Biology subjects

Norman, A.

Publications and source records attributed to Norman, A..

16 recordsLinked to original sources

bioRxiv2026

Layered phage therapy exploits capsule-loss escape and altered antibiotic susceptibility in CG23 hypervirulent Klebsiella pneumoniae

The rise of drug-resistant Klebsiella pneumoniae infections is prompting a re-evaluation of phage therapy as an alternative treatment. Phage therapy has achieved successful outcomes, yet important limitations persist, including the rapid emergence of phage resistance and the time required to source suitable phages. Combining multiple phages into a phage cocktail based on genetic diversity, morphology or distinct infection mechanisms is a common strategy to mitigate resistance. Phage pairing based on these criteria neither mitigates nor delays the emergence of resistance, using CG23 hypervirulent Klebsiella pneumoniae (hvKp) EC0675 as a model. In CG23 Kp strains, resistance arises through disruption of the capsular biosynthetic pathway, leading to capsule impairment and global cross-resistance to all capsule-active phages. Combining phages active against encapsulated wild-type bacteria with those active against capsule-deficient escape mutants can overcome this constraint, improving bacterial suppression in vitro and reducing bacterial burdens across multiple organs in a mouse systemic infection model. In parallel, phage-driven capsule loss increased susceptibility of hvKp EC0675 to selected antibiotics targeting the bacterial envelope or cell wall in vitro. These findings highlight the contribution of capsule-associated resistance to phage cross-resistance in the CG23 Kp strains examined, and support further evaluation of phage combinations targeting both wild-type bacteria and resistant derivatives, including their use alongside selected antibiotics, informing future clinical translation.

microbiology↗

bioRxiv2026

A searchable metadata network graph for microbiome metabolomics

Establishing the biological context of microbial metabolites remains a major challenge. We present microbiomeMASST, a metadata-driven network graph that maps metabolites across 467 available datasets with 144,424 mass spectrometry files from humans, animals, and microbial culture systems. MicrobiomeMASST integrates monocultures, synthetic communities, and host-associated samples across multiple body sites and plants. MS/MS spectra can be queried to trace occurrence across hosts, experimental conditions, and interventions, enabling cross-study integration. We demonstrate this framework by contextualizing microbial-conjugated bile acids and interrogating microbiome-mediated drug metabolism. Screening gut bacteria revealed deprolylation of the angiotensin-converting enzyme (ACE) inhibitor prodrug enalapril. Using microbiomeMASST, we traced this metabolite across human cohorts, microbial isolates, environmental samples, and in Gorilla gorilla. Structural modeling and enzymatic assays showed that microbial deprolylation abolishes ACE inhibition, thereby inactivating its therapeutic effect. Together, microbiomeMASST links MS/MS spectra to biological context, converting isolated observations into an interpretable microbiome map for cross-study analysis.

biochemistry↗

bioRxiv2025

Peptide molecular glues select between BET paralogues by exploiting allosteric sites and conformational dynamics

Achieving selective target inhibition is critical for minimising drug side effects. This can be especially challenging when targeting individual members of protein families with high sequence similarity. A well-recognised example is the Bromodomain and Extraterminal domain (BET) family of proteins. Chemical inhibition of the acetyllysine (AcK)-binding bromodomains (BDs) of BET proteins has shown considerable promise in a range of disease models. However, despite over a decade of medicinal chemistry efforts, it has proven challenging to develop BET BD inhibitors that exhibit high selectivity between BET family paralogues. Cyclic peptides are versatile scaffolds for therapeutic development and often exhibit high selectivity and affinity for their targets. To explore their potential as selective BET BD inhibitors, we have used mRNA display to identify cyclic peptide ligands for the N-terminal BD of BRD2 and BRD4. The structurally diverse cyclic peptides enriched from the selections boast superior selectivity and affinity to previously developed inhibitors. Most strikingly, we isolated cyclic peptides with [~]1000-fold higher affinity for their target BD over the paralogous BDs, far surpassing selectivities reported to date. Our biochemical and structural data suggest that paralogue-selective cyclic peptides act as molecular glues, exploiting both subtle sequence differences at locations far from the AcK-binding pocket and differences in conformational dynamics between BET BD paralogues to achieve this unprecedented level of specificity. This work provides a blueprint for the development of new classes of selective BET inhibitors and, more generally, underscores the potential of exploiting protein dynamics in the design of selective ligands.

biochemistry↗

bioRxiv2024

ProteinWeaver: A Webtool to Visualize Ontology-Annotated Protein Networks

Molecular interaction networks are a vital tool for studying biological systems. While many tools exist that visualize a protein or a pathway within a network, no tool provides the ability for a researcher to consider a proteins position in a network in the context of a specific biological process or pathway. We developed ProteinWeaver, a web-based tool designed to visualize and analyze non-human protein interaction networks by integrating known biological functions. ProteinWeaver provides users with an intuitive interface to situate a user-specified protein in a user-provided biological context (as a Gene Ontology term) in five model organisms. Protein-Weaver also reports the presence of physical and regulatory network motifs within the queried subnetwork and statistics about the proteins distance to the biological process or pathway within the network. These insights can help researchers generate testable hypotheses about the proteins potential role in the process or pathway under study. Two cell biology case studies demonstrate ProteinWeavers potential to generate hypotheses from the queried subnetworks. ProteinWeaver is available at https://proteinweaver.reedcompbio.org/.

systems biology↗

bioRxiv2024

Incorporating gene expression and environment improves genomic prediction of wheat traits

The adoption of novel molecular strategies such as genomic selection (GS) in crop breeding have been key to maintaining rates of genetic gain through increased efficiency and shortening the cycle of evaluation relative to conventional selection. In the search for improved methodologies that incorporate novel sources of variation for the assessment of genetic merit, GS remains a focus of crop breeding research globally. Here we explored the role transcrip-tome data could play in enhancing GS using wheat as a test case. Across 286 wheat lines, we integrated phenotype and multi-omic data from controlled environment and field experiments including ca. 40K single nucleotide polymorphisms (SNP), abundance data for ca. 50K transcripts as well as meta-data (e.g. categorical environments) predicted individual genetic merit for two agronomic traits, flowering time and height. We combined phenotype and multi-omic data from both controlled environments and field experiments. This included ca. 40K single nucleotide polymorphisms (SNPs), ca. 50K transcript abundance data, and metadata (such as categorical environmental conditions). Using this integrated data, we predicted individual genetic merit for two agronomic traits: flowering time and height. We evaluated the performance of different model scenarios based on linear (GBLUP) and Gaussian/nonlinear (RKHS) regression in the Bayesian analytical frame-work. These models explored the relative contributions of different combinations of explanatory variables; additive genomic (G), transcriptomic (T) and environment (E), with and without considering non-additive epistasis and the GxE random effects. In controlled environments, where traits were measured under contrasting daylength regimes (long and short days), transcriptome abundance outperformed other explanatory variables when considered independently, while the model combining SNP, environment and G x E marginally outperformed the transcriptome. The best performing model for prediction of both flowering and height combined all data types, G x E and epistasis, where the GBLUP framework showed slightly better performance overall compared with RKHS across all tests. Under field conditions, we similarly found that models combining all variables were superior, with the GBLUP and RKSH methods performing equally well. However, the relative contribution of the transcriptome was reduced. Our results show there is a predictive advantage to direct inclusion of the transcriptome for genomic evaluation in wheat breeding. However, the complexity and cost of generating large scale transcriptome data are likely to limit its feasibility for commercial breeding. We demonstrate that combining less costly environmental covariates with conventional genomic data provide a practical alternative with similar gains to the transcriptome when environments are well characterised. HighlightsO_LIIncorporating transcriptome and environment in genomic prediction; C_LIO_LIModel comparisons and Bayesian inference. C_LIO_LIDifferential random effects of transcriptome, SNP and environment. C_LI

genomics↗

bioRxiv2024

OzWheat: a genome-to-phenome platform to resolve complex traits for wheat pre-breeding and research.

For over a century, Australian wheat breeders have successfully adapted wheat to a broad range of climatic conditions and crop management practices. The OzWheat genome-to-phenome (G2P) platform was established to capture this breeding history and explore traits, genes, and their interactions with the environment to enable ongoing research and deliver targets for wheat improvement. A panel of 285 cultivars and landraces were chosen through knowledge of breeding pedigrees to represent both global diversity and the historic flow of genetic variation over more than 100 years of selective breeding in Australia. Genetic characterisation of the panel included identification of genome-wide sequence variants and gene expression profiling across environments. Important traits for adaptation (flowering time and plant height) were assayed in controlled environments and at multiple field sites and years, with genome-wide association analyses (GWAS) using linear mixed models detecting both known and novel loci. Here, we report establishment of the OzWheat G2P platform as a powerful tool to integrate wheat genomes and phenomes and demonstrate its use to identify candidate genes and understand gene by environment interactions. This provides the wheat research and breeding community a new resource to support future cultivar development.

genomics↗

bioRxiv2023

Airborne eDNA captures three decades of ecosystem biodiversity

Conserving biodiversity is a global imperative, yet our capacity to quantify and understand species occurrences has been limited. To help address this challenge, we develop a novel monitoring approach based on deep sequencing of airborne eDNA. When applied to a 34-year archive of weekly filters from an aerosol sampling station in northern Sweden, our methods enabled robust detection of over 2,700 genera across all domains of life and estimates of eDNA catchment areas. Reconstructed time series revealed regional biodiversity declines consistent with contemporary, large-scale transformations of forest composition and structure. Our results show airborne eDNA can reliably monitor biodiversity and underscore the immense latent potential in the thousands of aerosol monitoring stations deployed worldwide. One-Sentence SummaryDNA captured from air reveals organisms from all domains of life and their long-term trends.

ecology↗

bioRxiv2023

mRNA display reveals a class of high-affinity bromodomain-binding motifs that are not found in the human proteome

Bromodomains regulate gene expression by recognizing protein motifs containing acetyllysine. Although originally characterized as histone-binding proteins, it has since become clear that these domains interact with other acetylated proteins, perhaps most prominently transcription factors. The likely transient nature and low stoichiometry of such modifications, however, has made it challenging to fully define the interactome of any given bromodomain. To begin to address this knowledge gap in an unbiased manner, we carried out mRNA display screens against a bromodomain - the N-terminal bromodomain of BRD3 - using peptide libraries that contained either one or two acetyllysine residues. We discovered peptides with very strong consensus sequences and with affinities that are significantly higher than typical bromodomain-peptide interactions. X-ray crystal structures also revealed modes of binding that have not been seen with natural ligands. Intriguingly, however, our selected sequences are not found in the human proteome, perhaps suggesting that strong binders to bromodomains might have been selected against.

biochemistry↗

bioRxiv2022

Discovery and characterization of cyclic peptides selective for the C-terminal bromodomains of BET family proteins

SUMMARYDNA encoded cyclic peptide libraries offer unique opportunities to discover high-potency, high-specificity ligands directed against a target protein. We set out to explore the potential for such libraries to provide ligands that can distinguish between bromodomains from the closely related paralogues of the Bromodomain and ExtraTerminal domain (BET) family of epigenetic regulators. Analysis of peptides isolated from a screen against the C-terminal bromodomain of family member BRD2, together with new peptides discovered in previous screens against the corresponding domain from BRD3 and BRD4, reveals peptides with nanomolar and subnanomolar affinities. X-ray crystal structures of several of these bromodomain-peptide complexes reveal diverse structures and binding modes, which nevertheless display several conserved binding features. A subset of the peptides demonstrates significant paralogue-level specificity, though structural analysis does not reveal clear physicochemical explanations for this specificity. Our data demonstrate the power of cyclic peptides to discriminate between highly similar proteins with high potency and hint that differences in conformational dynamics between BET-family bromodomains might modulate binding affinities amongst family members for particular ligands.

biochemistry↗

bioRxiv2022

Cross-linking mass spectrometry discovers, evaluates, and validates the experimental and predicted structural proteome

Significant recent advances in structural biology, particularly in the field of cryo-electron microscopy, have dramatically expanded our ability to create structural models of proteins and protein complexes. However, many proteins remain refractory to these approaches because of their low abundance, low stability or - in the case of complexes - simply not having yet been analysed. Here, we demonstrate the power of combining cross-linking mass spectrometry (XL-MS) with artificial intelligence-based structure prediction to discover and experimentally substantiate models for protein and protein complex structures at proteome scale. We present the deepest XL-MS dataset to date, describing 28,910 unique residue pairs captured across 4,084 unique human proteins and 2,110 unique protein-protein interactions. We show that integrative models of complexes driven by AlphaFold Multimer and inspired and corroborated by the XL-MS data offer new opportunities to deeply mine the structural proteome and interactome and reveal new mechanisms underlying protein structure and function.

biochemistry↗

bioRxiv2022

A broad-spectrum macrocyclic peptide inhibitor of the SARS-CoV-2 spike protein

The ongoing COVID-19 pandemic has had great societal and health consequences. Despite the availability of vaccines, infection rates remain high due to immune evasive Omicron sublineages. Broad-spectrum antivirals are needed to safeguard against emerging variants and future pandemics. We used mRNA display under a reprogrammed genetic code to find a spike-targeting macrocyclic peptide that inhibits SARS-CoV-2 Wuhan strain infection and pseudoviruses containing spike proteins of SARS-CoV-2 variants or related sarbecoviruses. Structural and bioinformatic analyses reveal a conserved binding pocket between the receptor binding domain, N-terminal domain and S2 region, distal to the ACE2 receptor-interaction site. Our data reveal a hitherto unexplored site of vulnerability in sarbecoviruses that peptides and potentially other drug-like molecules can target. Significance statementThis study reports on the discovery of a macrocyclic peptide that is able to inhibit SARS-CoV-2 infection by exploiting a new vulnerable site in the spike glycoprotein. This region is highly conserved across SARS-CoV-2 variants and the subgenus sarbecovirus. Due to the inaccessability and mutational contraint of this site, it is anticipated to be resistant to the development of resistance through antibody selective pressure. In addition to the discovery of a new molecule for development of potential new peptide or biomolecule therapeutics, the discovery of this broadly active conserved site can also stimulate a new direction of drug development, which together may prevent future outbreaks of related viruses.

biochemistry↗

bioRxiv2022

Neonate personality affects early-life resource acquisition in a large social mammal

Current debate in the field of animal personality revolves around whether personality is reflecting individual differences in resource allocation or acquisition. Despite the large body of literature, the proximate relationships between personality, resource allocation, and acquisition are still unclear, especially during early stages of development. Here we studied how among-individual differences in behaviour develop over the first 6 months of life, and their potential association with resource acquisition in a free-ranging population of fallow deer (Dama dama). We related proxies of neonate personality - i.e. neonate physiological (heart rate) and behavioural (latency to leave at release) anti-predator responses to human handling - to the proportion of time fawns allocated to scanning during their first summer and autumn of life. We then investigated whether there was a trade-off between scanning time and foraging time in these juveniles, and how it developed over their first 6 months of life. We found that neonates with longer latencies at capture (i.e. risk-takers) allocated less time scanning their environment, but that this relationship was only present when fawns were 3-6 months old during autumn, but not when fawns were only 1-2 months old during summer. We also found that time spent scanning was negatively related to time spent foraging - a relationship rarely tested in juveniles of large mammals - and that this relationship becomes stronger over time, as fawns gradually switch from a nutrition rich (milk) to a nutrition poor (grass) diet. Our results highlight a potential mechanistic pathway in which neonate personality may drive differences in early-life resource acquisition, through allocation, of a large social mammal.

ecology↗

bioRxiv2021

Dichotomous Feedback: A Signal Sequestration-based Feedback Mechanism for Biocontroller Design

We introduce a new design framework for implementing negative feedback regulation in Synthetic Biology, which we term dichotomous feedback. Our approach is different from current methods, in that it sequesters existing fluxes in the process to be controlled, and in this way takes advantage of the processs architecture to design the control law. This signal sequestration mechanism appears in many natural biological systems and can potentially be easier to realise than molecular sequestration and other comparison motifs that are nowadays common in biomolecular feedback control design. The loop is closed by linking the strength of signal sequestration to the process output. Our feedback regulation mechanism is motivated by two-component signalling systems, where we introduce a second response regulator competing with the natural response regulator thus sequestering kinase activity. Here, dichotomous feedback is established by increasing the concentration of the second response regulator as the level of the output of the natural process increases. Extensive analysis demonstrates how this type of feedback shapes the signal response, attenuates intrinsic noise while increasing robustness and reducing crosstalk.

synthetic biology↗

bioRxiv2021

A Precision Medicine Approach to Metabolic Therapy for Breast Cancer in Mice

Increasing evidence highlights the possibility for approaches targeting metabolism as potential adjuvants to cancer therapy. Sodium-glucose transport protein 2 (SGLT2) inhibitors are the newest class of antihyperglycemic therapies, and have recently been highlighted as a novel therapeutic approach to breast cancer. To our knowledge, however, SGLT2 inhibitors have not been applied in the neoadjuvant setting as a precision medicine approach to combining metabolic therapy with standard of care therapy for this devastating disease. In this study we combine the SGLT2 inhibitor dapagliflozin with paclitaxel chemotherapy in both lean and obese mice. We show that dapagliflozin enhances the efficacy of paclitaxel, reducing tumor glucose uptake and prolonging survival in an insulin-dependent manner in some but not all breast tumors. Our data find a genetic signature for breast tumors most likely to respond to dapagliflozin in combination with paclitaxel. Tumors driven by mutations upstream of canonical insulin signaling pathways are likely to respond to such treatment, whereas tumors driven by mutations downstream of canonical insulin signaling are not. These data demonstrate that dapagliflozin enhances the response to chemotherapy in mice with breast cancer and suggest that breast cancer patients with driver mutations upstream of canonical insulin signaling may be most likely to benefit from this neoadjuvant approach. A clinical trial is currently in preparation, with an application recently submitted for Yale Human Investigations Committee approval, to test this hypothesis in breast cancer patients. One Sentence SummaryWe identify a driver mutation signature by which glucose-wasting metabolic therapy (dapagliflozin) enhances the efficacy of chemotherapy in mice with breast cancer.

cancer biology↗

bioRxiv2021

Pore structure controls stability and molecular flux in engineered protein cages

Protein cages are a common architectural motif used by living organisms to compartmentalize and control biochemical reactions. While engineered protein cages have recently been featured in the construction of nanoreactors and synthetic organelles, relatively little is known about the underlying molecular parameters that govern cage stability and molecular flux through their pores. In this work, we systematically designed a 24-member library of protein cage variants based on the T. maritima encapsulin, each featuring pores of different size and charge. Twelve encapsulin pore variants were successfully assembled and purified, including eight designs with exceptional and prolonged thermal stability. While pores lined with negatively charged residues resulted in more robust assemblies than their corresponding positively charged variants, we were able to form stable assemblies covering a full range of pore sizes and charges, as observed in seven new cryo-EM structures of pore variants elucidated at resolutions between 2.5-3.6 [A]. Alongside these structures, molecular dynamics simulations and stopped flow kinetics experiments reveal the importance of considering both pore size and surface charge, together with flexibility and rate determining steps, when designing protein cages for controlling molecular flux. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC="FIGDIR/small/428512v3_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@725e76org.highwire.dtl.DTLVardef@97a497org.highwire.dtl.DTLVardef@1b6ea1forg.highwire.dtl.DTLVardef@1c4d17f_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2020

Discovery of Cyclic Peptide Ligands to the SARS-CoV-2 Spike Protein using mRNA Display

The COVID-19 pandemic, caused by SARS-CoV-2, has led to substantial morbidity, mortality and disruption globally. Cellular entry of SARS-CoV-2 is mediated by the viral spike protein and affinity ligands to this surface protein have the potential for applications as antivirals and diagnostic reagents. Here, we describe the affinity selection of cyclic peptide ligands to the SARS-CoV-2 spike protein receptor binding domain (RBD) from three distinct libraries (in excess of a trillion molecules each) by mRNA display. We identified six high affinity molecules with dissociation constants (KD) in the nanomolar range (15-550 nM) to the RBD. The highest affinity ligand could be used as an affinity reagent to detect spike protein in solution by ELISA, and the co-crystal structure of this molecule bound to the RBD demonstrated that it binds to a cryptic binding site, displacing a {beta}-strand near the C-terminus. Our findings provide key mechanistic insight into the binding of peptide ligands to the SARS-CoV-2 spike RBD and the ligands discovered in this work may find future use as reagents for diagnostic applications.

biochemistry↗