Biology subjects

Hartman, H.

Publications and source records attributed to Hartman, H..

8 recordsLinked to original sources

bioRxiv2026

Methodological Evaluation and Data Resource for Andes Virus Sequencing Preparedness

As part of preparedness activities supporting pathogens classified under the UK High Consequence Infectious Diseases (HCID) framework, we previously evaluated both a whole-genome tiling amplicon sequencing scheme and a pan-viral hybridisation capture approach (TWIST-CVRP) for sequencing Andes virus (ANDV). In light of the recent outbreak, we make available viral sequencing datasets generated using a historical ANDV isolate (Chile, 1997). In addition, we provide an evaluation of tiling amplicon scheme performance and present recommended primer updates informed by in silico comparison with the recently released outbreak genome. These datasets are intended to support benchmarking, validation, and optimisation of bioinformatic pipelines across the community.

genomics↗

bioRxiv2026

SynAPSeg: A novel dataset and image analysis framework for deep learning-based synapse detection and quantification

Synapses are the fundamental units of neural computation, yet quantifying their organization across circuit-level scales remains a critical bottleneck in neuroscience. While advances in fluorescent labeling and imaging can generate vast datasets, analysis is often the limiting factor. Several deep learning-based tools have been proposed to ameliorate these issues. However, existing applications primarily focus on dendritic spines and lack robust solutions for segmenting synaptic puncta in dense tissue preparations. To address this, we introduce SynAPSeg, which encompasses an open-source framework for deep learning-based analysis and, to the best of our knowledge, the first large-scale, publicly available instance segmentation dataset specifically curated for synaptic puncta. We use this dataset to train deep learning models that reach the performance of human experts across a unique benchmark dataset. SynAPSeg integrates these models into an interactive interface, with support for multi-dimensional data, enabling fully automated segmentation and quantification pipelines alongside an annotation module for refinement and validation. We demonstrate the frameworks scalability by performing the first comprehensive mapping of nearly 4 million excitatory postsynaptic PSD95 puncta within inhibitory interneurons across the dorsal hippocampus, revealing regional differences in synapse properties. Finally, we show SynAPSegs utility for 3D quantification by applying these models to study aging-associated synaptic changes in CA1 parvalbumin (PV)-positive inhibitory neurons. Through this approach, we uncover a reduction in PSD95 density along PV dendrites in the aged CA1, indicating reduced glutamatergic recruitment of PV neurons which could contribute to age-related cognitive decline. Collectively, these results demonstrate that SynAPSeg provides a scalable solution for comprehensively studying synaptic architecture in health and disease.

neuroscience↗

bioRxiv2025

ROR2 drives right ventricular heart failure via disruption of proteostasis

BackgroundNo therapies exist to reverse right ventricular failure (RVF), and the molecular mechanisms that drive RVF remain under studied. We recently reported that the developmentally restricted noncanonical WNT receptor ROR2 is upregulated in human RVF in proportion to severity of disease. Here we test the mechanistic role of ROR2 in RVF pathogenesis. MethodsROR2 was overexpressed or knocked down in neonatal rat ventricular myocytes (NRVMs) and then characterized using confocal microscopy, RNAseq, proteomics, proteostatic functional assays, and pacing to assess contractile properties. The impact of cardiac ROR2 expression was evaluated in mice by AAV9-mediated overexpression and by AAV9-mediated delivery of shRNA to knockdown ROR2 in a pulmonary artery banded pressure overload model of RVF. ROR2-modified mice were evaluated by echocardiography, histology, and RV protein synthesis and proteasome capacity. ResultsIn NRVMs, we find that ROR2 profoundly dysregulates the coordination between protein translation and folding. This imbalance leads to excess protein clearance by the ubiquitin proteasome system (UPS) with dramatic impacts on sarcomere and cytoskeletal structure and function. Inhibiting the UPS or restoring chaperone expression is sufficient to partially rescue ROR2-induced structural and contractile deficits in cardiomyocytes. In mice, forced cardiac ROR2 expression is sufficient to disrupt proteostasis and drive RVF, while conversely ROR2 knockdown partially rescues proteostasis and RV structure and function in a pressure overload model of RVF. ConclusionsIn sum, ROR2 is a key driver of RVF pathogenesis through proteostatic disruption and, thus, provides a promising target to treat RVF.

molecular biology↗

bioRxiv2023

Salmonella Infantis, the emerging human multidrug resistant pathogen - a One Health perspective

Salmonella Infantis presents an ever-increasing threat to public health due to its spread throughout many countries and association with high levels of antimicrobial resistance (AMR). Whole genome sequences of 5,284 S. Infantis strains from 74 countries, isolated between 1989 and 2020 from a wide variety of sources including humans, animals, and food, were analysed to compare genetic phylogeny, AMR determinants and plasmid presence. The global S. Infantis population structure diverged into three clusters: a North American cluster, European cluster and a global cluster. The levels of AMR varied between the S. Infantis clusters and by isolation source; 73% of poultry isolates had multidrug resistance (MDR) compared to 35% of human isolates. This correlated with plasmid of emerging S. Infantis (pESI) presence; 71% of poultry isolates contained pESI versus 32% of human isolates. This provides important information for public health teams engaged in reducing the spread of this pathogen.

microbiology↗

bioRxiv2022

Genome-first detection of emerging resistance to novel therapeutic agents for SARS-CoV-2

Some COVID-19 patients are unable to clear their infection or are at risk of severe disease, requiring treatment with neutralising monoclonal antibodies (nmAb) and/or antivirals. The rapid roll-out of novel therapeutics means there is limited understanding of the likely genetic barrier to drug resistance. Unprecedented genomic surveillance of SARS-CoV-2 in the UK has enabled a genome-first approach to the detection of emerging drug resistance. Here we report the accrual of mutations in Delta and Omicron cases treated with casirivimab+imdevimab and sotrovimab respectively. Mutations occur within the epitopes of the respective nmAbs. For casirivimab+imdevimab these are present on contiguous raw reads, simultaneously affecting both components. Using surface plasmon resonance and pseudoviral neutralisation assays we demonstrate these mutations reduce or completely abrogate antibody affinity and neutralising activity, suggesting they are driven by immune evasion. In addition, we show that some mutations also reduce the neutralising activity of vaccine-induced serum.

genetics↗

bioRxiv2019

Informal genomic surveillance of regional distribution of Salmonella Typhi genotypes and antimicrobial resistance via returning travellers

Salmonella enterica serovar Typhi (S. Typhi) is the causative agent of typhoid fever, a systemic human infection with a burden exceeding 20 million cases each year that occur disproportionately among children in low and middle income countries. Antimicrobial therapy is the mainstay for treatment, but resistance to multiple agents is common. Here we report genotypes and antimicrobial resistance (AMR) determinants detected from routine whole-genome sequencing (WGS) of 533 S. Typhi isolates referred to Public Health England between April 2014 and April 2017, 488 (92%) of which had accompanying patient travel information obtained via an enhanced surveillance questionnaire. The majority of cases involved S. Typhi 4.3.1 (H58) linked with travel to South Asia (58%). Travel to East and West Africa were associated with genotypes 4.3.1 and 3.3.1, respectively. Point mutations in the quinolone resistance determining region (QRDR), associated with reduced susceptibility to fluoroquinolones, were very common (85% of all cases) but the frequency varied significantly by region of travel: 95% in South Asia, 43% in East Africa, 27% in West Africa. QRDR triple mutants, resistant to ciprofloxacin, were restricted to 4.3.1 lineage II and associated with travel to India, accounting for 23% of cases reporting travel to the country. Overall 24% of isolates were MDR, however the frequency varied significantly by region and country of travel: 27% in West Africa, 52% in East Africa, 55% in Pakistan, 24% in Bangladesh, 3% in India. MDR determinants were plasmid-borne (IncHI1 PST2 plasmids) in S. Typhi 3.1.1 linked to West Africa, but in all other regions MDR was chromosomally integrated in 4.3.1 lineage I. We propose that routine WGS data from travel-associated cases in industrialised countries could serve as informal sentinel AMR genomic surveillance data for countries where WGS is not available or routinely performed.\n\nAuthor SummaryOur data demonstrate how routine WGS data produced by Public Health England can be further mined for informal passive surveillance of Salmonella Typhi circulating in different geographical regions where typhoid is endemic. We have shown the public health utility of a simplified approach to WGS reporting based on the GenoTyphi genotyping framework and nomenclature, which doesnt require the generation of a phylogenetic tree or other phylogenetic analysis. These approaches yielded results consistent with previously reported antimicrobial resistance (AMR) patterns of S. Typhi, including prevalence of multi-drug resistant (MDR) and fluoroquinolone resistance in different regions in association with different pathogen variants. These data provide a rationale and framework for the extraction and reporting of geographically stratified genotype and AMR data from public health labs in non-endemic countries. Prospective analysis and reporting of such data could potentially detect shifts in regional S. Typhi populations, such as replacement or spread of different subclades and the emergence and dissemination of MDR, fluoroquinolone resistant and/or extensively drug resistant S. Typhi, providing valuable data to inform typhoid control measures in low and middle income countries that are still building their genomics capacity.

microbiology↗

bioRxiv2018

Boundary conditions for early life converge to an organo-sulfur metabolism

It has been suggested that a deep memory of early life is hidden in the architecture of metabolic networks, whose reactions could have been catalyzed by small molecules or minerals prior to genetically encoded enzymes (1-6). A major challenge in unraveling these early steps is assessing the plausibility of a connected, thermodynamically consistent proto-metabolism under different geochemical conditions, which are still surrounded by high uncertainty. Here we combine network-based algorithms (9, 10) with physicochemical constraints on chemical reaction networks to systematically show how different combinations of parameters (temperature, pH, redox potential and availability of molecular precursors) could have affected the evolution of a proto-metabolism. Our analysis of possible trajectories indicates that a subset of boundary conditions converges to an organo-sulfur-based proto-metabolic network fueled by a thioester- and redox-driven variant of the reductive TCA cycle, capable of producing lipids and keto acids. Surprisingly, environmental sources of fixed nitrogen and low-potential electron donors seem not to be necessary for the earliest phases of biochemical evolution. We use one of these networks to build a steady-state dynamical metabolic model of a proto-cell, and find that different combinations of carbon sources and electron acceptors can support the continuous production of a minimal ancient \"biomass\" composed of putative early biopolymers and fatty acids.

systems biology↗

bioRxiv2017

SnapperDB: A database solution for routine sequencing analysis of bacterial isolates

Real-time surveillance of infectious disease using whole genome sequencing data poses challenges in both result generation and communication. SnapperDB represents a set of tools to store bacterial variant data and facilitate reproducible and scalable analysis of bacterial populations. We also introduce the SNP address nomenclature to describe the relationship between isolates in a population to the single nucleotide resolution.\n\nSummaryWe announce the release of SnapperDB v1.0 a program for scalable routine SNP analysis and storage of microbial populations.\n\nAvailabilitySnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb.\n\nContacttim.dallman@phe.gov.uk\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗