUDT15 variants accurately predicted toxicity risk alleles in 2,398 patients treated with thiopurines, with 100% sensitivity and specificity, in contrast with poor performance of bioinformatic prediction algorithms. In conclusion, our massively parallel variant function assays identified 1,103 deleterious NUDT15 variants, providing a comprehensive reference of variant function and vastly improving the ability to implement pharmacogenetics-guided thiopurine treatment individualization.

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A single amino acid mutation (Ser180----Cys) determines the polymorphism in cytochrome P450g (P4502C13) by altering protein stability.

Journal of Biological Chemistry ◽

10.1016/s0021-9258(18)46049-8 ◽

1992 ◽

Vol 267 (3) ◽

pp. 2032-2037

Author(s):

M B Faletto ◽

P Linko ◽

J A Goldstein

Keyword(s):

Amino Acid ◽

Protein Stability ◽

Single Amino Acid ◽

Amino Acid Mutation ◽

Single Amino Acid Mutation

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Massively parallel single-amino-acid mutagenesis

Nature Methods ◽

10.1038/nmeth.3223 ◽

2015 ◽

Vol 12 (3) ◽

pp. 203-206 ◽

Cited By ~ 86

Author(s):

Jacob O Kitzman ◽

Lea M Starita ◽

Russell S Lo ◽

Stanley Fields ◽

Jay Shendure

Keyword(s):

Amino Acid ◽

Massively Parallel ◽

Single Amino Acid ◽

Amino Acid Mutagenesis

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Multiplex Assessment of Protein Variant Abundance by Massively Parallel Sequencing

10.1101/211011 ◽

2018 ◽

Cited By ~ 5

Author(s):

Kenneth A. Matreyek ◽

Lea M. Starita ◽

Jason J. Stephany ◽

Beth Martin ◽

Melissa A. Chiasson ◽

...

Keyword(s):

Amino Acid ◽

Massively Parallel Sequencing ◽

Dominant Negative ◽

Massively Parallel ◽

Single Amino Acid ◽

Protein Variant ◽

Parallel Sequencing ◽

Missense Variants ◽

Functional Variants ◽

Amino Acid Variants

ABSTRACTDetermining the pathogenicity of human genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes will likely require generalizable, scalable assays. Here we describe Variant Abundance by Massively Parallel Sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance in a single experiment. We apply VAMP-seq to quantify the abundance of 7,595 single amino acid variants of two proteins, PTEN and TPMT, in which functional variants are clinically actionable. We identify 1,079 PTEN and 805 TPMT single amino acid variants that result in low protein abundance, and may be pathogenic or alter drug metabolism, respectively. We observe selection for low-abundance PTEN variants in cancer, and our abundance data suggest that a PTEN variant accounting for ~10% of PTEN missense variants in melanomas functions via a dominant negative mechanism. Finally, we demonstrate that VAMP-seq can be applied to other genes, highlighting its potential as a generalizable assay for characterizing missense variants.

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Quantifying the Evolutionary Constraints and Potential of Hepatitis C Virus NS5A Protein

mSystems ◽

10.1128/msystems.01111-20 ◽

2021 ◽

Vol 6 (2) ◽

Author(s):

Lei Dai ◽

Yushen Du ◽

Hangfei Qi ◽

Christian D. Huber ◽

Dongdong Chen ◽

...

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Protein Stability ◽

Viral Evolution ◽

Antiviral Drug ◽

Single Amino Acid ◽

Fitness Costs ◽

Adaptive Potential ◽

Fitness Effects ◽

Ns5a Protein

ABSTRACT RNA viruses, such as hepatitis C virus (HCV), influenza virus, and SARS-CoV-2, are notorious for their ability to evolve rapidly under selection in novel environments. It is known that the high mutation rate of RNA viruses can generate huge genetic diversity to facilitate viral adaptation. However, less attention has been paid to the underlying fitness landscape that represents the selection forces on viral genomes, especially under different selection conditions. Here, we systematically quantified the distribution of fitness effects of about 1,600 single amino acid substitutions in the drug-targeted region of NS5A protein of HCV. We found that the majority of nonsynonymous substitutions incur large fitness costs, suggesting that NS5A protein is highly optimized. The replication fitness of viruses is correlated with the pattern of sequence conservation in nature, and viral evolution is constrained by the need to maintain protein stability. We characterized the adaptive potential of HCV by subjecting the mutant viruses to selection by the antiviral drug daclatasvir at multiple concentrations. Both the relative fitness values and the number of beneficial mutations were found to increase with the increasing concentrations of daclatasvir. The changes in the spectrum of beneficial mutations in NS5A protein can be explained by a pharmacodynamics model describing viral fitness as a function of drug concentration. Overall, our results show that the distribution of fitness effects of mutations is modulated by both the constraints on the biophysical properties of proteins (i.e., selection pressure for protein stability) and the level of environmental stress (i.e., selection pressure for drug resistance). IMPORTANCE Many viruses adapt rapidly to novel selection pressures, such as antiviral drugs. Understanding how pathogens evolve under drug selection is critical for the success of antiviral therapy against human pathogens. By combining deep sequencing with selection experiments in cell culture, we have quantified the distribution of fitness effects of mutations in hepatitis C virus (HCV) NS5A protein. Our results indicate that the majority of single amino acid substitutions in NS5A protein incur large fitness costs. Simulation of protein stability suggests viral evolution is constrained by the need to maintain protein stability. By subjecting the mutant viruses to selection under an antiviral drug, we find that the adaptive potential of viral proteins in a novel environment is modulated by the level of environmental stress, which can be explained by a pharmacodynamics model. Our comprehensive characterization of the fitness landscapes of NS5A can potentially guide the design of effective strategies to limit viral evolution.

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Erratum: Corrigendum: Massively parallel single-amino-acid mutagenesis

Nature Methods ◽

10.1038/nmeth0517-540b ◽

2017 ◽

Vol 14 (5) ◽

pp. 540-540

Author(s):

Jacob O Kitzman ◽

Lea M Starita ◽

Russell S Lo ◽

Stanley Fields ◽

Jay Shendure

Keyword(s):

Amino Acid ◽

Massively Parallel ◽

Single Amino Acid ◽

Amino Acid Mutagenesis

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A single amino acid variation of NV protein of viral hemorrhagic septicemia virus increases protein stability and decreases immune gene expression

Fish & Shellfish Immunology ◽

10.1016/j.fsi.2021.06.019 ◽

2021 ◽

Author(s):

Mi So Seong ◽

Eun Ah Jang ◽

Julan Kim ◽

Woo-Jin Kim ◽

JaeHun Cheong

Keyword(s):

Gene Expression ◽

Amino Acid ◽

Protein Stability ◽

Single Amino Acid ◽

Viral Hemorrhagic Septicemia Virus ◽

Immune Gene ◽

Amino Acid Variation ◽

Viral Hemorrhagic Septicemia ◽

Immune Gene Expression

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Machine learning integration for predicting the effect of single amino acid substitutions on protein stability

BMC Structural Biology ◽

10.1186/1472-6807-9-66 ◽

2009 ◽

Vol 9 (1) ◽

pp. 66 ◽

Cited By ~ 12

Author(s):

Ayşegül Özen ◽

Mehmet Gönen ◽

Ethem Alpaydın ◽

Türkan Haliloğlu

Keyword(s):

Machine Learning ◽

Amino Acid ◽

Protein Stability ◽

Single Amino Acid ◽

Amino Acid Substitutions

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Massively parallel enzyme kinetics reveals the substrate recognition landscape of the metalloprotease ADAMTS13

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1511328112 ◽

2015 ◽

Vol 112 (30) ◽

pp. 9328-9333 ◽

Cited By ~ 13

Author(s):

Colin A. Kretz ◽

Manhong Dai ◽

Onuralp Soylemez ◽

Andrew Yee ◽

Karl C. Desch ◽

...

Keyword(s):

Amino Acid ◽

Enzyme Kinetics ◽

High Throughput Sequencing ◽

Phage Display Library ◽

Massively Parallel ◽

Single Amino Acid ◽

Reaction Rate Constants ◽

Binding Domains ◽

Dependent Change ◽

Library Complexity

Proteases play important roles in many biologic processes and are key mediators of cancer, inflammation, and thrombosis. However, comprehensive and quantitative techniques to define the substrate specificity profile of proteases are lacking. The metalloprotease ADAMTS13 regulates blood coagulation by cleaving von Willebrand factor (VWF), reducing its procoagulant activity. A mutagenized substrate phage display library based on a 73-amino acid fragment of VWF was constructed, and the ADAMTS13-dependent change in library complexity was evaluated over reaction time points, using high-throughput sequencing. Reaction rate constants (kcat/KM) were calculated for nearly every possible single amino acid substitution within this fragment. This massively parallel enzyme kinetics analysis detailed the specificity of ADAMTS13 and demonstrated the critical importance of the P1-P1′ substrate residues while defining exosite binding domains. These data provided empirical evidence for the propensity for epistasis within VWF and showed strong correlation to conservation across orthologs, highlighting evolutionary selective pressures for VWF.

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