Biology subjects

Quinn, A.

Publications and source records attributed to Quinn, A..

At least 19 recordsLinked to original sources

bioRxiv2025

Engineered symbiont biosensor maps micron-scale sugar gradients in the honeybee gut

The honeybee gut microbiota plays a key role in shaping host health and susceptibility to disease. Yet, the nutrient environment it experiences within the gut remains poorly characterized. In particular, little is known about the spatial distribution of nutrients across this community, as resolving such fine gradients in vivo has been technically challenging. Here, we engineer the native honeybee symbiont Snodgrassella alvi as a living biosensor to quantify the bioavailability of the dietary sugar arabinose within the gut. By expanding the genetic toolkit for S. alvi through chromosomal integration of high-burden genes and a suite of low-strength promoters, we achieve stable multi-gene expression without compromising host colonization. The resulting biosensor generates a specific, dose-dependent response to arabinose in situ, enabling visualization of sugar gradients across gut-associated bacterial biofilms at micron-scale resolution. Using this system, we show that diet-derived arabinose distribution is highly heterogeneous and can be influenced by the metabolic activity of co-colonizing Gilliamella species. These findings highlight how diet composition and microbial specialization generate fine-scale microenvironments within the gut. More broadly, this work further establishes S. alvi as a genetically tractable platform for in situ probing of microbial metabolism and nutrient distribution.

synthetic biology↗

bioRxiv2025

Cardiac myofibril networks induce shear stress

Myofibril arrangement is critical to cardiac muscle function in health and disease. Historically, analysis of the impact of myofibril organisation on force and cell contraction has relied on the assumption of uniaxial arrays. However, improvements in imaging indicate that myofibrils form complex networks, though how these networks modulate force has yet to be explored. Here, morphological analysis of sheep left-ventricular cardiomyocytes is utilised to inform a non-linear finite element model of cell contraction. Analysis of deep learning segmentations of Z-Discs demonstrate that myofibrils are oriented about the major axis (mean = 0.03{degrees}) but deviate locally by up to 30{degrees} (standard deviation = 6.56{degrees}). Simulations produce unique deformations for geometries informed by myofibril orientations, displaying internal rotation and off-axis deformations. Moreover, anisotropy generates shear stresses distinct from the uniaxial case, demonstrating spatial relationships that balance shear across the cell. These findings highlight the impact of myofibril networks on forces during cell contraction.

biophysics↗

bioRxiv2025

Rhythmic light stimulation elicits multiple concurrent neural responses that separably shape human perception

Rhythmic light stimulation offers solutions to innumerable cognitive and neurological disorders. However, like any neuromodulatory technique, responses to rhythmic light stimulation are highly variable, producing challenges in replicating lab-based studies and translating findings to the clinic. Across three MEG/EEG experiments, we show that this variability can, in part, be attributed to rhythmic light stimulation eliciting multiple, coexisting neural responses which have separable impacts on cognition. Specifically, we find that rhythmic light stimulation produces distinct neural responses at the fundamental (f) and second harmonic (2f) frequencies, and that these responses are differentially shaped by endogenous oscillatory dynamics that vary across participants. Importantly, these responses separably contribute to perception, with harmonic gamma-band responses supporting the representation of stimulus-specific information, and the phase of harmonic alpha-band responses causally contributing to near-threshold visual perception. We reproduce these effects across datasets, paradigms, and oscillatory bands, suggesting that the multiplex oscillatory responses elicited by rhythmic light stimulation are a robust and pervasive phenomenon. We propose that the complexity of neural responses to rhythmic stimulation can explain why there is substantial variability between studies using these techniques, and that understanding these complex responses may help advance neuromodulatory technologies for both fundamental and clinical neuroscience. Supplementary MaterialAll supplementary material can be found at the end of this document.

neuroscience↗

bioRxiv2025

In vivo genome-wide CRISPRi-Seq in Streptococcus pneumoniae reveals host-adaptive pathways essential for meningitis and identifies new therapeutic targets

Streptococcus pneumoniae is an important human pathogen that causes invasive diseases and remains the leading cause of bacterial meningitis. However, the bacterial determinants required for survival within the central nervous system (CNS) are poorly understood. Here, we performed a genome-wide CRISPR interference screen (CRISPRi-Seq) in an in vivo zebrafish model to systematically map pneumococcal fitness determinants during meningitis. Using this approach, we investigated essential and non-essential genes contributing to the pathogenesis of pneumococcal meningitis. The screen identified 244 loci whose repression significantly reduced bacterial fitness in vivo, representing pathways involved in virulence, metabolism, cell-envelope biogenesis, translation, and stress adaptation. Comparative analysis with in vitro datasets showed that metabolic genes such as purA, proABC, thrC, glyA, and manLMN, as well as those involved in peptidoglycan and capsule biosynthesis (pbp3, cps2 operon) and oxidative stress response (nox, dpr), become selectively more essential in vivo. Functional validation confirmed that these pathways are critical for virulence, nutrient-dependent growth, and oxidative stress response during meningitis. Untargeted metabolomics of infected zebrafish corroborate several observed bacterial genetic sensitivities in the CNS with altered levels of key nutrients such as glucose and 4-aminobenzoic acid. Integration of the CRISPRi-Seq dataset with antibiotic-target annotations revealed both established and previously unrecognised vulnerabilities, including aminoacyl-tRNA synthetases such as leucyl-tRNA synthetase (LeuRS), whose inhibition by the benzoxaborole epetraborole improved host survival, highlighting its potential as a new therapeutic strategy for multidrug-resistant (MDR) S. pneumoniae. Together, these findings demonstrate the power of in vivo CRISPRi-Seq to define the pneumococcal essentialome under physiological conditions and reveal that metabolic adaptation, cell-envelope maintenance, and the oxidative stress response are central to bacterial survival in the CNS. This fitness map advances our understanding of pneumococcal adaptation in the CNS and identifies promising targets for developing therapies against S. pneumoniae.

microbiology↗

bioRxiv2025

Microbes release lower-value metabolites at higher rates

Microbial interactions are shaped by the exchange of metabolites, ranging from intermediates in central carbon metabolism to amino acids, vitamins and fermentation by-products. While specific metabolic processes such as overflow metabolism are well documented, a general principle explaining the chemical diversity of metabolite release and the variation in individual release rates remains elusive. Here, using a combination of computational and experimental approaches on seven different microbes, we show that release rates are negatively correlated with the value of metabolites, and that this relationship explains more variability in release rates than other frequently associated factors. By measuring metabolite release from 67 E. coli mutants lacking individual transport genes, we find that transporters both cause and counteract net metabolite release. These findings suggest that metabolite release constitutes a fitness cost that microbes have evolved to reduce, while revealing the underlying transport mechanism. This unifying explanation reshapes our understanding of how microbial interactions emerge and persist.

microbiology↗

bioRxiv2024

Optimizing Genome Editing in Bovine Cells: A Comparative Study of Cas9 Variants and CRISPR Delivery Methods

To assist in the establishment of an efficient CRISPR/Cas9 gene editing workflow in bovine cells, we compared the efficiency of four Streptococcus pyogenes Cas9 (SpCas9) nuclease variants (produced in-house or commercially) and two different Cas9/sgRNA ribonucleoprotein (RNP) delivery methods applied to Madin-Darby bovine kidney (MDBK) cells (Bos taurus). We targeted three genes for simple sequence deletion or modification via a single-stranded oligodeoxynucleotide donor template: the testis-determining gene Sry (sex-determining region on Y chromosome), germ cell-specific gene Nanos2 (nanos C2HC-type zinc finger 2) and PRLR (prolactin receptor). RNPs and donor templates were delivered into cells via lipofectamine CRISPRMAX transfection or Neon electroporation. The efficiency of gene editing was determined by target-specific PCR genotyping, real-time PCR assays and next generation sequencing analyses. When targeting Sry, the commercial Alt-R High-Fidelity (HiFi) SpCas9 nuclease exhibited the highest deletion efficiency, followed by the in-house generated Sniper2L, HiFi SpCas9 and wild-type SpCas9. Notably, for PRLR and Nanos2, Sniper2L induced comparable editing outcomes to Alt-R HiFi SpCas9. The two delivery methods, lipofectamine CRISPRMAX transfection and Neon electroporation, demonstrated similar efficiency (60% to 83%) in producing indels in all three target genes. However, Neon electroporation (5.5% to 11%) was superior to CRISPRMAX lipofection (1.5% to 4.8%) at inducing target-specific sequence knock-ins. Strategies to inhibit NHEJ repair and/or enhance HDR may be necessary to improve HDR efficiency in these bovine cells. These findings provide valuable insights for improving gene editing outcomes in bovines and may assist in accelerating the widespread application of genome editing technology in large animals.

molecular biology↗

bioRxiv2023

Gut microbiota influences foraging onset without affecting division of labor and associated physiological hallmarks in honeybees

Gut microbes can impact cognition and behavior, but whether they regulate division of labor in animal societies is unknown. We addressed this question using honeybees since they exhibit division of labor between nurses and foragers and because their gut microbiota can be manipulated. Using automated behavioral tracking and controlling for co-housing effects, we show that gut microbes influence the age at which bees start foraging but have no effects on the time spent in a foraging area and number of foraging trips. Moreover, the gut microbiota did not influence hallmarks of behavioral maturation such as body weight, cuticular hydrocarbon (CHC) profile, hypopharyngeal gland size, and the proportion of bees maturing into foragers. Overall, this study shows that the honeybee gut microbiota does not affect division of labor but rather plays an important function in controlling the onset of bee foraging.

evolutionary biology↗

bioRxiv2023

Foraging on host synthesized metabolites enables the bacterial symbiont Snodgrassella alvi to colonize the honey bee gut

Dietary nutrients and microbial cross-feeding allow diverse bacteria to colonize the animal gut. Less is known about the role of host-derived nutrients in enabling gut bacterial colonization. We examined metabolic interactions within the evolutionary ancient symbiosis between the honey bee (Apis mellifera) and the core gut microbiota member Snodgrassella alvi. This Betaproteobacteria is incapable of metabolizing saccharides, yet colonizes the honey bee gut in the presence of only a sugar diet. Using comparative metabolomics, 13C tracers, and Nanoscale secondary ion mass spectrometry (NanoSIMS), we show in vivo that S. alvi grows on host-derived organic acids, including citrate, glycerate and 3-hydroxy-3-methylglutarate which are actively secreted by the host into the gut lumen. S. alvi additionally modulates tryptophan metabolism in the gut by converting kynurenine to anthranilate. These results suggest that S. alvi is adapted to a specific metabolic niche in the gut that depends on host-derived nutritional resources.

microbiology↗

bioRxiv2022

Determinants of Viscoelasticity and Flow Activation Energy in Biomolecular Condensates

The form and function of biomolecular condensates, which are phase-separated intracellular granules of proteins and RNAs, are regulated by their material and dynamical properties. Emerging reports suggest that biomolecular condensates are viscoelastic network fluids, and the primary sequence and structure of the constituent biopolymers govern their bulk fluid phase properties. Here, we employ a multi-parametric approach to dissect the molecular determinants of condensate viscoelasticity by studying a series of condensates formed by engineered multivalent arginine-rich polypeptides and single-stranded DNA. By measuring the terminal relaxation time of the condensate network through optical tweezer-based microrheology and the activation energy of viscous flow through temperature-controlled video particle tracking, we show that condensate viscoelasticity is controlled by two distinct factors - sequence-encoded inter-chain interactions of associative polymers and entropic factors emerging from their intrinsic polymer properties such as the chain length. The biomolecular diffusion in the dense phase shows a strong dependence on the flow activation energy, indicating that the intra-condensate transport properties are primarily reaction-dominant. These results provide a glimpse of the multifaceted control of viscoelasticity and transport properties within biomolecular condensates. Flow activation energy measurement of single and multicomponent condensates by thermo-rheology provides a direct route to quantify inter-chain interactions in the dense phase and dissect the roles of chain entropy and valence in dictating the viscoelastic behavior of biomolecular condensates.

biophysics↗

bioRxiv2022

Mixtures of large-scale dynamic functional brain network modes

Accurate temporal modelling of functional brain networks is essential in the quest for understanding how such networks facilitate cognition. Researchers are beginning to adopt time-varying analyses for electrophysiological data that capture highly dynamic processes on the order of milliseconds. Typically, these approaches, such as clustering of functional connectivity profiles and Hidden Markov Modelling (HMM), assume mutual exclusivity of networks over time. Whilst a powerful constraint, this assumption may be compromising the ability of these approaches to describe the data effectively. Here, we propose a new generative model for functional connectivity as a time-varying linear mixture of spatially distributed statistical "modes". The temporal evolution of this mixture is governed by a recurrent neural network, which enables the model to generate data with a rich temporal structure. We use a Bayesian framework known as amortised variational inference to learn model parameters from observed data. We call the approach DyNeMo (for Dynamic Network Modes), and show using simulations it outperforms the HMM when the assumption of mutual exclusivity is violated. In resting-state MEG, DyNeMo reveals a mixture of modes that activate on fast time scales of 100-150 ms, which is similar to state lifetimes found using an HMM. In task MEG data, DyNeMo finds modes with plausible, task-dependent evoked responses without any knowledge of the task timings. Overall, DyNeMo provides decompositions that are an approximate remapping of the HMMs while showing improvements in overall explanatory power. However, the magnitude of the improvements suggests that the HMMs assumption of mutual exclusivity can be reasonable in practice. Nonetheless, DyNeMo provides a flexible framework for implementing and assessing future modelling developments.

neuroscience↗

bioRxiv2022

The gut microbiota affects the social network of honeybees

The gut microbiota influences animal neurophysiology and behavior but has not previously been documented to affect emergent group-level behaviors. Here we combine gut microbiota manipulation with automated behavioral tracking of honeybee sub-colonies to show that the microbiota increases the rate and specialization of social interactions. Microbiota colonization was associated with higher abundances of one third of metabolites detected in the brain, including several amino acids, and a subset of these metabolites were significant predictors of social interactions. Colonization also affected brain transcriptional processes related to amino acid metabolism and epigenetic modification in a brain region involved in sensory perception. These results demonstrate that the gut microbiota modulates the emergent colony social network of honeybees, likely via changes in chromatin accessibility and amino acid biosynthesis.

animal behavior and cognition↗

bioRxiv2021

Polyclonal pathogen populations accelerate the evolution of antibiotic resistance in patients

Antibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that pulmonary populations of the opportunistic pathogen P. aeruginosa are often polyclonal. Crucially, resistance evolves rapidly in patients colonized by polyclonal populations through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by monoclonal populations due to selection for novel resistance mutations. However, strong trade-offs between resistance and fitness occur in polyclonal populations that can drive the loss of resistant strains. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment. One sentence summaryAntibiotic resistance evolves quickly in patients colonized by polyclonal pathogen populations.

evolutionary biology↗

bioRxiv2021

Functional analysis of Mmd2 and related PAQR genes during sex determination in mice

Sex determination in eutherian mammals is controlled by the Y-linked gene Sry, which drives the formation of testes in male embryos. Despite extensive study, the genetic steps linking Sry action and male sex determination remain largely unknown. Here, we focused on Mmd2, a gene that encodes a member of the progestin and adipoQ receptor (PAQR) family. We show that Mmd2 is expressed during the sex-determining period in XY but not XX gonads, specifically in the Sertoli cell lineage which orchestrates early testis development. Analysis of knockout mice deficient in Sox9 and Sf1 revealed that Mmd2 operates downstream of these known sex-determining genes. However, when we used CRISPR to ablate Mmd2 in the mouse, fetal testis development appeared to progress normally. To determine if other genes might have compensated for the loss of Mmd2, we identified the closely related PAQR family members Paqr8 and Mmd as also being expressed during testis development. We used CRISPR to generate mouse strains deficient in Paqr8 and Mmd, but both knockout lines appeared phenotypically normal and fertile. Finally, we generated Mmd2;Mmd and Mmd2;Paqr8 double-null embryos and again observed normal testis development. These results may reflect functional redundancy among these factors. Our findings highlight the difficulties involved in identifying genes with a functional role in sex determination and gonadal development through expression screening and loss-of-function analyses of individual candidate genes, and may help to explain the paucity of genes in which variations have been found to cause human disorders/differences of sex development.

developmental biology↗

bioRxiv2021

Niche partitioning facilitates coexistence of closely related gut bacteria

Ecological processes underlying bacterial coexistence in the gut are not well understood. Here, we disentangled the effect of the host and the diet on the coexistence of four closely related Lactobacillus species colonizing the honey bee gut. We serially passaged the four species through gnotobiotic bees and in liquid cultures in the presence of either pollen (bee diet) or simple sugars. Although the four species engaged in negative interactions, they were able to stably coexist, both in vivo and in vitro. However, coexistence was only possible in the presence of pollen, and not in simple sugars, independent of the environment. Using metatranscriptomics and metabolomics, we found that the four species utilize different pollen-derived carbohydrate substrates indicating resource partitioning as the basis of coexistence. Our results show that despite longstanding host association, gut bacterial interactions can be recapitulated in vitro providing insights about bacterial coexistence when combined with in vivo experiments.

microbiology↗

bioRxiv2020

Bacterially produced small molecules stimulate diatom growth

Diatoms are photosynthetic microalgae that fix a significant fraction of the worlds carbon. Because of their photosynthetic efficiency and high-lipid content, diatoms are priority candidates for biofuel production. Here, we report that sporulating Bacillus thuringiensis when in co-culture with a marine diatom Phaeodactylum tricornutum significantly increases the diatom cell count. Bioassay-guided purification led to the identification of two diketopiperazines (DKPs) that both stimulate P. tricornutum growth and increase its lipid content. RNA-seq analysis revealed upregulation of a small set of P. tricornutum genes involved in iron starvation response and nutrient recycling when DKP was added to the diatom culture. This work demonstrates that two DKPs produced by a bacterium could positively impact P. tricornutum growth and lipid content, offering new approaches to enhance P. tricornutum-based biofuel production. As increasing numbers of DKPs are isolated from marine microbes, the work gives potential clues to bacterially produced growth factors for marine microalgae. One sentence summaryTwo diketopiperazines (DKPs) produced by sporulating bacterium Bacillus thuringiensis stimulate diatom P. tricornutum growth and increase diatom lipid content.

plant biology↗

bioRxiv2020

Rapid evolution drives the rise and fall of carbapenem resistance during an acute Pseudomonas aeruginosa infection

It is well established that antibiotic treatment selects for resistance in pathogenic bacteria. However, the evolutionary responses of pathogen populations to antibiotic treatment during infections remain poorly resolved, especially in acute infections. Here we map the evolutionary responses to treatment in high definition through genomic and phenotypic characterization of >100 isolates from a patient with P. aeruginosa pneumonia. Antibiotic therapy (meropenem, colistin) caused a rapid crash of the P. aeruginosa population in the lung, but this decline was followed by the spread of meropenem resistance mutations that restrict antibiotic uptake (oprD) or modify LPS biosynthesis (wbpM). Low fitness strains with high-level meropenem resistance (oprD) were then replaced by high fitness strains with anti-resistance mutations in the MexAB-OprM efflux pump, causing a rapid decline in resistance to both meropenem and a collateral loss of resistance to a broad spectrum of antibiotics. In contrast, we did not observe any evolutionary responses to antibiotic treatment in the intestinal population of P. aeruginosa. Carbapenem antibiotics are key to the treatment of infections caused by Gram negative pathogens, and our work highlights the ability of natural selection to drive both the rapid rise and fall of carbapenem resistance during acute infections.

evolutionary biology↗

bioRxiv2020

The Primary Tumor Immune Microenviornment Status Predicts the Response to Immunotherapy and Overall Survival in Breast Cancer

The tumor immune microenvironment (TIME) of breast cancer is a known source of tumor heterogeneity and it has been increasingly recognized as having a role in the course of disease. In the present study, we used a computational approach to dissect the landscape of TIME states among TCGA breast cancer patients. Our central hypothesis is that the pre-existing TIME states represent a dimension which is informative about the prognosis and the response to immunotherapy. In order to test this hypothesis, we first classified breast cancer patients according to their primary TIME status. Next, we describe a TIME-based classification with prognostic value for overall survival among the TCGA patients. We further demonstrated that absolute quantification of mast cells, M0 macrophages, CD8 T cells and neutrophils were predictive of overall survival. In order to identify the TIME states which, predict response to immune checkpoint blockade, we performed a similar analysis of 11 different mouse models of primary invasive breast carcinoma that were subsequently treated with immune checkpoint inhibitor (ICI) therapy. These analyses revealed that the TIME content of M1 macrophages, monocytes and resting dendritic cells were predictive of sensitivity to ICI therapy. Taken together, these results indicate that (1) the landscape of human primary TIME states is diverse and can identify patients with more or less aggressive disease and (2) that pre-existing TIME states may be able to identify patients, of all molecular subtypes of breast cancer, who are good candidates for ICI therapy.View Full Text

cancer biology↗

bioRxiv2019

Tau pathology in early Alzheimer’s disease disrupts selective neurophysiological networks dynamics

The role of aggregation of misfolded Tau protein in the pathogenesis of Alzheimers disease is the subject of rapid biomarker development and new therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography (E/MEG) in combination with [18F]AV1451 PET scanning to quantify Tau-dependent network disruption. Using a graph theoretical approach to MEG connectivity, we quantified nodal measures of functional segregation, centrality and efficiency of information transfer. We correlated these metrics against the nodes uptake of [18F]AV1451. There were both regional- and frequency-specific effects of Tau levels on the efficiency of information transfer and network segregation in early AD. Tau correlated with temporal regional participation coefficient (in delta, theta, beta bands); and temporal lobar eigenvector centrality (in theta, alpha, beta bands), but greater eccentricity at higher frequencies (gamma). The results support the translational development of neurophysiological "signatures" as biomarkers of Alzheimers disease, with potential to facilitate experimental medicines studies.

neuroscience↗