Biology subjects

Hunt, A.

Publications and source records attributed to Hunt, A..

10 recordsLinked to original sources

bioRxiv2026

Reliable and Efficient Agentic Protein Design with Toolset Harnessing

Computational protein design workflows require the orchestration of multiple tools, data formats, and analysis steps that are often fragmented. Here, we introduce Chaperone, a lightweight and customizable framework that enables seamless integration of RFdiffusion3 (RFD3) with downstream sequence design, structure prediction, and evaluation tools, including ProteinMPNN, AlphaFold3 (AF3), and more than 50 other protein design tools. By combining a programmable agent-friendly interface with parallelized execution on high-performance computing systems, Chaperone as a harness enables rapid iteration and scalable exploration of complex protein design workflows. Across an evaluation of nine biomolecular design tasks, we find using Chaperone reduces total token usage relative to baseline agents by 86% and GPU costs by 64%, while increasing the overall computational design pass rate. We demonstrate Chaperones utility for large-scale design-space exploration through a two-week end-to-end small-molecule binder design campaign, yielding low nanomolar binders to cortisol zero shot. We further demonstrate its versatility across distinct design challenges, including the design of a symmetric 12-subunit self-assembly nanoparticle and a linker that mediates interactions between C2- and D3-symmetric protein complexes to form crystalline assemblies. Together, these results demonstrate how agent harnesses built around standardized tool interfaces can substantially improve the efficiency and success of complex, long-horizon agentic design workflows in biology. We make Chaperone freely available to the community on GitHub: https://github.com/RosettaCommons/chaperone.

biochemistry↗

bioRxiv2026

Guide scaffolding improves phylogenetic accuracy and enables integration across 16S amplicon regions

The growing magnitude and scale of microbiome studies now support application of meta-analytical frameworks, however the challenge of integrating microbiome sequence data across distinct studies into a unified phylogeny remains a critical barrier to progress. The 16S rDNA gene has been key to sequence-based phylogenetic microbial community analyses for over 30 years in applications ranging from human health to agricultural production efficiency. Because the full length 16S gene ([~]1500 base pairs) is longer than what short-read sequencing technologies can typically capture, researchers must target a portion of the gene, or variable region, typically [~]250 base pairs in length. Using a simulation-based approach, we show that full-length, phylogenetically diverse 16S guide sequences can serve as a scaffold to improve topological accuracy of phylogenetic trees constructed from any variable region. We also show that guide sequences can provide enough essential context to build accurate tree topologies, even in the case of disjoint amplicons, allowing for integration of microbial datasets across variable regions. We validate that our findings extend to experimental data. Our approach not only suggests that guide sequences should become a standard for building phylogenetic trees from any short-read microbial data, but also extends microbial meta-analytical methods by allowing phylogenetic integration across cohorts which have used different variable regions to assess the microbiomes association with ecosystem services. We provide an easily usable application of our method, phyloguidesR, as an open-sourced tool to enable any researcher to apply and use guide sequences easily in their microbial community of interest. IMPORTANCEIntegrating data across independent studies can uncover robust biological patterns that strengthen inference and support more generalizable conclusions. In microbiome research, such integration is constrained by the heterogeneity of how microbial communities are sequenced. May studies target different regions of the 16S rDNA gene, producing datasets that lack a shared phylogenetic framework, and are difficult to analyze together without discarding information. As a result, comparisons across studies often rely on coarse conglomeration of taxonomic summaries or exclude entire datasets to integrate results. Here, we introduce a phylogenetic scaffolding framework that produces more accurate phylogenetic trees and demonstrate that it can unify even non-overlapping 16S amplicon datasets. Such integration has the power to reveal generalizable patterns that are invisible within individual microbiome studies, where noise and region-specific amplification have long obscured biological signals. In doing so, guides set the stage for a more powerful and integrative microbiome science at scale.

microbiology↗

bioRxiv2025

Image-based Morphological Profiling Reveals Signatures of Radiation Exposure

Exposure to ionizing radiation has the potential to induce significant health risks including radiation sickness and death. Here, the utility of image-based morphological profiling (IBMP) assays was investigated as a method to visualize signatures of radiation over time. Human-derived fibroblasts were used as the model system, and were exposed to varying doses of radiation. Cell Painting protocols were then applied to generate images for profiling. Quantitative analysis of images taken from fibroblasts exposed to 1 Gray of ionizing radiation revealed considerable morphological changes by 24 hours post-exposure, with some morphological signs of exposure emerging as early as 4 hours post-exposure. This work demonstrates proof-of-concept for the use of cell painting and IBMP to visualize signatures of radiation, paving the way for its use as a tool for assessing repeated exposures, screening of potential treatments, and establishing relevant timepoints for downstream orthogonal assays.

cell biology↗

bioRxiv2024

Computational design of serine hydrolases

Enzymes that proceed through multistep reaction mechanisms often utilize complex, polar active sites positioned with sub-angstrom precision to mediate distinct chemical steps, which makes their de novo construction extremely challenging. We sought to overcome this challenge using the classic catalytic triad and oxyanion hole of serine hydrolases as a model system. We used RFdiffusion1 to generate proteins housing catalytic sites of increasing complexity and varying geometry, and a newly developed ensemble generation method called ChemNet to assess active site geometry and preorganization at each step of the reaction. Experimental characterization revealed novel serine hydrolases that catalyze ester hydrolysis with catalytic efficiencies (kcat/Km) up to 3.8 x 103 M-1 s-1, closely match the design models (C RMSDs < 1 [A]), and have folds distinct from natural serine hydrolases. In silico selection of designs based on active site preorganization across the reaction coordinate considerably increased success rates, enabling identification of new catalysts in screens of as few as 20 designs. Our de novo buildup approach provides insight into the geometric determinants of catalysis that complements what can be obtained from structural and mutational studies of native enzymes (in which catalytic group geometry and active site makeup cannot be so systematically varied), and provides a roadmap for the design of industrially relevant serine hydrolases and, more generally, for designing complex enzymes that catalyze multi-step transformations.

biochemistry↗

bioRxiv2024

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

bioRxiv2022

High neutralizing antibody levels against SARS-CoV-2 Omicron after UB-612 booster vaccination

The highly transmissible Omicron variant has caused high rates of breakthrough infections among vaccinated and convalescent individuals. Here, we demonstrate that a booster dose of UB-612 vaccine candidate delivered 7-9 months after primary vaccination increases neutralizing antibody levels by 131-, 61- and 49-fold against ancestral SARS-CoV-2, Omicron BA.1 and BA.2 variants, respectively. Based on the RBD protein binding antibody responses, we estimated a [~]95% efficacy against symptomatic COVID-19 caused by the ancestral strain after a UB-612 booster. Our results support UB-612 vaccine as a potent booster against current and emerging SARS-CoV-2 variants.

microbiology↗

bioRxiv2020

Evaluation of a novel multiplexed assay for determining IgG levels and functional activity to SARS-CoV-2.

BackgroundThe emergence of SARS-CoV-2 has led to the development of new serological assays that could aid in diagnosis and evaluation of seroprevalence to inform an understanding of the burden of COVID-19 disease. Many available tests lack rigorous evaluation and therefore results may be misleading. ObjectivesThe aim of this study was to assess the performance of a novel multiplexed immunoassay for the simultaneous detection of antibodies against SARS-CoV-2 trimeric spike (S), spike receptor binding domain (RBD), spike N terminal domain and nucleocapsid antigen and a novel pseudo-neutralisation assay. MethodsA multiplexed solid-phase chemiluminescence assay (Meso Scale Discovery) was evaluated for the simultaneous detection of IgG binding to four SARS-CoV-2 antigens and the quantification of antibody-induced ACE-2 binding inhibition (pseudo-neutralisation assay). Sensitivity was evaluated with a total of 196 COVID-19 serum samples (169 confirmed PCR positive and 27 anti-nucleocapsid IgG positive) from individuals with mild symptomatic or asymptomatic disease. Specificity was evaluated with 194 control serum samples collected from adults prior to December 2019. ResultsThe specificity and sensitivity of the binding IgG assay was highest for S protein with a specificity of 97.4% and sensitivity of 96.2% for samples taken 14 days and 97.9% for samples taken 21 days following the onset of symptoms. IgG concentration to S and RBD correlated strongly with percentage inhibition measured by the pseudo-neutralisation assay. ConclusionExcellent sensitivity for IgG detection was obtained over 14 days since onset of symptoms for three SARS-CoV-2 antigens (S, RBD and N) in this multiplexed assay which can also measure antibody functionality.

immunology↗

bioRxiv2020

A three-dimensional musculoskeletal model of the dog

Dogs are an interesting object of investigation because of the wide range of body size, body mass, and physique. In the last several years, the number of clinical and biomechanical studies on dog locomotion has increased. However, the relationship between body structure and joint load during locomotion, as well as between joint load and degenerative diseases of the locomotor system (e.g. dysplasia), are not sufficiently understood. In vivo measurements/records of joint forces and loads or deep/small muscles are complex, invasive, and sometimes ethically questionable. The use of detailed musculoskeletal models may help in filling that knowledge gap. We describe here the methods we used to create a detailed musculoskeletal model with 84 degrees of freedom and 134 muscles. Our model has three key-features: Three-dimensionality, scalability, and modularity. We tested the validity of the model by identifying forelimb muscle synergies of a beagle at walk. We used inverse dynamics and static optimization to estimate muscle activations based on experimental data. We identified three muscle synergy groups by using hierarchical clustering. Predicted activation patterns exhibited good agreement with experimental data for most of the forelimb muscles. We expect that our model will speed up the analysis of how body size, physique, agility, and disease influence joint neuronal control and loading in dog locomotion.

bioengineering↗

bioRxiv2019

Global profiling of myristoylation in Toxoplasma gondii reveals key roles for lipidation in CDPK1 and MIC7 function

N-myristoylation is a ubiquitous class of protein lipidation across eukaryotes and N-myristoyl transferase has been proposed as an attractive drug target in several pathogens. Functionally the myristate often primes for subsequent palmitoylation and stable membrane attachment, however, growing evidence also suggests additional regulatory roles for myristoylation on proteins. Here we describe the first global chemoproteomic screening of protein myristoylation in Toxoplasma gondii. Through quantitative mass spectrometry coupled with validated chemoproteomic tools, we identify 65 myristoylated proteins. We report functionally important myristoylation on the key signalling protein CDPK1 and, surprisingly, myristoylation of the microneme protein 7 (MIC7), a predicted type-I-transmembrane protein. We demonstrate that myristoylation of MIC7 is not important for the trafficking to micronemes, but appears to play a role in host cell invasion. This dataset represents a large fraction of the parasites myristoylated proteome and a prerequisite to investigate this modification in Toxoplasma.

microbiology↗

bioRxiv2019

Differential requirements of cyclase associated protein (CAP) for actin turnover during the lytic cycle of Toxoplasma gondii

Toxoplasma gondii contains a limited subset of actin binding proteins. Here we show that ablation of the putative actin regulator cyclase-associated protein (TgCAP) leads to significant defects in some but not all actin dependent processes, including a defect in cell-cell communication, but surprisingly not synchronicity of division. Two CAP isoforms originate from alternative translational start sites and are beneficial for parasite fitness while a single isoform is sufficient for virulence in mice. Examination of the mutant parasites by 3D electron microscopy reveals that loss of CAP results in a defect to form a normal residual body, but all parasites remain connected within the vacuole. This dissociates synchronicity of division and parasite rosetting and reveals that establishment and maintenance of the residual body may be more complex than previously thought. These results highlight the different spatial requirements for actin turnover in Toxoplasma, controlled by a reduced subset of actin binding proteins.

microbiology↗