Structural and Functional Characterization of G Protein-Coupled Receptors with Deep Mutational Scanning
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA604999 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11031448_1.fastq.gz | Fastqsanger.gz | |||
| SRR11031448_2.fastq.gz | Fastqsanger.gz | |||
| SRR11031449_1.fastq.gz | Fastqsanger.gz | |||
| SRR11031449_2.fastq.gz | Fastqsanger.gz | |||
| SRR11031450_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 36 |
Similar Datasets
Project description:In humans, the 813 G protein-coupled receptors (GPCRs) are responsible for transducing diverse chemical stimuli to alter cell state, and are the largest class of drug targets. Their myriad structural conformations and various modes of signaling make it challenging to understand their structure and function. Here we developed a platform to characterize large libraries of GPCR variants in human cell lines with a barcoded transcriptional reporter of G-protein signal transduction. We tested 7,800 of 7,828 possible single amino acid substitutions to the beta-2 adrenergic receptor (β2AR) at four concentrations of the agonist isoproterenol. We identified residues specifically important for β2AR signaling, mutations in the human population that are potentially loss of function, and residues that modulate basal activity. Using unsupervised learning, we resolve residues critical for signaling, including all major structural motifs and molecular interfaces. We also find a previously uncharacterized structural latch spanning the first two extracellular loops that is highly conserved across Class A GPCRs and is conformationally rigid in both the inactive and active states of the receptor. More broadly, by linking deep mutational scanning with engineered transcriptional reporters, we establish a generalizable method for exploring pharmacogenomics, structure and function across broad classes of drug receptors.
2020-02-06 | GSE144819 | GEO
Project description:Deep mutational scanning is a powerful method for exploring the mutational fitness landscape of proteins. Its adaptation to anti-CRISPR proteins, which are natural CRISPR-Cas inhibitors and key players in the co-evolution of microbes and phages, facilitates their characterization and optimization. Here, we developed a robust anti-CRISPR deep mutational scanning pipeline in Escherichia coli that combines synthetic gene circuits based on CRISPR interference with flow cytometry coupled sequencing and mathematical modeling. Using this pipeline, we characterized comprehensive single point mutation libraries for AcrIIA4 and AcrIIA5, two potent inhibitors of CRISPR-Cas9. The resulting mutational fitness landscapes revealed considerable mutational tolerance for both Acrs, suggesting an intrinsic redundancy with respect to Cas9 inhibitory features, and – for AcrIIA5 – indicated mutations that boost Cas9 inhibition. Subsequent in vitro characterization suggested that the observed differences in inhibitory potency between mutant inhibitors were mostly due to changes in binding affinity rather than protein expression levels. Finally, to demonstrate that our pipeline can inform Acrs-based genome editing applications, we employed a selected subset of mutant inhibitors to increase CRISPR-Cas9 target specificity by modulating Cas9 activity. Taken together, our work establishes deep mutational scanning as a powerful method for anti-CRISPR protein characterization and optimization.
2024-03-01 | GSE254101 | GEO
Project description:The >800 human G protein-coupled receptors (GPCRs) are responsible for transducing diverse chemical stimuli to alter cell state- and are the largest class of drug targets. Their myriad structural conformations and various modes of signaling make it challenging to understand their structure and function. Here, we developed a platform to characterize large libraries of GPCR variants in human cell lines with a barcoded transcriptional reporter of G protein signal transduction. We tested 7800 of 7828 possible single amino acid substitutions to the beta-2 adrenergic receptor (?2AR) at four concentrations of the agonist isoproterenol. We identified residues specifically important for ?2AR signaling, mutations in the human population that are potentially loss of function, and residues that modulate basal activity. Using unsupervised learning, we identify residues critical for signaling, including all major structural motifs and molecular interfaces. We also find a previously uncharacterized structural latch spanning the first two extracellular loops that is highly conserved across Class A GPCRs and is conformationally rigid in both the inactive and active states of the receptor. More broadly, by linking deep mutational scanning with engineered transcriptional reporters, we establish a generalizable method for exploring pharmacogenomics, structure and function across broad classes of drug receptors.
| S-EPMC7707821 | biostudies-literature
Project description:Deep mutational scanning of the interaction of JUN's leucine zipper domain and other human bZIPs in different experimental conditions
2023-10-18 | GSE245485 | GEO
Project description:The HIV-1 genome gains access to the inside of a cell via the mechanism of the viral spike protein Env, which undergoes a series of major conformational rearrangements after binding target receptors that ultimately drive virus-cell membrane fusion. Env is expressed as a heterogenous ensemble of conformations, which can inappropriately misdirect the host immune response towards the production of non-protective, strain-specific antibodies. Potent, broadly neutralizing antibodies (bnAbs) frequently recognize a ‘closed’ Env conformation, and therefore Env has undergone significant engineering to stabilize the closed state for vaccine incorporation. Previously, we used deep mutational scanning of Env from a prototypical tier 1 clade B strain (BaL) to characterize the sequence-activity landscape for binding to PG16, a bnAb that preferentially binds the closed state. Mutations were identified that increased expression of closed Env and reduced conformational heterogeneity, but these mutations were only partially transferable to Env sequences from other strains. To generate an expanded set of mutations that may be broadly applicable to diverse HIV-1 strains, we present here the deep mutational scanning of Env from the tier 2 clade C strain DU422 for interactions with CD4 and PG16. Residues across the trimerization domain and trimer interface have low mutational tolerance for maintaining PG16 recognition. New mutations are identified that enhance presentation of the closed Env conformation, and these are applied to Env sequences spanning multiple clades and tiers.
2019-02-01 | GSE117328 | GEO
Project description:Despite the importance of Aβ aggregation in Alzheimer’s disease etiology, our understanding of the sequence determinants of aggregation is sparse and largely derived from in vitro studies. For example, in vitro proline and alanine scanning mutagenesis of Aβ40 proposed core regions important for aggregation. However, we lack even this limited mutagenesis data for the more disease-relevant Aβ42. Thus, to better understand the molecular determinants of Aβ42 aggregation in a cell-based system, we combined a yeast DHFR aggregation assay with deep mutational scanning. We measured the effect of 791 of the 798 possible single amino acid substitutions on the aggregation propensity of Aβ42. We found that ~75% of substitutions, largely to hydrophobic residues, maintained or increased aggregation. We identified 11 positions at which substitutions, particularly to hydrophilic and charged amino acids, disrupted Aβ aggregation. These critical positions were similar but not identical to critical positions identified in previous Aβ mutagenesis studies. Finally, we analyzed our large-scale mutagenesis data in the context of different Aβ aggregate structural models, finding that the mutagenesis data agreed best with models derived from fibrils seeded using brain-derived Aβ aggregates.
2019-10-21 | GSE139122 | GEO
Project description:This dataset provides allele counts and raw fastqs for deep mutational scanning of the HIV-1 genes tat and rev when not-overlapped with one another (placed in the nef locus) as described in Fernandes et al. Functional segregation of overlapping genes in HIV Cell 2016 (in revision). Preselection (input) and post selection (replicate 1/2) files for every possible point mutant of these two HIV proteins from the NL4-3 background are given.Tab delimited files including codon counts across the amplicons are also included and are probably the most useful thing to most researchers. The data here was used to generate Figures 3 and 4 and 7 and might be of general use for people interested in deep mutational scanning, looking for signatures of epistasis in rev or tat, or reanalyzing and mining the data. FAQ: Why do the ends of each amplicon have such variation? In order to increase diversity across the flowcell, I pooled standard primers with N, NN, and NNN extensions to throw amplicons out of phase. When aligning you should trim the ends or ignore them. This means that the overlap between PE's can vary by 3 nt. Why are the filenames not easy to deal with? The filenames are tied to separate MiSeq runs. I hope to clean up the nomenclature and update this entry in the future while preserving the run information. You can get a sense of that as different residues will vary in Q-score, and that is mostly tied to the run they were pooled on and not any interesting biology. While this is makes it a little harder to follow, I think it's good to get a sense that doing this kind of analysis in high-throughput fashion leads to a reasonable amount of failure (i.e. RNA isolation, RT, fail) that led to repetition until we had good data for every position. Can you help me deal with this dataset? Yes. Please email me at jferna10@ucsc.edu, or contact me on twitter @jdf_ev. For reagents please contact Alan Frankel at frankel@cgl.ucsf.edu. Do you have the analysis scripts you used to process the data? Yes they are on github. https://github.com/nbstrauli/allele_frequency_trajectory_sim
2016-10-30 | E-MTAB-5154 | biostudies-arrayexpress
Project description:Chemokine receptors CXCR4 and CCR5 regulate white blood cell trafficking, and are engaged by the HIV-1 envelope glycoprotein gp120 during infection. We combine directed evolution of CXCR4 and CCR5 libraries comprising nearly all ~7,000 single amino acid substitutions with deep sequencing to define sequence-fitness landscapes for surface expression and ligand interactions. Functional interaction sites are mapped based on conservation; for example, extracellular residues are conserved for binding HIV-1-blocking antibodies, as expected. Chemokine CXCL12 interacts with residues extending asymmetrically into the CXCR4 ligand-binding cavity, and distal mutations within allosteric and G protein coupling sites are identified that enhance chemokine binding. CCR5 residues conserved for gp120 interactions partially overlap with the chemokine-binding site, and gp120 binding is increased by acidic substitutions in the CCR5 N-terminus and extracellular loops. Furthermore, general features are apparent from sequence patterns, including membrane regions that are intolerant to polar mutations, and deleterious cysteine substitutions within extracellular loops.
2018-04-23 | GSE100368 | GEO
Project description:Elucidating the molecular determinants of Aβ aggregation with deep mutational scanning
| PRJNA578530 | ENA
Project description:Deep mutational scanning of CYP2C19 reveals a substrate specificity-abundance tradeoff
| PRJNA1023263 | ENA