Biology subjects

Sullivan, J.

Publications and source records attributed to Sullivan, J..

At least 19 recordsLinked to original sources

bioRxiv2025

Cigarette Smoke and E-Cigarette Aerosol Extracts Induce Myelopoiesis and Suppress Inflammatory Cytokine Production

Tobacco and nicotine use remain the leading preventable drivers of cancer risk, and both direct and secondhand exposure to combustible cigarettes or electronic nicotine devices perturbs immune function and hematopoiesis. Here, we evaluate the impact of e-cigarette vapor and combustible cigarette smoke on in vitro cell inflammatory responses and in vivo long-term hematopoietic differentiation. In cell-based studies, cigarette smoke extract (CSE) and e-cigarette vapor extract (EVE) consistently suppress LPS-induced TNF- secretion across macrophage/monocyte models, including primary mouse and human cells and complementary cell lines, indicating a reproducible immunosuppressive effect on mature myeloid cells. Brief ex vivo exposure to CSE also alters myeloid subset composition and modifies the proliferative behavior of Tet2-knockout cells, suggesting that smoke-related cues can reshape competitive dynamics among mutant and wild-type myeloid progenitors. To assess consequences of smoking behavior in vivo, we used a custom nose-cone inhalation system to deliver controlled exposures to combustible cigarette smoke or e-cigarette aerosol to mice. Chronic exposure increased myeloid proliferation, consistent with smoking behavior inducing premature aging of the hematopoietic stem cell pool. Thus, these studies support a model in which tobacco exposures blunt innate immune responsiveness while simultaneously driving myeloid expansion conditions that accelerate hematopoietic aging.

cancer biology↗

bioRxiv2025

Ex Vivo Testing of Inflatable Penile Prosthesis in Human Cadaveric Penis with Paired in Silico Model offering Surgical and Biomechanical Insights

BackgroundInflatable penile prostheses (IPPs) are a critical solution for patients with erectile dysfunction refractory to medical therapy. However, a detailed understanding of their mechanical interaction with penile tissues remains limited. AimTo develop and validate an innovative experimental-computational framework for studying IPP behaviour through ex vivo implantation and inflation testing in human cadaveric penile tissue, paired with a finite element-based (FE-based) computational model. MethodsAn AMS 700 IPP was surgically implanted into a human cadaveric penis (including the glans and [~]15 cm of shaft) using standard clinical techniques. The cylinders were placed within the corpora cavernosa, with the pump and reservoir positioned externally in a closed hydraulic loop. An inflation test was performed ex vivo, with real-time ultrasound imaging used to monitor cylinder expansion. Internal pressure was recorded using a digital barometer. Following inflation, sectional analysis enabled 3D approximation of penile shaft geometry. A representative FE-based computational model was developed, incorporating anatomically accurate tissue layers--tunica albuginea (TA), corpus cavernosa (CC), corpus spongiosum (CS), and fascia--with realistic material properties to simulate the inflation process. OutcomesThis study enabled the mechanical response of penile tissues to IPP inflation to be quantified using both experimental and computational modalities. ResultsThe combined use of ultrasound imaging and digital pressure monitoring successfully captured dynamic IPP behaviour during inflation. The FE model reproduced experimental outcomes with good fidelity, providing a detailed understanding of stress distribution and tissue deformation. Clinical ImplicationsThis integrated approach can inform future IPP design improvements and aid surgeons in preoperative planning by offering predictive insights into prosthesis-tissue interaction. Strengths & LimitationsA major strength of this study is the novel integration of cadaveric experimentation with computational modelling. However, limitations include the absence of active physiological responses and potential variability due to cadaveric tissue properties. ConclusionThis pioneering work establishes a robust platform for studying IPP mechanics in realistic anatomical contexts, with promising implications for optimising device design and improving patient outcomes in urologic surgery.

bioengineering↗

bioRxiv2025

The lag phase of seed development plays an important role in determining the maximum potential final seed weight in soybean (Glycine max L.)

Soybean (Glycine max L.) cultivars exhibit substantial variation in seed weight; however, the developmental and physiological mechanisms contributing to this variation remain incompletely characterized. Here, we investigated the relationship between early seed developmental dynamics and final seed weight by comparing two large-seeded and two small-seeded cultivars under control and depodding conditions. Depodding, achieved by retaining a single pod per node, minimized assimilate competition. Final seed weight was positively correlated with cotyledon cell number and duration of the lag phase, which is a key early stage of seed development. Large-seeded cultivars exhibited significantly longer lag phases and higher cotyledon pavement cell numbers than small-seeded cultivars, suggesting that extended lag phases promote enhanced cell proliferation, contributing to increased seed weight. Depodding further increased the cotyledon cell number; however, this response was associated with accelerated embryo development rather than an extension of the lag phase. These findings indicate that both the duration of the lag phase and the rate of early embryo development influence cotyledon cell proliferation and ultimately seed weight. Moreover, genetic factors and assimilate availability regulate developmental processes through distinct pathways. Together, our results highlight the importance of early seed developmental timing in determining final seed weight and provide new insights into the developmental basis of yield-related traits in soybean.

plant biology↗

bioRxiv2025

Not So Mosaic After All? The Core Genomes of IncP-1 Plasmids Evolve Predominantly Through Vertical Trasmission

Broad-host-range plasmids of the incompatibility group IncP-1 play an important role in bacterial evolution by disseminating genes between diverse bacteria. This includes the notable spread of antibiotic resistance genes to bacterial pathogens that increasingly threaten human health. A better understanding of the evolution of genetic elements like IncP-1 plasmids that underwrite bacterial adaptation is required to counter this threat. Here we examined the evolutionary history of IncP-1 plasmids by utilizing the large increase in published genomes and advancing techniques for lineage-based detection of microbial recombination. We specifically tested whether IncP-1 backbone genes evolve primarily (1) through vertical transmission, or (2) horizontally through homologous recombination between distinct plasmids. Our key finding is the IncP-1 plasmid backbone evolves predominantly through vertical transmission, which was supported by a nucleotide-level mapping of backbone recombination. We also showed via a phylogeny of 187 IncP-1 plasmids that established subgroup categories are well-supported. Finally, we examined factors that are potentially associated with IncP-1 subgroup diversification, including a gene related to plasmid-host adaptation and accessory genes like antibiotic and resistance metals. While some IncP-1 subgroups do correlate with certain categories of accessory genes, it remains unknown if these are causes or consequences of subgroup diversification.

evolutionary biology↗

bioRxiv2025

Predicting cellular responses to perturbation across diverse contexts with STATE

Cellular responses to perturbations are a cornerstone for understanding biological mechanisms and selecting drug targets. While machine learning models offer tremendous potential for predicting perturbation effects, they currently struggle to generalize to unobserved cellular contexts. Here, we introduce SO_SCPLOWTATEC_SCPLOW, a transformer model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. SO_SCPLOWTATEC_SCPLOW predicts perturbation effects across sets of cells and is trained using gene expression data from over 100 million perturbed cells. SO_SCPLOWTATEC_SCPLOW improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling and chemical perturbations with significantly improved accuracy. Using its cell embedding trained on observational data from 167 million cells, SO_SCPLOWTATEC_SCPLOW identified strong perturbations in novel cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that highlights SO_SCPLOWTATEC_SCPLOWs ability to detect cell type-specific perturbation responses, such as cell survival. Overall, the performance and flexibility of SO_SCPLOWTATEC_SCPLOW sets the stage for scaling the development of virtual cell models.

systems biology↗

bioRxiv2025

Multiplex-edited mice recapitulate woolly mammoth hair phenotypes

The woolly mammoth (Mammuthus primigenius) possessed a thick woolly coat and other cold-adaptive traits that enabled survival in harsh arctic environments. Current de-extinction efforts focus on genetically modifying the closely related Asian elephant to express woolly mammoth traits. In this study, we establish a multiplex-edited mouse model with modifications in genes associated with hair morphology and lipid metabolism, enabling insights into traits involved in developing woolly hair textures. Our optimized workflows achieved high editing efficiencies and produced genetically modified mice with simultaneous editing of up to seven different genes. Selected modifications include loss-of-function mutations in Fgf5, Tgm3, and Fam83g, among others. The resulting mice display exaggerated hair phenotypes including curly, textured coats, and golden-brown hair. This study advances methods of rapid establishment of complex genetic models. These approaches inform de-extinction efforts and research involving the genetic basis of mammalian hair development.

genetics↗

bioRxiv2025

Genome modeling and design across all domains of life with Evo 2

All of life encodes information with DNA. While tools for sequencing, synthesis, and editing of genomic code have transformed biological research, intelligently composing new biological systems would also require a deep understanding of the immense complexity encoded by genomes. We introduce Evo 2, a biological foundation model trained on 9.3 trillion DNA base pairs from a highly curated genomic atlas spanning all domains of life. We train Evo 2 with 7B and 40B parameters to have an unprecedented 1 million token context window with single-nucleotide resolution. Evo 2 learns from DNA sequence alone to accurately predict the functional impacts of genetic variation--from noncoding pathogenic mutations to clinically significant BRCA1 variants--without task-specific finetuning. Applying mechanistic interpretability analyses, we reveal that Evo 2 autonomously learns a breadth of biological features, including exon-intron boundaries, transcription factor binding sites, protein structural elements, and prophage genomic regions. Beyond its predictive capabilities, Evo 2 generates mitochondrial, prokaryotic, and eukaryotic sequences at genome scale with greater naturalness and coherence than previous methods. Guiding Evo 2 via inference-time search enables controllable generation of epigenomic structure, for which we demonstrate the first inference-time scaling results in biology. We make Evo 2 fully open, including model parameters, training code, inference code, and the OpenGenome2 dataset, to accelerate the exploration and design of biological complexity.

genomics↗

bioRxiv2024

A systematic review of laboratory investigations into the pathogenesis of avian influenza viruses in wild avifauna of North America

The lack of consolidated information regarding wild bird species response to avian influenza virus (AIV) infection is a challenge for conservation managers, researchers, and related sectors such as public health and commercial poultry. Such information could be used to model complex disease dynamics within communities, prioritize species for surveillance and conservation efforts, or identify species more likely to facilitate spillover into domestic animals or humans. Using two independent searches, we reviewed published literature for studies describing wild bird species experimentally infected with avian influenza to assess host species relative susceptibility to AIVs. Additionally, we summarized broad-scale parameters for elements such as shedding duration and minimum infectious dose that can be used in transmission modeling efforts. Our synthesis documented that waterfowl (i.e., Anatidae) comprise the vast majority of published AIV pathobiology studies, whereas gulls and passerines were less represented in research despite evidence that they also are susceptible and contribute to high pathogenicity avian influenza disease dynamics. This study represents the first comprehensive effort to compile available literature regarding the pathobiology of AIVs in all wild birds in over a decade. This database provides an opportunity to critically examine and assess what is known and identify where further insight is needed.

ecology↗

bioRxiv2024

Perturbation-Specific Transcriptional Mapping facilitates unbiased target elucidation of antibiotics

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the post-genomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called Perturbation-Specific Transcriptional Mapping (PerSpecTM), in which large-throughput expression profiling of wildtype or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three new molecules with activity against Pseudomonas aeruginosa by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small molecule inhibition resemble those resulting from genetic depletion of essential targets by CRISPRi by PerSpecTM, demonstrating proof-of-concept that correlations between expression profiles of small molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts. Significance StatementNew antibiotics are critically needed in the face of increasing antibiotic resistance. However, mechanism-of-action (MOA) elucidation remains challenging and imposes a major bottleneck in antibiotic discovery and development. Building on the principle that molecules with similar MOAs elicit similar transcriptional responses, we have developed a highly scalable strategy for MOA prediction in the important bacterial pathogen Pseudomonas aeruginosa based on correlations between the expression profiles of new molecules and known perturbations, either small molecule inhibition by known antibiotics or transcriptional repression of essential targets by CRISPRi. By rapidly assigning MOAs to three new molecules with anti-pseudomonal activity, we provide proof-of-concept for a rapid, comprehensive, systematic, reference-based approach to MOA prediction with the potential to transform antibiotic discovery efforts.

genomics↗

bioRxiv2024

Sequence modeling and design from molecular to genome scale with Evo

The genome is a sequence that completely encodes the DNA, RNA, and proteins that orchestrate the function of a whole organism. Advances in machine learning combined with massive datasets of whole genomes could enable a biological foundation model that accelerates the mechanistic understanding and generative design of complex molecular interactions. We report Evo, a genomic foundation model that enables prediction and generation tasks from the molecular to genome scale. Using an architecture based on advances in deep signal processing, we scale Evo to 7 billion parameters with a context length of 131 kilobases (kb) at single-nucleotide, byte resolution. Trained on 2.7M prokaryotic and phage genomes, Evo can generalize across the three fundamental modalities of the central dogma of molecular biology to perform zero-shot function prediction that is competitive with, or outperforms, leading domain-specific language models. Evo also excels at multi-element generation tasks, which we demonstrate by generating synthetic CRISPR-Cas molecular complexes and entire transposable systems for the first time. Using information learned over whole genomes, Evo can also predict gene essentiality at nucleotide resolution and can generate coding-rich sequences up to 650 kb in length, orders of magnitude longer than previous methods. Advances in multi-modal and multiscale learning with Evo provides a promising path toward improving our understanding and control of biology across multiple levels of complexity.

synthetic biology↗

bioRxiv2023

A novel framework to build saliva-based DNA methylation biomarkers: quantifying systemic chronic inflammation as a case study

Accessible and non-invasive biomarkers that measure human ageing processes and the risk of developing age-related disease are paramount in preventative healthcare. In this study, we describe a novel framework to train saliva-based DNA methylation (DNAm) biomarkers that are reproducible and biologically interpretable. By leveraging a reliability dataset with replicates across tissues, we demonstrate that it is possible to transfer knowledge from blood DNAm data to saliva DNAm data using DNAm proxies of blood proteins (EpiScores). We then apply these methods to create a new saliva-based epigenetic clock (InflammAge) that quantifies systemic chronic inflammation (SCI) in humans. Using a large blood DNAm human cohort with linked electronic health records and over 18,000 individuals (Generation Scotland), we demonstrate that InflammAge significantly associates with all-cause mortality, disease outcomes, lifestyle factors and immunosenescence; in many cases outperforming the widely used SCI biomarker C-reactive protein (CRP). We propose that our biomarker discovery framework and InflammAge will be useful to improve our understanding of the molecular mechanisms underpinning human ageing and to assess the impact of gero-protective interventions.

bioinformatics↗

bioRxiv2023

High-efficiency base editing for Stargardt disease in mice, non-human primates, and human retina tissue

Stargardt disease is a currently untreatable, inherited neurodegenerative disease that leads to macular degeneration and blindness due to loss-of-function mutations in the ABCA4 gene. We have designed a dual adeno-associated viral vector split-intein adenine base-editing strategy to correct the most common mutation in ABCA4 (c.5882G>A, p.G1961E). We optimized ABCA4 base editing in human models, including retinal organoids, iPSC-derived retinal pigment epithelial (RPE) cells, as well as adult human retinal- and RPE/choroid explants in vitro. The resulting gene therapy vectors achieved high levels of gene correction in mutation-carrying mice and in non-human primates, with an average editing of 37% of photoreceptors and 73% of RPE cells in vivo. The high editing rates in primates make way for precise and efficient gene editing in other neurodegenerative ocular diseases.

neuroscience↗

bioRxiv2023

Structural insights into TRPV4-Rho GTPase signaling complex function and disease

Crosstalk between ion channels and small GTPases is critical during homeostasis and disease1, but little is known about the structural underpinnings of these interactions. TRPV4 is a polymodal, calcium-permeable cation channel that has emerged as a potential therapeutic target in multiple conditions2-5. Gain-of-function mutations also cause hereditary neuromuscular disease6-11. Here, we present cryo-EM structures of human TRPV4 in complex with RhoA in the apo, antagonist-bound closed, and agonist-bound open states. These structures reveal the mechanism of ligand-dependent TRPV4 gating. Channel activation is associated with rigid-body rotation of the intracellular ankyrin repeat domain, but state-dependent interaction with membrane-anchored RhoA constrains this movement. Notably, many residues at the TRPV4-RhoA interface are mutated in disease and perturbing this interface by introducing mutations into either TRPV4 or RhoA increases TRPV4 channel activity. Together, these results suggest that the interaction strength between TRPV4 and RhoA tunes TRPV4-mediated calcium homeostasis and actin remodeling, and that disruption of TRPV4-RhoA interactions leads to TRPV4-related neuromuscular disease, findings that will guide TRPV4 therapeutics development.

biophysics↗

bioRxiv2022

HumanMine: advanced data searching, analysis and cross-species comparison.

HumanMine (www.humanmine.org) is an integrated database of human genomics and proteomics data that provides a powerful interface to support sophisticated exploration and analysis of data compiled from experimental, computational and curated data sources. Built using the InterMine data integration platform, HumanMine includes genes, proteins, pathways, expression levels, SNPs, diseases and more, integrated into a single searchable database. HumanMine promotes integrative analysis, a powerful approach in modern biology that allows many sources of evidence to be analysed together. The data can be accessed through a user-friendly web interface as well as a powerful, scriptable web service API to allow programmatic access to data. The web interface includes a useful identifier resolution system, sophisticated query options and interactive results tables that enable powerful exploration of data, including data summaries, filtering, browsing and export. A set of graphical analysis tools provide a rich environment for data exploration including statistical enrichment of sets of genes or other biological entities. HumanMine can be used for integrative multi-staged analysis that can lead to new insights and uncover previously unknown relationships. Database URL: https://www.humanmine.org

genomics↗

bioRxiv2022

Comprehensive phylogenomics of Methylobacterium reveals four evolutionary distinct groups and underappreciated phyllosphere diversity.

Methylobacterium is a group of methylotrophic microbes associated with soil, fresh water, and particularly the phyllosphere, the aerial part of plants that has been well-studied in terms of physiology but whose evolutionary history and taxonomy are unclear. Recent work has suggested that Methylobacterium is much more diverse than thought previously, questioning its status as an ecologically and phylogenetically coherent taxonomic genus. However, taxonomic and evolutionary studies of Methylobacterium have mostly been restricted to model species, often isolated from habitats other than the phyllosphere, and have yet to utilize comprehensive phylogenomic methods to examine gene trees, gene content, or synteny. By analyzing 189 Methylobacterium genomes from a wide range of habitats, including the phyllosphere, we inferred a robust phylogenetic tree while explicitly accounting for the impact of horizontal gene transfers. We showed that Methylobacterium contains four evolutionary distinct groups of bacteria (namely A, B, C, D), characterized by different genome size, GC content, gene content and genome architecture, revealing the dynamic nature of Methylobacterium genomes. In addition of recovering 59 described species, we identified 45 candidate species, mostly phyllosphere-associated, stressing the significance of plants as a reservoir of Methylobacterium diversity. We inferred an ancient transition from a free-living lifestyle to association with plant roots in Methylobacteriaceae ancestor, followed by phyllosphere association of three of the major groups (A, B, D), which early branching in Methylobacterium history was heavily obscured by HGT. Together, our work lays the foundations for a thorough redefinition of Methylobacterium taxonomy, beginning with the abandon of Methylorubrum.

genomics↗

bioRxiv2022

Genomic resolution of cryptic species diversity in chipmunks

Discovery of cryptic species is essential to understanding the process of speciation and assessing the impacts of anthropogenic stressors. Here, we used genomic data to test for cryptic species diversity within an ecologically well-known radiation of North American rodents, western chipmunks (Tamias). We assembled a de novo reference genome for a single species (Tamias minimus) combined with new and published targeted sequence-capture data for 21,551 autosomal and 493 X-linked loci sampled from 121 individuals spanning 22 species. We identified at least two cryptic lineages corresponding with an isolated subspecies of least chipmunk (T. minimus grisescens) and with a restricted subspecies of the yellow-pine chipmunk (T. amoenus cratericus) known only from around the extensive Craters of the Moon lava flow. Additional population-level sequence data revealed that the so-called Crater chipmunk is a distinct species that is abundant throughout the coniferous forests of southern Idaho. This cryptic lineage does not appear to be most closely related to the ecologically and phenotypically similar yellow-pine chipmunk but does show evidence for recurrent hybridization with this and other species.

evolutionary biology↗

bioRxiv2021

Genomic resources for the North American water vole (Microtus richardsoni) and the montane vole (Microtus montanus)

BackgroundVoles of the genus Microtus are important research organisms, yet genomic resources in the genus are lacking. Providing such resources would benefit future studies of immunology, phylogeography, cryptic diversity, and more. FindingsWe sequenced and assembled nuclear genomes from two subspecies of water vole (Microtus richardsoni) and from the montane vole (Microtus montanus). The water vole genomes were sequenced with Illumina and 10X Chromium plus Illumina sequencing, resulting in assemblies with ~1,600,000 and ~30,000 scaffolds respectively. The montane vole was assembled into ~13,000 scaffolds using Illumina sequencing also. In addition to the nuclear assemblies, mitochondrial genome assemblies were also performed for both species. We conducted a structural and functional annotation for the best water vole nuclear genome, which resulted in ~24,500 annotated genes, with 83% of these receiving functional annotations. Finally, we find that assembly quality statistics for our nuclear assemblies fall within the range of genomes previously published in the genus Microtus, making the water vole and montane vole genomes useful additions to currently available genomic resources.

genomics↗

bioRxiv2020

Insights into the diversity and survival strategies of soil bacterial isolates from the Atacama Desert

The Atacama Desert, the driest and oldest desert in the world, is a hostile environment for life. Despite the inhospitable conditions, bacterial sequences detected in this location suggest rich bacterial life. This study tested the idea that certain bacteria would thrive in this location and that some of them could be cultivated permitting further characterization. Environmental surface soil samples from 1-5 cm deep were collected from 18 diverse locations within the Atacama Desert. To assess the bacterial taxa, diversity, and abundance, Illumina 16S rRNA gene sequencing was performed directly on soil samples. Bacteria were also cultured from the samples. We have a collection of 74 unique bacterial isolates after cultivation and confirmation by 16S rRNA gene sequencing. Pigmentation, biofilm formation, antibiotic production against Escherichia coli MG1655 and Staphylococcus aureus HG003, and antibiotic resistance were assessed on these isolates. We found that approximately a third of the colonies produced pigments, 80% of isolates formed biofilms, many isolates had antibiotic activity against E. coli and/or S. aureus, and many were resistant to commercial antibiotics. The functional characterization of these isolates gives us insight into the adaptive bacterial strategies in harsh environments and enables us to learn about their possible use in agriculture, healthcare, or biotechnology. Originality-Significant StatementThis study provides the first microbial diversity analysis from Atacama Desert soil, presents the cultivation and isolation of 74 unique bacterial isolates, many of which may be novel genera and species, and explores pigment production, antibiotic production and resistance, and unique biofilm development as bacterial survival strategies for living within extreme environments.

microbiology↗