Biology subjects

Hart, S.

Publications and source records attributed to Hart, S..

15 recordsLinked to original sources

bioRxiv2026

Ultrasensitive detection of neuronal DNA using genome-wide non-CG methylation patterns

Methylation-based liquid biopsies can identify the tissue origins of circulating cell-free DNA (cfDNA). A major constraint on the sensitivity of these assays is the limited number of cell-type-specific CpG markers. Here we exploit the high abundance of non-CpG (CpH) methylation in neurons to enable ultrasensitive detection of neuronal DNA. We show that neurons carry 100-fold higher CpH methylation than other tissues, in which apparent CpH methylation largely reflects experimental artifacts. Using a computational criterion to identify cfDNA molecules carrying clusters of methylated CpA sites, we detect neuronal DNA at proportions as low as 20 parts per million. Analysis of 231 samples from 163 individuals revealed minimal neuronal cfDNA in the plasma of healthy subjects; elevated levels in patients with measles or acute neurological conditions; strikingly high levels in brain-dead donors, indicating extensive ongoing neuronal death; and the highest levels in the cerebrospinal fluid of patients in a neurological intensive care unit. These findings establish genome-wide, fragment-level analysis of non-CpG methylation as an ultrasensitive approach for blood-based monitoring of brain injury and disease.

genomics↗

bioRxiv2026

Functional Differentiation of GH172 Arabinofuranosidases Through Divergent Quaternary Structures

Mycobacteria synthesise the unusual glycan [x1D05]-arabinan as a major component of the cell wall glycoconjugates arabinogalactan (AG) and lipoarabinomannan (LAM). We previously identified Dysgonomonas gadei, a member of the Bacteroidota, as capable of complete [x1D05]-arabinan degradation through the concerted action of endo- and exo-acting enzymes. Among these are three glycoside hydrolase family 172 (GH172) enzymes with exo--[x1D05]-arabinofuranosidase activity against AG and LAM, although their linkage specificities were unknown. Here, using defined synthetic substrates, we show that the three enzymes possess distinct linkage preferences. We also develop -[x1D05]-arabinofuranosyl cyclophellitol aziridines as covalent inhibitors and activity-based probes for GH172 enzymes. X-ray crystallography and cryo-EM to reveal strikingly different quaternary assemblies across the three homologues, while a 1.5 [A] cryo-EM structure of dodecameric Dg67 covalently modified by an aziridine inhibitor identifies the catalytic nucleophile and provides direct structural support for a retaining mechanism. A BODIPY-tagged aziridine probe selectively labelled the three GH172 enzymes in D. gadei cell lysates. Together, these findings define functional and structural diversity within GH172 and establish chemical probes for profiling -[x1D05]-arabinofuranosidase activity in complex biological samples.

biochemistry↗

bioRxiv2026

Niche differentiation confers coexistence prior to the species boundary in an aquatic plant

Despite the prevailing view that ecological divergence drives speciation, we know little about when or how nascent lineages evolve the ecological differences needed to coexist upon secondary contact. Here, we apply ecological coexistence theory to quantify the potential for coexistence among 126 allopatric lineages of the globally distributed duckweed Spirodela polyrhiza. Using competition experiments simulating secondary contact, we found that rapid accumulation of niche differences stabilized coexistence to permit sympatry among potentially interbreeding lineages. Competition against sister-species Spirodela intermedia further showed that niche differences accumulate more slowly post-speciation, revealing that niche differences enabling coexistence evolve well before timescales at which speciation is complete. Our findings suggest that rapid coexistence may thus contribute to time-lags in speciation, shaping both the origin and maintenance of biodiversity.

ecology↗

bioRxiv2025

Enhancing Missense Variant Classification in Predicted Intrinsically Disordered Regions

The accurate classification of missense variants is a fundamental challenge in genomics, particularly for those within intrinsically disordered regions (IDRs) where the performance of existing computational predictors is suboptimal. To address this, we developed a machine learning model that extends traditional missense tools with properties that infer globular IDR conformation, phase separation, and protein embeddings. Using ClinVar variant classifications as ground truth, AlphaMissense, EVE, and ESM1b were the highest scoring unsupervised in silico missense predictors for IDR variants. Our baseline model, using only IDR-specific features achieved competitive performance on the hold-out test set with a PR-AUC of 0.800. Critically, when these IDR features were combined with these methods we saw significant overall improvement. The AlphaMissense-Enhanced model increased its PR-AUC from 0.807 to 0.931. Similarly, ESM1b-Enhanced improved PR-AUC from 0.679 to 0.878 and EVE increased from 0.591 to 0.918. These results demonstrate the effectiveness of our enhancements for classifying missense variants in IDRs and highlight its ability to complement existing in silico missense predictors.

bioinformatics↗

bioRxiv2024

Generative AI impact on protein stability prediction in breast cancer genes

The functional classification of a missense variant in cancer predisposition genes is often challenging due to how rare the variant is observed in the population. When available, clinicians utilize a combination of family history, in vitro functional assays and in silico methods to infer protein function. In silico methods, such as missense predictors (predict changes in protein function) and protein stability predictors (predict changes in free energy) have been used to help classify a missense variant in accordance with the American College of Medical Genetics and Genomics (ACMG) guideline. To measure protein stability, many in silico algorithms predict stability based on the change of free energy and most accurate protein stability predictors require a wild-type protein template. In this study, we examine the use of generative AI to predict high-resolution protein structures as templates analyzed with protein stability methods to evaluate loss of function (LOF) activity in cancer predisposition genes BRCA1, BRCA2, PALB2 and RAD51C upon the presence of missense variant. Utilizing multiplexed assay of variant effect measurements and variant classifications from ClinVar, we find that prediction of Gibbs free energy ({Delta}{Delta}G) from AlphaFold2 (AF2) structures analyzed with FoldX predicts LOF better than experimental-derived wild type structures in the BRCT domain of BRCA1 and the DNA binding domain (DBD) of BRCA2, but not in PALB2 and RAD51C. We also find that AF2 structures in the BRCT domain of BRCA1 and DBD-Dss1 domain of BRCA2 analyzed with FoldX measure homologous DNA recombination (HDR) activity significantly better than Rosetta and DDGun3D. Our study also revealed that there are other factors that contribute to predicting loss of function activity other than protein stability, with AlphaMissense ranking the best overall predictor of LOF activity in these tumor suppressor breast cancer genes. Author SummaryThe stability of a protein, often expressed in terms of Gibbs free energy ({Delta}{Delta}G), is a critical factor in predicting loss of function (LOF) activity when a missense variant is present. The effect is higher in haploinsufficient genes like the tumor suppressor genes BRCA1, BRCA2, PALB2 and RAD51C. Protein stability predictors that utilizes a wild-type structure to make its predictions is often limited by the availability of experimentally-derived protein structures. Here, in our study we show that generative AI, like AlphaFold2 (AF2) can predict structures similar to experimentally-derived structures with high similarity. Furthermore, protein stability tools such as FoldX, Rosetta, and DDGun3D can be used in conjunction to measure changes in stability. From our study, we find that complex AF2 structures representing the BRCT domain of BRCA1 and DBD domain of BRCA2 analyzed by FoldX predicts function significantly better than the experimentally-derived structures. However, predicted |{Delta}{Delta}G| does not predict function better than purpose-built in silico missense predictors for protein function. Overall, we find the AlphaMissense is the best predictor to predict function in these tumor suppressor breast cancer genes.

bioinformatics↗

bioRxiv2024

Low copy CRISPR-Cas13d mitigates collateral RNA cleavage

While CRISPR-Cas13 systems excel in accurately targeting RNA, the potential for collateral RNA degradation poses a concern for therapeutic applications and limits broader adoption for transcriptome perturbations. We evaluate the extent to which collateral RNA cleavage occurs when RfxCas13d is delivered via plasmid transfection or lentiviral transduction and find that collateral activity only occurs with high levels of RfxCas13d expression. Using transcriptome-scale and combinatorial CRISPR pooled screens in cell lines with low-copy RfxCas13d, we find high on-target knockdown, without extensive collateral activity regardless of the expression level of the target gene. In contrast, transfection of RfxCas13d, which yields higher nuclease expression, results in collateral RNA degradation. Further, our analysis of a high-fidelity Cas13 variant uncovers a marked decrease in on-target efficiency, suggesting that its reduced collateral activity may be due to an overall diminished nuclease capability.

genomics↗

bioRxiv2024

Adaptation of pain-related projection neurons in acute but not chronic pain

Pain hypersensitivity is associated with increased activity of peripheral and central neurons along the pain neuroaxis1. On the other hand, in other neuronal systems, increased activity leads to adaptive reduction of neuronal excitability to maintain homeostasis2-4. Projection neurons (PNs) of spinal and medullary dorsal horns summate the activity of primary nociceptive and local central interneurons and convey it to higher centers5. We show that at the peak of acute inflammatory pain, PNs reduce their intrinsic excitability and, consequently, action potential firing. When pain resolves, the excitability of PNs returns to baseline. Using electrophysiological and computational approaches, we found that an increase in potassium A-current (IA) underlies the decrease in the excitability of PNs in acute pain conditions. We hypothesized that an IA-induced decrease in PNs firing may restrain the output from the dorsal horn to prevent sensitization and pain chronification. Indeed, no changes of IA in PNs were observed in chronic pain conditions, and PNs exhibit increased intrinsic excitability and firing. Our results reveal an adaptive mechanism in acute pain conditions for regulating the output from the dorsal horn network, which, if interrupted, could trigger pain chronification.

neuroscience↗

bioRxiv2023

Cryo-EM structure of the CDK2-cyclin A-CDC25A complex

The cell division cycle 25 phosphatases CDC25A, B and C regulate cell cycle transitions by dephosphorylating residues in the conserved glycine-rich motif of cyclin-dependent protein kinases (CDKs) to activate CDK activity. Here, we present the cryogenic-electron microscopy (cryo-EM) structure of CDK2-cyclin A in complex with CDC25A at 2.91 [A] resolution, providing a detailed structural analysis of the overall complex architecture and key protein-protein interactions that underpin this 86 kDa complex. We further reveal an unanticipated CDC25A C-terminal helix that is critical for complex formation. Sequence conservation analysis suggests CDK1/2-cyclin A, CDK1-cyclin B and CDK2/3-cyclin E are suitable binding partners for CDC25A, whilst CDK4/6-cyclin D complexes appear unlikely substrates. A comparative structural analysis of CDK-containing complexes also confirms the functional importance of the conserved CDK1/2 GDSEID motif. This structure improves our understanding of the roles of CDC25 phosphatases in CDK regulation and may inform the development of CDC25- targeting anticancer strategies.

biochemistry↗

bioRxiv2022

Fungal community dynamics and carbon mineralization in coarse woody debris across decay stage, tree species, and stand development stage in northern boreal forests

Fungi are primary agents of coarse woody debris (CWD) decay in forests, playing an essential role in nutrient cycling and carbon storage. Characterizing fungal communities within CWD will promote further understanding of the fungal controls on CWD decomposition. We compared fungal community assemblages using alpha and beta diversity metrics, carbon mineralization, and physical and chemical properties of CWD across 3 tree species (trembling aspen [Populus tremuloides], black spruce [Picea mariana], and jack pine [Pinus banksiana]), 5 decay classes, and 2 stand development stages, differing in time-since-stand replacing disturbance (i.e., young/self-thinning and mature/steady-state) in Ontarios boreal forest region. In total, we sampled 180 individual CWD logs from 6 independent stands, with 3 replicates per each species x decay class combination at each site. We found that fungal community structure significantly differed across tree species, decay stage, and stand age. Higher proportions of white rot fungi were found in trembling aspen CWD, whereas higher proportions of brown rot fungi were found in black spruce and jack pine CWD. Proportions of specialized wood decay fungi increased with decay stage and were higher in CWD located in mature forest stands. Fungal diversity was highest in decay class 4 CWD. We found that Mn and K concentrations, total carbon, C/N ratio, carbon mineralization (mg CO2 g dry CWD-1 d-1), and moisture content were important predictors of fungal composition across CWD species and/or decay stage, though how CWD chemistry influences fungal species composition (and vice versa) is unknown. Carbon mineralization was highest in trembling aspen CWD and increased with decay stage, perhaps facilitated by increased N concentrations. This study suggests that forest management guidelines that consider both deadwood quantity and quality will support a broader range of fungal species and communities through post-disturbance stand development, thereby conserving biodiversity over the longer-term in our managed forest systems.

ecology↗

bioRxiv2021

Dexamethasone induces senescence of lung epithelial cells and augments TGF-β1-mediated production of the fibrosis mediator serpin E1 (plasminogen activator inhibitor-1)

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive, incurable scarring disease of the lungs with a prognosis worse than most cancers. Pathologically, IPF is characterised by upregulation of the pro-fibrotic cytokine transforming growth factor-{beta}1 (TGF-{beta}1), activation of fibroblasts, and deposition of collagen in the alveolar interstitium. Recent evidence has highlighted the role of senescent type 2 alveolar epithelial cells in the pathogenesis of IPF. In a clinical trial, a treatment regimen containing a corticosteroid drug accelerated pulmonary fibrosis leading to more hospitalizations and deaths, particularly in patients with telomere shortening which drives cellular senescence. AimTo investigate the potential pro-fibrotic actions of corticosteroids on lung epithelial cells in vitro, including effects on cellular senescence and interactions with TGF-{beta}1. MethodsThe synthetic glucocorticoid dexamethasone (DEX) was incubated with A549 and BEAS-2B human lung epithelial cells in the presence or absence of TGF-{beta}1. Cellular senescence was assessed by morphology, senescence-associated beta-galactosidase (SA {beta}-Gal) expression, and qPCR for transcription of senescence-associated molecular markers. Conditioned media were screened for growth factors and cytokines and cultured with human lung fibroblasts. An IPF lung tissue RNA array dataset was re-analysed with a focus on senescence markers. ResultsDEX induced senescence in lung epithelial cells associated with increased p21 (CDKN1A) expression independently of p16 (CDKN2A) or p53 (TP53). DEX amplified upregulation of the pro-fibrotic mediator serpin E1/plasminogen activator inhibitor-1 (PAI-1) in the presence of TGF-{beta}1. The senescence-associated secretory phenotype from lung epithelial cells treated with DEX plus TGF-{beta}1-treated contained increased concentrations of GM-CSF and IL-6 and when incubated with primary human lung fibroblasts there were trends to increased senescence and production of fibrosis markers. Upregulation of senescence markers was demonstrated by analysis of an IPF transcriptomic dataset. DiscussionDEX induces senescence in lung epithelial cell lines in vitro and interacts with TGF-{beta}1 to amplify production of the pro-fibrotic mediator serpin E1 (PAI-1). This may be a mechanism by which corticosteroids promote pulmonary fibrosis in susceptible individuals. Serpin E1/PAI-1 is a potential druggable target in pulmonary fibrosis.

cell biology↗

bioRxiv2019

Ecological and genomic attributes of novel bacterial taxa that thrive in subsurface soil horizons

While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the U.S. to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi, Nitrospirae, Euryarchaeota, and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments.\n\nImportanceSoil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the U.S., we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored distinct communities compared to the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising amount of novel microbes with unique adaptations to oligotrophic subsurface conditions.

microbiology↗

bioRxiv2019

Robust Hierarchical Density Estimation and Regression for Re-stained Histological Whole Slide Image Co-registration

For many disease conditions, tissue samples are colored with multiple dyes and stains to add contrast and location information for specific proteins to accurately identify and diagnose disease. This presents a computational challenge for digital pathology, as whole-slide images (WSIs) need to be properly overlaid (i.e. registered) to identify co-localized features. Traditional image registration methods sometimes fail due to the high variation of cell density and insufficient texture information in WSIs - particularly at high magnifications. In this paper, we proposed a robust image registration strategy to align re-stained WSIs precisely and efficiently. This method is applied to 30 pairs of immunohistochemical (IHC) stains and their hematoxylin and eosin (H&E) counterparts. Our approach advances the existing methods in three key ways. First, we introduce refinements to existing image registration methods. Second, we present an effective weighting strategy using kernel density estimation to mitigate registration errors. Third, we account for the linear relationship across WSI levels to improve accuracy. Our experiments show significant decreases in registration errors when on matching IHC and H&E pairs, enabling subcellular-level analysis on stained and re-stained histological images. We also provide a tool to allow users to develop their own registration benchmarking experiments.

bioinformatics↗

bioRxiv2018

Clinical diagnosis of TIA or stroke and prognosis in patients with neurological symptoms: a rapid access clinic cohort

BackgroundThe long-term risk of stroke or MI in patients with minor neurological symptoms who are not clinically diagnosed with transient ischaemic attack (TIA) or minor stroke is uncertain.\n\nMethodsWe used data from a rapid access clinic for patients with suspected TIA or minor stroke and follow-up from four overlapping data sources for a diagnosis of ischaemic or haemorrhagic stroke, myocardial infarction, major haemorrhage and death. We identified patients with and without a clinical diagnosis of TIA or minor stroke. We estimated hazard ratios of stroke, MI and death in early and late time periods.\n\nResults5,997 patients were seen from 2004-2013, who were diagnosed TIA or minor stroke (n=3604, 60%) or with other diagnoses (n=2392, 40%). By 5 years the proportion of patients who had a subsequent ischaemic stroke or MI, in patients with a clinical diagnosis of minor stroke or TIA was 19% [95% confidence interval (CI): 17-20%], and in patients with other diagnoses was 10% (95%CI: 8-15%). Patients with clinical diagnosis of TIA or minor stroke had three times the hazard of stroke or MI compared to patients with other diagnoses (HR 2.83 95%CI:2.13-3.76, adjusted age and sex) by 90 days post-event; however from 90 days to end of follow up, this difference was attenuated (HR 1.52, 95%CI:1.25-1.86). Older patients and those who had a history of vascular disease had a high risk of stroke or MI, whether or not they were diagnosed with minor stroke or TIA.\n\nConclusionsCareful attention to vascular risk factors in patients presenting with transient or minor neurological symptoms not thought to be due to stroke or TIA is justified, particularly those who are older or have a history of vascular disease.

epidemiology↗

bioRxiv2018

Cities of the future, visualizing climate change to inspire actions

Combating against climate change requires unified action across all sectors of society. However, this collective action is precluded by the consensus gap between scientific knowledge and public opinion. A growing body of evidence suggests that facts do not persuade people to act. Instead, it is visualization - the ability to simulate relatable scenarios - is the most effective approach for motivating behavior change. Here, we exemplify this approach, using current climate projections to enable people to visualize cities of the future, rather than describing intangible climate variables. Analyzing city pairs for 520 major cities of the world, we characterize which cities will most closely resemble the climate conditions of which other major cities by 2050. On average, most cities will resemble cities that are over 1000km south, and 22% of cities will experience climate conditions that are not currently experienced by any existing major cities. We predict that Londons climate in 2050 will resemble Barcelonas climate today, Madrid will resemble to Marrakesh, Moscow to Sofia, Seattle to San Francisco, Stockholm to Budapest, Tokyo to Changsha, etc. Our approach illustrates how complex climate data can be packaged to provide tangible information. By allowing people to visualize their own climate futures, we hope to empower citizens, policy makers and scientists to visualize expected climate impacts and adapt decision making accordingly.

scientific communication and education↗

bioRxiv2018

Does deterministic coexistence theory matter in a finite world? Insights from serpentine annual plants

Contemporary studies of species coexistence are underpinned by deterministic models that assume that competing species have continuous (i.e. non-integer) densities, live in infinitely large landscapes, and coexist over infinite time horizons. By contrast, in nature species are composed of discrete individuals subject to demographic stochasticity, and occur in habitats of finite size where extinctions occur in finite time. One consequence of these discrepancies is that metrics of species coexistence derived from deterministic theory may be unreliable predictors of the duration of species coexistence in nature. These coexistence metrics include invasion growth rates and niche and fitness differences, which are now commonly applied in theoretical and empirical studies of species coexistence. Here we test the efficacy of deterministic coexistence metrics on the duration of species coexistence in a finite world. We introduce new theoretical and computational methods to estimate coexistence times in stochastic counterparts of classic deterministic models of competition. Importantly, we parameterized this model using experimental field data for 90 pairwise combinations of 18 species of annual plants, allowing us to derive biologically-informed estimates of coexistence times for a natural system. Strikingly, we find that for species expected to deterministically coexist, habitat sizes containing only tens of individuals have predicted coexistence times of greater than 1, 000 years. We also find that invasion growth rates explain 60% of the variation in intrinsic coexistence times, reinforcing their general usefulness in studies of coexistence. However, only by integrating information on both invasion growth rates and species equilibrium population sizes could most (> 99%) of the variation in species coexistence times be explained. This integration is achieved with demographically uncoupled single species models solely determined by the invasion growth rates and equilibrium population sizes. Moreover, because of a complex relationship between niche overlap/fitness differences and equilibrium population sizes, increasing niche overlap and increasing fitness differences did not always result in decreasing coexistence times as deterministic theory would predict. Nevertheless, our results tend to support the informed use of deterministic theory for understanding the duration of species coexistence, while highlighting the need to incorporate information on species equilibrium population sizes in addition to invasion growth rates.

ecology↗