Biology subjects

Hunt, S. E.

Publications and source records attributed to Hunt, S. E..

8 recordsLinked to original sources

bioRxiv2025

Mapping Functional Dynamics Hotspots for Protein Engineering with NMR Peak Intensity Analysis

Structural dynamics play a crucial role in protein function, and tuning these dynamics through mutagenesis has emerged as a promising strategy for enhancing activity. However, identifying dynamics hotspots for protein engineering remains a labor-intensive challenge. Here, we demonstrate that NMR peak intensity analysis--a rapid, qualitative method with residue-level resolution--can identify functionally relevant dynamic regions with high precision. Using a family of red fluorescent proteins (RFPs) as a case study, we reveal that flexibility in specific regions of their structures correlates with function. Specifically, as quantum yield increases, the side of the {beta}-barrel closest to the chromophore phenolate moiety becomes more rigid, while the opposite side, closest to the acylimine group, gains flexibility. Notably, the phenolate face corresponds to a mutational hotspot frequently targeted in directed evolution campaigns aimed at enhancing brightness, underscoring its functional significance. B-factor analysis of non-cryogenic X-ray crystal structures further supports our findings. Our results establish NMR peak intensity analysis as a promising tool for mapping functional dynamics hotspots to guide protein engineering campaigns.

biophysics↗

bioRxiv2025

Distal mutations enhance catalysis in designed enzymes by facilitating substrate binding and product release

The role of amino-acid residues distant from an enzymes active site in facilitating the complete catalytic cycle--including substrate binding, chemical transformation, and product release-- remains poorly understood. Here, we investigate how distal mutations promote the catalytic cycle by engineering mutants of three de novo Kemp eliminases containing either active-site or distal mutations identified through directed evolution. Kinetic analyses, X-ray crystallography, and molecular dynamics simulations reveal that while active-site mutations create preorganized catalytic sites for efficient chemical transformation, distal mutations enhance catalysis by facilitating substrate binding and product release through tuning structural dynamics to widen the active-site entrance and reorganize surface loops. These distinct contributions work synergistically to improve overall activity, demonstrating that a well-organized active site, though necessary, is not sufficient for optimal catalysis. Our findings reveal critical roles that distal residues play in shaping the catalytic cycle to enhance efficiency, yielding valuable insights for enzyme design.

biochemistry↗

bioRxiv2025

Distal mutations in a designed retro-aldolase alter loop dynamics to shift and accelerate the rate-limiting step

Amino-acid residues distant from an enzymes active site are known to influence catalysis, but their mechanistic contributions to the catalytic cycle remain poorly understood. Here, we investigate the structural, functional, and mechanistic impacts of distal and active-site mutations discovered through directed evolution of the computationally designed retro-aldolase RA95. Active-site mutations improve catalytic efficiency by 3,600-fold, while distal mutations alone offer no improvement. When combined with active-site mutations, distal mutations further increase efficiency by 6-fold, demonstrating an epistatic effect. X-ray crystallography and molecular dynamics simulations reveal that distal mutations promote active site opening by altering loop dynamics. Kinetic solvent viscosity effects and electrostatic analysis show that distal mutations accelerate the chemical transformation by 100-fold, shifting the rate-limiting step to product release, which is further accelerated by the increased opening of the active site. These findings highlight the critical role of distal residues in shaping the active-site environment and facilitating the structural dynamics essential for progression through the catalytic cycle.

biochemistry↗

bioRxiv2024

Complex genetic variation in nearly complete human genomes

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8, and AMY1/AMY2, and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in -satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into -satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies.

genomics↗

bioRxiv2023

Mapping MAVE data for use in human genomics applications

The large-scale experimental measures of variant functional assays submitted to MaveDB have the potential to provide key information for resolving variants of uncertain significance, but the reporting of results relative to assayed sequence hinders their downstream utility. The Atlas of Variant Effects Alliance mapped multiplexed assays of variant effect data to human reference sequences, creating a robust set of machine-readable homology mappings. This method processed approximately 2.5 million protein and genomic variants in MaveDB, successfully mapping 98.61% of examined variants and disseminating data to resources such as the UCSC Genome Browser and Ensembl Variant Effect Predictor.

bioinformatics↗

bioRxiv2022

The complete sequence of a human Y chromosome

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure including long palindromes, tandem repeats, and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4, 5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029 base pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, revealing the complete ampliconic structures of TSPY, DAZ, and RBMY gene families; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a prior assembly of the CHM13 genome4 and mapped available population variation, clinical variants, and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

genomics↗

bioRxiv2022

SUsPECT: A pipeline for variant effect prediction based on custom long-read transcriptomes for improved clinical variant annotation

Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECTs utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

bioinformatics↗

bioRxiv2020

The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

bioinformatics↗