Biology subjects

Booth, J.

Publications and source records attributed to Booth, J..

8 recordsLinked to original sources

bioRxiv2026

Structure-function studies of HRIKD-{triangleup}KI, a Minimal Kinase Domain of Human Heme-Regulated Inhibitor Kinase

EIF2 kinase heme-regulated inhibitor (HRI) is a novel target for haematological malignancies with modulators reported to trigger cell death via the HRI-eIF2-ATF4 pathway. We report a protocol for producing the minimal kinase domain of full-length human HRI, termed HRIKD-{Delta}KI, where the unstructured 140 amino acid (aa) kinase insert (KI) within HRI kinase domain (HRIKD) is replaced with a 2aa glycine/serine (GS) linker. X-ray crystal structures were determined of apo-HRIKD-{Delta}KI and of its complex with ATP at 2.1 & 2.5 [A] resolution respectively. Both structures display a canonical bi-lobal kinase fold. However, they remain in a non-productive state with a displaced C-helix, disassembled R-spine, and a disordered activation segment hindering the substrate site. Biophysical assays (fluorescence based thermal shift & Synchrotron Radiation Circular Dichroism) demonstrate HRIKD-{Delta}KI retains its functional ligand-binding conformation. All together, these findings define structural and ligand-binding features of HRI to support ongoing drug discovery efforts in blood cancer.

biochemistry↗

bioRxiv2026

Barcoding biology: Chemotype predicts variation in genotype, physiology, and stress response

Predicting biological responses to perturbations such as stress, nutrition, or pharmaceuticals could transform healthcare and biosciences. The task is challenging because complex interactions among many factors interactively drive biological variation, and thereby alter responses. However, metabolism integrates these drivers of variation, suggesting that emergent biological states may be reflected in aggregate chemical states. We define such states as chemotypes and test their predictive utility. Using Fourier-transform infrared (FTIR) spectroscopy coupled with machine learning in Drosophila melanogaster, we show that chemotypes serve as proxies for biological variation driven by sex, genotype, nutrition and age, and - critically - predict among-population variation in stress response. These findings indicate that chemotypes provide a computable and integrative representation of organismal biology, predicting genotype, phenotype, and response to perturbation.

systems biology↗

bioRxiv2025

Continuous evolution of a halogenase enzyme with improved solubility and activity for sustainable bioproduction

Halogenation enhances the stability and function of pharmaceuticals, biomaterials, and industrial compounds. However, chemical halogenation lacks stereoselectivity and requires the use of toxic or expensive chemicals. Although enzymatic halogenation can improve selectivity and reduce environmental impact, current halogenases are inefficient and insoluble, leading to low yields that limit their applications. Here, we develop RebHEvo4, a soluble and highly active tryptophan halogenase, containing 12 mutations that confer 37-fold and 44-fold increases in 7-chloro and 7-bromotryptophan production respectively, in vivo. To create RebHEvo4, we devised an aminoacyl tRNA synthetase based halogenase biosensor and conducted over 500 hours of phage-assisted continuous evolution (PACE). Use of RebHEvo4 in a bioreactor resulted in the production of 2.7 g/L of halogenated tryptophan. When coupled with a downstream enzyme, RebHEvo4 allowed 36-fold increased yields of halogenated tryptamines compared to the wild-type enzyme. Additionally, RebHEvo4 enabled efficient production of genetically encoded antimicrobial halogenated peptides. The efficient, site-specific halogenation by our evolved halogenase will accelerate sustainable biomanufacturing of halogenated drugs.

biochemistry↗

bioRxiv2025

The Balance between B55α and Greatwall expression levels predicts sensitivity to Greatwall inhibition in cancer cells

The Greatwall kinase inhibits PP2A-B55 phosphatase activity during mitosis to stabilise critical Cdk1-driven mitotic phosphorylation. Although Greatwall represents a potential oncogene and prospective therapeutic target, our understanding of cellular and molecular consequences of chemical Greatwall inactivation remains limited. To address this, we introduce C-604, a highly selective Greatwall inhibitor, and characterise both immediate and long-term cellular responses to the chemical attenuation of Greatwall activity. We demonstrate that Greatwall inhibition causes systemic destabilisation of the mitotic phosphoproteome, premature mitotic exit and pleiotropic cellular pathologies. Importantly, we demonstrate that the cellular and molecular abnormalities linked to reduced Greatwall activity are specifically dependent on the B55 isoform rather than other B55 variants, underscoring PP2A-B55 phosphatases as key mediators of cytotoxic effects of Greatwall-targeting agents in human cells. Additionally, we show that sensitivity to Greatwall inhibition varies in different cell line models and that dependency on Greatwall activity reflects the balance between Greatwall and B55 expression levels. Our findings highlight Greatwall dependency as a cell-specific vulnerability and propose the B55-to-Greatwall expression ratio as a predictive biomarker of cellular responses to Greatwall-targeted therapeutics.

cell biology↗

bioRxiv2024

MAGMa: Your Comprehensive Tool for Differential Expression Analysis in Mass-Spectrometry Proteomic Data.

Proteomics, the study of proteins and their functions, plays a vital role in understanding biological processes. In this study, we sought to address the challenges in analyzing complex proteomic datasets, where subtle changes in protein abundance are difficult to detect. Utilizing a newly developed tool, Maximal Aggregation of Good protein signal from Mass spectrometric data (MAGMa), we demonstrated its superior performance in accurately identifying true signals while effectively filtering out noise. Here we show that MAGMa strikes a balance between sensitivity and specificity on benchmarking datasets, offering a robust solution for analyzing various quantitative proteomic datasets. These findings advance the field by providing researchers with a powerful tool to uncover subtle changes in protein abundance, contributing to our understanding of complex biological systems and potentially facilitating the discovery of new therapeutic targets.

bioinformatics↗

bioRxiv2023

A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology

A major goal of cancer biology is to understand the mechanisms underlying tumorigenesis driven by somatically acquired mutations. Two distinct types of computational methodologies have emerged: one focuses on analyzing clustering of mutations within protein sequences and 3D structures, while the other characterizes mutations by leveraging the topology of protein-protein interaction network. Their insights are largely non-overlapping, offering complementary strengths. Here, we established a unified, end-to-end 3D structurally-informed protein interaction network propagation framework, NetFlow3D, that systematically maps the multiscale mechanistic effects of somatic mutations in cancer. The establishment of NetFlow3D hinges upon the Human Protein Structurome, a comprehensive repository we compiled that incorporates the 3D structures of every single protein as well as the binding interfaces of all known protein interactions in humans. NetFlow3D leverages the Structurome to integrate information across atomic, residue, protein and network levels: It conducts 3D clustering of mutations across atomic and residue levels on protein structures to identify potential driver mutations. It then anisotropically propagates their impacts across the protein interaction network, with propagation guided by the specific 3D structural interfaces involved, to identify significantly interconnected network "modules", thereby uncovering key biological processes underlying disease etiology. Applied to 1,038,899 somatic protein-altering mutations in 9,946 TCGA tumors across 33 cancer types, NetFlow3D identified 1,4444 significant 3D clusters throughout the Human Protein Structurome, of which ~55% would not have been found if using only experimentally-determined structures. It then identified 26 significantly interconnected modules that encompass ~8-fold more proteins than applying standard network analyses. NetFlow3D and our pan-cancer results can be accessed from http://netflow3d.yulab.org.

systems biology↗

bioRxiv2022

Dietary Lipid Oxidization Products Alter Growth, Adiposity and Gut Microbial Ecology in Prepubertal Porcine Model

Elevated levels of dietary fats in westernized diets, associated with increased risk of obesity and other chronic diseases, are increasingly consumed by children in the United States. Cooking practices such as high heat frying and increased use of oxidizable sources of fats have introduced high levels of lipid oxidation products (LOPs) into these diets. The effects of these highly reactive dietary compounds on human biology are largely unstudied, especially in the gut where these compounds are likely present at higher concentrations. Given that the gut microbiome can be influenced by dietary components and then in turn have a systemic impact, we investigated the effects of consuming LOPs on gut bacterial and fungal communities and on growth and body composition during the prepubertal period in a porcine model. The presence of LOPs in the high fat diet reduced growth and body fat gain in the model. The gut microbiome was uniquely altered by both high fat and the presence of LOPs, with notable changes in the abundances of Turicibacterales, Spriochaetales, RF39, Lactobacillales and Erysipelotrichales. The mycobiome was dominated by Kazachstania, a porcine specific yeast, which was only minimally influenced by the dietary regimen. Application of machine learning identified dietary fat and LOPs as strong predictors of body fat. The genus Methanobrevibacter was the key microbial predictor of body fat. This study highlights the need for further studies on the biological effects of LOPs which have become ubiquitous in human, livestock and pet diets in developed countries.

physiology↗

bioRxiv2021

Characterizing the genetic basis of trait evolution in the Mexican cavefish

Evolution in response to a change in ecology often coincides with various morphological, physiological, and behavioral traits. For most organisms little is known about the genetic and functional relationship between evolutionarily derived traits, representing a critical gap in our understanding of adaptation The Mexican tetra, Astyanax mexicanus, consists of largely independent populations of fish that inhabit at least 30 caves in Northeast Mexico, and a surface fish population, that inhabits the rivers of Mexico and Southern Texas. The recent application of molecular genetic approaches combined with behavioral phenotyping have established A. mexicanus as a model for studying the evolution of complex traits. Cave populations of A. mexicanus are interfertile with surface populations and have evolved numerous traits including eye degeneration, insomnia, albinism and enhanced mechanosensory function. The interfertility of different populations from the same species provides a unique opportunity to define the genetic relationship between evolved traits and assess the co-evolution of behavioral and morphological traits with one another. To define the relationships between morphological and behavioral traits, we developed a pipeline to test individual fish for multiple traits. This pipeline confirmed differences in locomotor activity, prey capture, and startle reflex between surface and cavefish populations. To measure the relationship between traits, individual F2 hybrid fish were characterized for locomotor behavior, prey-capture behavior, startle reflex and morphological attributes. Analysis revealed an association between body length and slower escape reflex, suggesting a trade-off between increased size and predator avoidance in cavefish. Overall, there were few associations between individual behavioral traits, or behavioral and morphological traits, suggesting independent genetic changes underlie the evolution of behavioral and morphological traits. Taken together, this approach provides a novel system to identify genes that underlie naturally occurring genetic variation in morphological and behavioral traits.

evolutionary biology↗