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Jamieson, A.

Publications and source records attributed to Jamieson, A..

16 recordsLinked to original sources
bioRxiv2026

Cryo-EM Structure of a Triazole alpha-Conotoxin GI Mimetic Bound to the Muscle-Type Nicotinic Acetylcholine Receptor

Disulfide-rich peptides possess exceptional potency and selectivity but are often limited by the instability and synthetic challenges associated with native disulfide bonds. Here, we report the design, synthesis, pharmacological evaluation, and structural characterisation of triazole-based peptidomimetics of the -GI conotoxin, a selective antagonist of the muscle-type nicotinic acetylcholine receptor (nAChR). A series of 1,4- and 1,5-disubstituted triazole analogues were prepared entirely on resin using CuAAC and RuAAC chemistry to replace the native Cys3/13 disulfide bridge. Functional evaluation against human muscle nAChRs revealed that 1,5-triazole analogues retained low-nanomolar potency, with the lead mimetic exhibiting activity comparable to native -GI. Cryo-electron microscopy of the lead compound bound to the muscle-type nAChR provided the first structure of a disulfide-isostere peptidomimetic in complex with a membrane receptor. The structure demonstrates that the 1,5-triazole reproduces the native peptide fold with high fidelity while contributing receptor-facing interactions not available to the native disulfide bridge. Molecular dynamics simulations further revealed conserved hydration networks and similar conformational sampling between the native peptide and lead mimetic. Together, these findings establish triazoles as effective disulfide surrogates and provide a structural framework for the rational design of stabilised conotoxin therapeutics.

biochemistry↗
bioRxiv2026

Honey bee (Apis mellifera) gut microbiome associations with viruses and pesticides across Canadian agroecosystems

The honey bee (Apis mellifera) gut microbiome plays a central role in host health, yet its variation across agricultural landscapes remains poorly resolved. This study investigates how major environmental stressors, particularly pesticide exposure and RNA virus loadings, shape the honey bee gut microbiome in a large-scale field study conducted across Canada, spanning diverse agroecosystems from British Columbia to Quebec. We identify consistent associations between specific bacterial taxa and major RNA viruses, including enrichment of Serratia marcescens with SBV and depletion of Bombella intestini with BQCV. Pesticide exposure is likewise linked to reproducible shifts in key microbial taxa. Together, these findings reveal that interacting stressors jointly shape the bee gut microbiome and enable prediction of microbiome responses in agroecosystems. HighlightsDistinct associations identified between gut bacteria and major bee RNA viruses (BQCV, SBV, LSV, IAPV) Pesticide exposure is linked to reproducible shifts in key microbial taxa Combined virus-pesticide effects form coordinated clusters that predict microbiome variation and specific bacterial responses Integrated modeling demonstrates that environmental stressors can jointly explain microbiome structure beyond crop effects Graphical abstractSchematic overview of potential links between pesticide exposure and RNA virus infection and their effects on the bee gut bacterial community. Solid arrows indicate associations supported by the present study, whereas dashed arrows indicate hypothesized or unresolved interactions. Associations between the presence of specific bee RNA viruses (left) or pesticide residues (right) and changes in the relative abundance of particular gut taxa (pink {uparrow}, increased; blue {downarrow}, decreased). The pesticide subtype is indicated by the icon in the cell (leaf - herbicide, hyphae - fungicide and insect - insecticide). Several bacterial taxa showed reproducible associations with specific viral or pesticide variables, including Bombella intestini, Serratia marcescens, Melissococcus plutonius, Paenibacillus alvei, Apibacter sp. wkB309, and Gilliamella sp. A7. Abbreviations: BQCV Black queen cell virus; LSV, Lake Sinai virus; SBV, Sacbrood virus; IAPV, Israeli acute paralysis virus. (p/n/b) indicate the sample matrix in which the pesticide was detected, namely pollen, nectar, and bee tissue, respectively. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/731697v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@cb92a4org.highwire.dtl.DTLVardef@1087045org.highwire.dtl.DTLVardef@102cabforg.highwire.dtl.DTLVardef@4ce2f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗
bioRxiv2026

Comparative Proteomics Across Tissues and Crop Agroecosystems Reveals Agricultural Stressor Responses in the Western Honey Bee

Maintaining honey bee health in crop production systems is increasingly difficult because worker bees encounter multiple chemical and biological pressures from pesticides and pathogens. How these field-realistic pressures affect molecular physiology across functionally distinct tissues remains poorly understood. Here, we tested whether tissue-resolved proteomics could separate stable tissue-specific patterns from crop-associated molecular changes. To do this, we profiled abdomen, gut, and head proteomes from honey bees collected across four Canadian crop ecosystems over two consecutive years, and integrated these data with pesticide-residue and pathogen-load measurements. Proteomic variation was structured by both tissue identity and crop environment. Tissue-specific proteomic profiles were characterized across samples, whereas crop-associated effects were detected in both years and were stronger in 2021, the second year of the study. Tissue-specific enrichment and network analyses linked the abdomen to lipid catabolism and ubiquitin-proteasome proteostasis, the gut to central carbon metabolism, membrane transport, vesicle trafficking, and cytoskeletal organization, and the head to neurosensory and mitochondrial functions, together with amino-sugar metabolism and vesicle-associated quality-control modules. Among the measured pesticide residues, boscalid was the most reproducible chemical correlate of proteomic variation, with the strongest signal in the gut. Cross-year validation associated boscalid exposure with reduced abundance of gut proteins involved in mitochondrial metabolism, protein quality control, vesicle trafficking, nutrient transport, and biosynthetic pathways. Additionally, integrated proteome-transcriptome-microbiome factor analysis further identified gut-centered components associated with measured stressor variables and linked protein-level variation to coordinated transcriptomic and microbial shifts. Independent-year validation showed that compact crop-associated protein signatures detected in 2020 were also present in 2021. Together, these results show that honey bee tissues maintain stable proteomic identities while showing tissue- and year-specific responses to pesticide and pathogen pressures encountered in crop ecosystems. The gut proteome may specifically provide a sensitive molecular indicator of pesticide-associated perturbation under field conditions.

bioinformatics↗
bioRxiv2026

Inhibition of VP2-mediated entry: a potential antiviral strategy to treat or prevent calicivirus disease

The Caliciviridae include many notable human and animal pathogens, including norovirus and sapovirus, which cause outbreaks of acute gastroenteritis. We previously demonstrated that, following receptor engagement, feline calicivirus (FCV) assembles a portal structure at a unique capsid three-fold axis. This comprises twelve copies of the minor capsid protein VP2 and is essential for genome delivery. We designed a short peptide based on our structure data that occludes the VP2 binding sites on the capsid surface, to prevent assembly of the VP2 portal and thereby halt the viral entry mechanism. Incubation with low micromolar concentrations of the peptide considerably reduced the infectivity of two laboratory strains and four clinical isolates of FCV associated with respiratory or virulent-systemic disease. Cryo-electron microscopy structures of FCV virions complexed with the peptide confirmed that the peptide occupies the VP2 binding site on the major capsid protein VP1, preventing portal assembly and subsequent genome delivery. Our data show that targeting VP2 is a viable antiviral approach to preventing calicivirus infection, with potential for the treatment or prevention of norovirus disease.

microbiology↗
bioRxiv2026

Structures of muscle-type nicotinic acetylcholine receptor with α-conotoxins reveal determinants of receptor-subtype specificity

-Conotoxins (-CTX) are disulfide-rich peptide antagonists with exceptional potency and subtype selectivity across nicotinic acetylcholine receptors (nAChRs), making them promising leads for therapeutic development. The molecular basis of their specificity has remained unresolved for decades, limiting rational drug design. Here, we present the first high-resolution cryo-EM structures of full-length muscle-type nAChR bound to three distinct -CTXs, revealing their precise binding modes at both acetylcholine binding sites. Our integrated approach, combining structural biology, pharmacological profiling, and computational hydration mapping, uncovers conserved pharmacophore features, water-mediated interactions, and subunit-specific determinants that govern potency and selectivity. These findings provide a long-sought molecular framework for -conotoxin recognition and inhibition, addressing a critical gap required to realise the full potential of conotoxins as lead compounds in drug discovery.

molecular biology↗
bioRxiv2025

Resolving phenotyping discordance with SPACEMAP, an integrated machine learning framework

Multiplex imaging technologies have revolutionized our ability to study cellular behavior within the tissue microenvironment. Translating this complex data into meaningful biological insights requires a unified analytical framework. To address this, we developed SPACEMAP (Spatial Phenotyping And Classification with Enhanced Multiplex Analysis Pipeline), a comprehensive Python and Qupath-based platform for multiplex imaging analysis. SPACEMAP integrates image registration, segmentation, artifact removal, tissue and zone classification, spatial feature extraction, and a consolidated phenotyping approach into a single system. A core feature of SPACEMAP is its high-fidelity phenotyping. To evaluate classification performance, we benchmarked our method RESOLVE, against three established approaches, Leiden clustering, Self-Organizing Maps, and SCIMAP revealing substantial disagreement among them. SPACEMAP overcomes this through two complementary workflows: a machine learning model trained on expert-labeled cells, and a consensus classifier that integrates high-confidence cells across methods. Here, we validated SPACEMAP on in-house colorectal cancer samples and a public dataset, demonstrating its robustness.

bioinformatics↗
bioRxiv2025

Inhibition of PfCLK3 a master regulator of malaria parasite RNA-splicing provides the basis for a radical cure for malaria

Emerging resistance to front-line anti-malarials means there is a race to discover new drugs with novel mechanisms of action that remain effective across multiple stages of the parasite life cycle. Previously we reported the malaria protein kinase, PfCLK3, as a target offering a cure, prophylaxis and transmission blocking. The homology between PfCLK3 and human kinases suggested that the mechanism of parasiticidal activity of PfCLK3 inhibitors is disruption of RNA processing. Here, we use whole genome RNA-sequencing to reveal that selective PfCLK3 inhibition extensively affects RNA-splicing with 2039 splice-junctions across 1125 genes mis-spliced in treated wild type parasites compared to controls. The function of mis-spliced transcripts showed that the affected genes were involved in numerous essential parasite processes associated with multiple life cycle stages and revealed transcripts and introns particularly susceptible to inhibition. Our study supports the role of PfCLK3 as an important regulator of spliceosome activity and establishes the distinct mechanism of parasiticidal activity of PfCLK3 inhibitors from current front-line treatments.

molecular biology↗
bioRxiv2025

Biomechanical Phenotyping Reveals Unique Mechanobiological Signatures of Early-Onset Colorectal Cancer

While both incidence and mortality of sporadic average-onset colorectal cancer (AO CRC, above 50 years of age) are in constant decline, sporadic early-onset colorectal cancer (EO CRC, under 50 years of age) is rising rapidly. Yet, the causes behind this rise remain poorly understood. Epidemiological studies indicate that lifestyle and environmental exposures may result in chronic inflammation, which is known to trigger tissue fibrosis. This study tests the hypothesis that fibrotic remodeling and biomechanical stiffening of colorectal tissues represent measurable hallmarks and potential drivers of EO CRC. Using primary human tissues, this work shows that EO CRC is associated with changes in collagen microstructure, increased stiffness and elevated viscosity of primary tumors. Spatial transcriptional profiling and immunostaining reveal pro-fibrotic signatures in stromal cells, alongside enhanced Yes-associated protein (YAP) mechanotransduction and proliferation in epithelial cells of EO CRC tissues. Mechanistically, increasing matrix stiffness in vitro promotes proliferation of epithelial cells in 2D and 3D colorectal cancer models. Together, these findings establish EO CRC as a disease marked by early and widespread biomechanical remodeling, suggesting that a fibrotic and stiffened tissue microenvironment may orchestrate EO CRC tumor initiation.

bioengineering↗
bioRxiv2024

Pollen foraging mediates exposure to dichotomous stressor syndromes in honey bees

Recent declines in the health of honey bee colonies used for crop pollination pose a considerable threat to global food security. Foraging by honey bee workers represents the primary route of exposure to a plethora of toxins and pathogens known to affect bee health, but it remains unclear how foraging preferences impact colony-level patterns of stressor exposure. Resolving this knowledge gap is crucial for enhancing the health of honey bees and the agricultural systems that rely on them for pollination. To address this, we carried out a national-scale experiment encompassing 456 Canadian honey bee colonies to first characterize pollen foraging preferences in relation to major crops, then explore how foraging behaviour influences patterns of stressor exposure. We used a metagenetic approach to quantify honey bee dietary breadth and found that bees display distinct foraging preferences that vary substantially relative to crop type and proximity, and the breadth of foraging interactions can be used to predict the abundance and diversity of stressors a colony is exposed to. Foraging on diverse plant communities was associated with increased exposure to pathogens, while the opposite was associated with increased exposure to xenobiotics. Our work provides the first large-scale empirical evidence that pollen foraging behaviour plays an influential role in determining exposure to dichotomous stressor syndromes in honey bees. Significance StatementInsect-mediated pollination is an important ecological process that is crucial for food production. Managed honey bee colonies are one of the most important insect pollinators, but their health has been under threat from a variety of stressors. Bee workers are primarily exposed to stressors while foraging and understanding how bee foraging preferences are related to exposure risk could provide pivotal information to improve management efforts. Here, we studied honey bee foraging preferences in relation to prominent Canadian crops and across a gradient of modified environments. We found that honey bees show distinct, measurable foraging preferences and that dietary diversity is a strong predictor of the stressors that colonies are exposed to.

ecology↗
bioRxiv2024

Aspartic proteases are abundant and active in acidified wound fluid

Wound healing necessitates a balance between synthesis and breakdown of extracellular matrix components, which is tightly regulated by proteases and their inhibitors. Studies have shown that treatment of poorly healing wounds with acid results in improved healing. In this study, we systematically evaluated changes in proteolytic activity of murine wound fluid upon acidification. A library of 228 synthetic peptides served as reporters of protease activity at pH 7.4, pH 5.0 and pH 3.5. The peptide digestion patterns differed at each pH, revealing that proteases active at pH 7.4 are inactivated at pH 3.5. Notably, aspartic acid proteases emerged as the dominant active enzymes at pH 3.5 and their activity was inhibited by pepstatin. Using a fluorogenic substrate, we quantified aspartic protease activity across varying pH levels and demonstrated optimal activity between pH 3.0 and 3.8. This activity was detectable as early as one day post-injury and persisted over the following ten days. Importantly, human wound fluid exhibited the same activity profile, validating the mouse model as a relevant system for studying acid-mediated wound healing processes.

biochemistry↗
bioRxiv2024

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

Cell segmentation is the foundation of a wide range of microscopy-based biological studies. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation, and computation. However, 3D cell segmentation, requiring dense annotation of 2D slices still poses significant challenges. Manual labeling of 3D cells to train broadly applicable segmentation models is prohibitive. Even in high- contrast images annotation is ambiguous and time-consuming. Here we develop a theory and toolbox, u- Segment3D, for 2D-to-3D segmentation, compatible with any 2D method generating pixel-based instance cell masks. u-Segment3D translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data, as demonstrated on 11 real-life datasets, >70,000 cells, spanning single cells, cell aggregates, and tissue. Moreover, u-Segment3D is competitive with native 3D segmentation, even exceeding when cells are crowded and have complex morphologies.

bioinformatics↗
bioRxiv2024

Machine Learning Assisted Spectral Fingerprinting for Immune Cell Phenotyping

Spectral fingerprinting has emerged as a powerful tool, adept at identifying chemical compounds and deciphering complex interactions within cells and engineered nanomaterials. Using near-infrared (NIR) fluorescence spectral fingerprinting coupled with machine learning techniques, we uncover complex interactions between DNA-functionalized single-walled carbon nanotubes (DNA-SWCNTs) and live macrophage cells, enabling in situ phenotype discrimination. Through the use of Raman microscopy, we showcase statistically higher DNA-SWCNT uptake and a significantly lower defect ratio in M1 macrophages as compared to M2 and naive phenotypes. NIR fluorescence data also indicate that distinctive intra-endosomal environments of these cell types give rise to significant differences in many optical features such as emission peak intensities, center wavelengths, and peak intensity ratios. Such features serve as distinctive markers for identifying different macrophage phenotypes. We further use a support vector machine (SVM) model trained on SWCNT fluorescence data to identify M1 and M2 macrophages, achieving an impressive accuracy of > 95%. Finally, we observe that the stability of DNA-SWCNT complexes, influenced by DNA sequence length, is a crucial consideration for applications such as cell phenotyping or mapping intra-endosomal microenvironments using AI techniques. Our findings suggest that shorter DNA-sequences like GT6 give rise to more improved model accuracy (> 87%) due to increased active interactions of SWCNTs with biomolecules in the endosomal microenvironment. Implications of this research extend to the development of nanomaterial-based platforms for cellular identification, holding promise for potential applications in real time monitoring of in vivo cellular differentiation. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/583608v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@11e2c60org.highwire.dtl.DTLVardef@1f3553forg.highwire.dtl.DTLVardef@61dcb9org.highwire.dtl.DTLVardef@e216b4_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗
bioRxiv2023

Interleukin-1α links peripheral CaV2.2 channel activation to rapid adaptive increases in heat sensitivity in skin

Neurons have the unique capacity to adapt output in response to changes in their environment. Within seconds, sensory nerve endings can become hypersensitive to stimuli in response to potentially damaging events. The underlying behavioral response is well studied, but several of the key signaling molecules that mediate sensory hypersensitivity remain unknown. We previously discovered that peripheral voltage-gated CaV2.2 channels in nerve endings in skin are essential for the rapid, transient increase in sensitivity to heat, but not to mechanical stimuli, that accompanies intradermal capsaicin. Here we report that the cytokine interleukin-1 (IL-1), an alarmin, is necessary and sufficient to trigger rapid heat and mechanical hypersensitivity in skin. Of 20 cytokines screened, only IL-1 was consistently detected in hind paw interstitial fluid in response to intradermal capsaicin and, similar to behavioral sensitivity to heat, IL-1 levels were also dependent on peripheral CaV2.2 channel activity. Neutralizing IL-1 in skin significantly reduced capsaicin-induced changes in hind paw sensitivity to radiant heat and mechanical stimulation. Intradermal IL-1 enhances behavioral responses to stimuli and, in culture, IL-1 enhances the responsiveness of Trpv1-expressing sensory neurons. Together, our data suggest that IL-1 is the key cytokine that underlies rapid and reversible neuroinflammatory responses in skin.

neuroscience↗
bioRxiv2021

Palaeogenomic analysis of black rat (Rattus rattus) reveals multiple European introductions associated with human economic history

The distribution of the black rat (Rattus rattus) has been heavily influenced by its association with humans. The dispersal history of this non-native commensal rodent across Europe, however, remains poorly understood, and different introductions may have occurred during the Roman and medieval periods. Here, in order to reconstruct the population history of European black rats, we generated a de novo genome assembly of the black rat, 67 ancient black rat mitogenomes and 36 ancient nuclear genomes from sites spanning the 1st-17th centuries CE in Europe and North Africa. Analyses of mitochondrial DNA confirm that black rats were introduced into the Mediterranean and Europe from Southwest Asia. Genomic analyses of the ancient rats reveal a population turnover in temperate Europe between the 6th and 10th centuries CE, coincident with an archaeologically attested decline in the black rat population. The near disappearance and re-emergence of black rats in Europe may have been the result of the breakdown of the Roman Empire, the First Plague Pandemic, and/or post-Roman climatic cooling.

evolutionary biology↗
bioRxiv2020

Heritability estimates of antler and body traits in white-tailed deer (Odocoileus virginianus) from genomic-relatedness matrices

Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and SNP data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated GRMs from >10,000 SNPs: dressed body mass and peroneus muscle mass had moderate h2 values of 0.49 and 0.56, respectively. Heritability in male-only antler features ranged from 0.00 to 0.51 and had high standard errors. We explored the influence of minor allele frequency and data completion filters on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management.

genomics↗