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Deep Mutational Scan of a DNA Polymerase via Compartmentalized Self-Replication

ABSTRACT: Deep Mutational Scan of a DNA Polymerase via Compartmentalized Self-Replication

PROVIDER: PRJNA1111587 | ENA |

REPOSITORIES: ENA

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Deep Mutational Scan of a DNA Polymerase via Compartmentalized Self-Replication

Project description:We present a novel platform for high-resolution mapping of DNA polymerase activity and stability under the effects of harsh chemistries that are incompatible with most other mutational scanning methods. This approach pairs compartmentalized self-replication (CSR), a high-throughput method for polymerase directed evolution, with deep mutational scanning (DMS), a method of quantifying variant effect via next-generation sequencing of libraries that are subjected to a functional selection. We demonstrate the validity of this “CSR-DMS” platform by showing that it identifies loss-of-function variants at sites with known DNA binding or catalytic activity in the wild-type protein. We further explore the efficacy of this method by imposing denaturing selective pressures (heat or guanidinium thiocyanate) during screening and showing that variants with high positive enrichment under these selective pressures possess higher resistance to denaturation in activity assays. These variants may be useful for “direct” diagnostic workflows that detect biomarkers from crude sample matrices with little to no sample purification. Furthermore, the mechanisms of stabilizing mutations can be inferred from trends in the scores of similar mutations in sequence-to-function heatmaps and corroborated by the behavior of residues of interest in molecular dynamics simulations of the wild-type protein. These mechanisms, uncovered by CSR-DMS, inform future approaches to rational design of extremely stable DNA polymerases. Overall, we propose that CSR-DMS could be used both for the study of the biophysical mechanisms of selective pressures and for the engineering of polymerases with novel capabilities.

2025-05-01 | GSE267497 | GEO

A deep mutational scan of the MHC class I-specific chaperone tapasin

Project description:A deep mutational scan of the MHC class I-specific chaperone tapasin

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Deep mutational scan of a drug efflux pump reveals its structure-function landscape

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Deep mutational scan of a drug efflux pump reveals its structure-function landscape

Project description:Drug efflux is a common resistance mechanism found in bacteria and cancer cells. Although several structures of drug efflux pumps are available, they provide only limited functional information on the phenomenon of drug efflux. Here, we performed deep mutational scanning (DMS) on the bacterial ATP binding cassette (ABC) transporter EfrCD from Enterococcus faecalis to determine the drug efflux activity profile of more than 1400 single variants

2021-11-25 | GSE189399 | GEO

A deep mutational scan of the MHC class I-specific chaperone TAPBPR for sites important for peptide editing

Project description:A deep mutational scan of the MHC class I-specific chaperone TAPBPR for sites important for peptide editing

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A comprehensive mutational scan of the TAPBPR scoop loop defines a region of the sequence-activity landscape for class I MHC interactions

Project description:The loading of high affinity peptides onto nascent class I MHC (MHC-I) molecules is facilitated by chaperones, including the class I-specific chaperone TAP-binding protein-related (TAPBPR). TAPBPR features a ‘scoop’ loop that projects towards the empty MHC-I peptide binding groove and rests above the F pocket. The scoop loop is not found in the closely related homologue tapasin, and therefore may be partly responsible for the unique antigen editing properties of TAPBPR. A deep mutational scan of the TAPBPR scoop loop defines the relative effects of all single amino acid mutations on binding and peptide-mediated release of the murine H2-Dd MHC-I allomorph. Increased hydrophobic packing between the scoop loop and rim of the peptide binding groove tightens the TAPBPR-MHC-I interaction.

2019-10-31 | GSE118568 | GEO

A focused deep mutational scan on the Env transmembrane and proximal cytosolic regions reveals an absence of sequence features for MA association

Project description:The HIV-1 surface glycoprotein Env binds target receptors to mediate fusion of the viral and host cell membranes during infection. Env is incorporated with very low density into virions, and in some cell types, regions within the long cytosolic C-terminal tail may mediate direct or indirect associations with Gag during virus assembly and budding. Here, the mutational landscape is determined across the transmembrane and proximal cytosolic domains of Env (001428 isolate from clade C) interacting with the MA domain of Gag at cellular membranes. No evidence is found in a derivative line of HEK293 cells for specific motifs that mediate Env/MA associations.

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Deep Mutational Scan of an <i>SCN5A</i> Voltage Sensor.

Project description:BackgroundVariants in ion channel genes have classically been studied in low throughput by patch clamping. Deep mutational scanning is a complementary approach that can simultaneously assess function of thousands of variants.MethodsWe have developed and validated a method to perform a deep mutational scan of variants in SCN5A, which encodes the major voltage-gated sodium channel in the heart. We created a library of nearly all possible variants in a 36 base region of SCN5A in the S4 voltage sensor of domain IV and stably integrated the library into HEK293T cells.ResultsIn preliminary experiments, challenge with 3 drugs (veratridine, brevetoxin, and ouabain) could discriminate wild-type channels from gain- and loss-of-function pathogenic variants. High-throughput sequencing of the pre- and postdrug challenge pools was used to count the prevalence of each variant and identify variants with abnormal function. The deep mutational scan scores identified 40 putative gain-of-function and 33 putative loss-of-function variants. For 8 of 9 variants, patch clamping data were consistent with the scores.ConclusionsThese experiments demonstrate the accuracy of a high-throughput in vitro scan of SCN5A variant function, which can be used to identify deleterious variants in SCN5A and other ion channel genes.

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Unsupervised Inference of Protein Fitness Landscape from Deep Mutational Scan.

Project description:The recent technological advances underlying the screening of large combinatorial libraries in high-throughput mutational scans deepen our understanding of adaptive protein evolution and boost its applications in protein design. Nevertheless, the large number of possible genotypes requires suitable computational methods for data analysis, the prediction of mutational effects, and the generation of optimized sequences. We describe a computational method that, trained on sequencing samples from multiple rounds of a screening experiment, provides a model of the genotype-fitness relationship. We tested the method on five large-scale mutational scans, yielding accurate predictions of the mutational effects on fitness. The inferred fitness landscape is robust to experimental and sampling noise and exhibits high generalization power in terms of broader sequence space exploration and higher fitness variant predictions. We investigate the role of epistasis and show that the inferred model provides structural information about the 3D contacts in the molecular fold.

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A focused deep mutational scan on the Env transmembrane and proximal cytosolic regions reveals an absence of sequence features for MA association

Project description:A focused deep mutational scan on the Env transmembrane and proximal cytosolic regions reveals an absence of sequence features for MA association

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