Biology subjects

Sullivan, A.

Publications and source records attributed to Sullivan, A..

14 recordsLinked to original sources

bioRxiv2026

Neurometabolic signatures of addiction vulnerability and heroin versus social seeking: a PET study in rats

Only a subset of heroin users develop addiction, characterized by binge-like heroin use and preference for heroin over other rewards, including social rewards. We recently established a rat model of these features. We trained rats to lever-press for social interaction and heroin (or saline, control) infusions and then tested heroin- and social-seeking and heroin-vs.-social choice. During 3-5 abstinence weeks, we used 2-deoxy-2-[{superscript 1}F]fluoro-D-glucose (FDG) PET imaging to assess regional brain metabolic activity at rest (homecage) and during heroin and social seeking. We assessed regional differences in FDG uptake using unbiased voxel-wise analysis and statistical parametric mapping, and correlated FDG uptake with principle-component-analysis-derived addiction severity score incorporating heroin intake, binge-like episodes, and heroin preference. Compared with saline-trained rats, heroin-trained rats showed overall higher FDG uptake across multiple brain regions at rest and during both reward-seeking tests. Comparison of heroin-vs.-social-seeking in heroin-trained rats showed higher uptake in claustrum/lateral striatum and auditory cortex during social seeking. Analysis of individual differences showed that addiction severity was primarily associated with metabolic alterations under resting conditions rather than during heroin- or social-seeking. At rest, higher addiction severity was associated with lower uptake in piriform cortex and higher uptake in ventral hippocampus, whereas during heroin-seeking, addiction severity was associated with lower uptake in post-subiculum and cerebellum. Addiction severity was not associated with differences in social seeking or FDG uptake during social seeking. These findings identify neurometabolic features of social and heroin seeking and heroin addiction vulnerability that can potentially serve as brain biomarkers and targets for neuromodulation. Significance StatementHeroin addiction develops in only a subset of users, yet the determinants of vulnerability versus resilience to addiction remain largely unknown. We combined a rat model capturing key features of heroin addiction, including binge-like heroin intake and preference for heroin over social interaction, with behavioral heroin- and social-seeking assays and longitudinal whole-brain metabolic imaging using FDG-PET. We identified distinct patterns of neurometabolic alterations associated with heroin self-administration and addiction severity at rest and in the context of heroin seeking. In contrast, heroin self-administration and addiction severity were not significantly associated with neurometabolic alterations during social seeking. These findings highlight brain-wide neurometabolic features of vulnerability to heroin addiction that can serve as brain biomarkers and targets for neuromodulation.

neuroscience↗

bioRxiv2025

Sugar ABC transporter repertoires predict ecological dynamics in gut microbiome communities

The gut microbiome plays a central role in human health, but modern diets and lifestyles alter its composition. The microbial genomic traits that drive these ecological shifts, particularly in response to dietary sugars, remain poorly characterized. Here, we integrate a large dataset of longitudinal human diet-microbiome records and comparative genomics of human and murine gut isolates with in vitro and in vivo experiments to identify sugar ABC (ATP-binding cassette) transporters as key predictors of bacterial fitness and microbial community responses to dietary sugars. Strains encoding these transporters exhibit enhanced growth and consistently outcompete others in both monocultures and complex consortia across contexts. In gnotobiotic mice, dietary sugar supplementation selectively increases the expansion of sugar ABC transporter-positive bacteria, including the model gut pathobiont Escherichia coli. Systematic deletion of sugar transporter genes in E. coli revealed that a specific sugar ABC transporter gene was required to invade a model gut consortium, highlighting its importance in microbial competition. Together, these findings establish sugar ABC transporters as genomic predictors of microbial community dynamics in response to dietary sugars.

microbiology↗

bioRxiv2025

ALK1-BMPRII agonism by clustering bispecific antibodies treats hereditary hemorrhagic telangiectasia

Hereditary hemorrhagic telangiectasia (HHT) is characterized by arteriovenous malformations (AVMs) and severe bleeding caused by loss-of-function mutations in the ALK1 receptor pathway. We developed clustering agonist bispecific antibodies (BsAbs) targeting ALK1 and its activating partner, the Ser/Thr receptor kinase BMPRII. These BsAbs induced ALK1-BMPRII proximity association, stimulated the downstream Smad1/5/8 signaling cascade, and treated HHT pathologies in various mouse models. BsAb treatment reduced AVM burden by up to 95% in HHT mice, preventing anemia, cardiomegaly, and premature death. The BsAbs also enhanced Smad1/5/8 signaling in endothelial cells derived from HHT patients with ALK1 mutations and prevented retinal AVMs in a newly developed knock-in mouse carrying an HHT-causing ALK1 mutation. These findings establish ALK1-BMPRII agonism as a promising therapeutic strategy for HHT.

cell biology↗

bioRxiv2025

Expanding the utility of transcriptome analysis for mutation detection in high-risk childhood precision oncology

In precision oncology, whole transcriptome sequencing (RNA-seq) excels at identifying oncogenic fusions. Here, using a cohort of 477 high-risk paediatric tumours, we demonstrate that RNA-seq can identify all mutation classes found previously using whole genome sequencing (WGS) and provides additional functional insights into their pathogenicity. By incorporating reference-guided fusion, and reference-free structural variant (SV) detection algorithms with RNA abundance assessment, RNA-seq identified 96% of SVs and resolved 33 complex SVs that WGS failed to identify. Furthermore, RNA-seq identified 92% of all single nucleotide variants and small insertions and deletions. Importantly RNA-seq informed the pathogenicity assessment in 22% of variants through identification of allele specific expression or the functional consequence of splice-altering variants. The utility of RNA-seq extends beyond fusion identification to the interpretation of mutation pathogenicity and the discovery of important mutations that would otherwise go undetected. We propose that RNA-seq is an indispensable companion to WGS in precision medicine.

genomics↗

bioRxiv2024

STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging

We introduce Single-Cell Transcriptomics Analysis and Multimodal Profiling (STAMP), a scalable profiling approach of individual cells. Leveraging transcriptomics and proteomics imaging platforms, STAMP eliminates sequencing costs, to enable single-cell genomics from hundreds to millions of cells at an unprecedented low cost. Stamping cells in suspension onto imaging slides, STAMP supports single-modal (RNA or protein) and multimodal (RNA and protein) profiling and flexible, ultra-high-throughput formats. STAMP allows the analysis of a single or multiple samples within the same experiment, enhancing experimental flexibility, throughput and scale. We tested STAMP with diverse sample types, including peripheral blood mononuclear cells (PBMCs), dissociated cancer cells and differentiated embryonic stem cell cultures, as well as whole cells and nuclei. Combining RNA and protein profiling, we applied immuno-phenotyping of millions of blood cells simultaneously. We also used STAMP to identify ultra-rare cell populations, simulating clinical applications to identify circulating tumor cells (CTCs). Performing in vitro differentiation studies, we further showed its potential for large-scale perturbation studies. Together, STAMP establishes a new standard for cost-effective, scalable single-cell analysis. Without the need for sequencing, STAMP makes high-resolution profiling more affordable and accessible. Designed to meet the needs of research labs, diagnostic cores and pharmaceutical companies, STAMP holds the promise to transform our capacity to map human biology, diagnose diseases and drug discovery.

genomics↗

bioRxiv2022

Survivin is a mechanosensitive cell cycle regulator in vascular smooth muscle cells

Stiffened arteries are a pathology of atherosclerosis, hypertension, and coronary artery disease and a key risk factor for cardiovascular disease events. The increased stiffness of arteries triggers the hypermigration and hyperproliferation of vascular smooth muscle cells (VSMCs), leading to neointimal hyperplasia and accelerated neointima formation, but the mechanism of this trigger is not known. Our analyses of whole-transcriptome microarray data sets from mouse VSMCs cultured on stiff hydrogels simulating arterial pathology and from injured mouse femoral arteries revealed 80 genes that were differentially regulated (74 upregulated and 6 downregulated) relative to expression in control VSMCs cultured on soft hydrogels and in uninjured femoral arteries. A functional enrichment analysis revealed that these stiffness-sensitive genes are linked to cell cycle progression and proliferation. Furthermore, we found that survivin, a member of the inhibitor of apoptosis protein family, mediates stiffness-sensitive cell cycling and proliferation in vivo and in vitro as determined by gene network and pathway analyses, RT-qPCR, and immunoblotting. The stiffness signal is mechanotransduced via FAK and Rac signaling to regulate survivin expression, establishing a regulatory pathway for how the stiffness of the cellular microenvironment affects VSMC behaviors. Our findings indicate that survivin is necessary for VSMC cycling and proliferation and regulates stiffness-responsive phenotypes.

cell biology↗

bioRxiv2022

Survivin Regulates Intracellular Stiffness and Extracellular Matrix Production in Vascular Smooth Muscle Cells

Vascular dysfunction is a common cause of cardiovascular diseases characterized by the narrowing and stiffening of arteries, such as atherosclerosis, restenosis, and hypertension. Arterial narrowing results from the aberrant proliferation of vascular smooth muscle cells (VSMCs) and their increased synthesis and deposition of extracellular matrix (ECM) proteins. These, in turn, are modulated by arterial stiffness, but the mechanism for this is not fully understood. We found that survivin (an inhibitor of apoptosis) is an important regulator of stiffness-mediated ECM synthesis and intracellular stiffness in VSMCs. Whole-transcriptome analysis and cell culture experiments showed that survivin expression is upregulated in injured femoral arteries in mice and in human VSMCs cultured on stiff fibronectin-coated hydrogels. Suppressed expression of survivin in human VSMCs and mouse embryonic fibroblasts decreased the stiffness-mediated expression of ECM components implicated in arterial stiffness, namely, collagen-I, fibronectin, and lysyl oxidase. By contrast, expression of these proteins was upregulated by the overexpression of survivin in human VSMCs cultured on soft hydrogels. Atomic force microscopy analysis showed that suppressed or enhanced expression of survivin decreases or increases intracellular stiffness, respectively. These findings suggest a novel mechanism by which survivin modulates arterial stiffness.

cell biology↗

bioRxiv2022

Dynamic Transcriptomic Network Responses to Divergent Acute Exercise Challenges in Young Adults

Acute exercise elicits dynamic transcriptional changes that, when repeated, form the fundamental basis of adaptations in health, resilience, and performance. While moderate-intensity endurance training combined with conventional resistance training (traditional, TRAD) is often prescribed and recommended by public health guidance, high-intensity training combining maximal-effort intervals with intensive, limited-rest resistance training is a time-efficient alternative that may be used tactically (HITT) to seek whole body health benefits. Mechanisms of action of these distinct doses are incompletely characterized and have not been directly compared. We assessed transcriptome-wide responses in skeletal muscle and circulating extracellular vesicles (EVs) to a single exercise bout in young adults randomized to TRAD (n=21, 12M/9F, 22{+/-}3y) or HITT (n=19, 11M/8F, 22{+/-}2y). Next-generation sequencing captured small, long, and circular RNA in muscle and EVs. Analysis identified differentially expressed transcripts (|log2FC|>1, FDR[≤]0.05) immediately (h0, EVs only), h3, and h24 post-exercise within and between exercise doses. Additionally, all apparently responsive transcripts (FDR<0.2) underwent singular value decomposition to summarize data structures into latent variables (LVs) to deconvolve molecular expression circuits and inter-regulatory relationships. LVs were compared across time and exercise dose. TRAD generally elicited a stronger, more consistent transcriptional response than HITT, but considerable overlap and key differences existed. Findings reveal shared and unique molecular responses to divergent exercise stimuli and lay groundwork toward establishing relationships between protein-coding genes and lesser-understood transcripts that serve regulatory roles in response to exercise. Future work should advance the understanding of these circuits and whether they repeat in other populations or following other types of exercise/stress. NEW AND NOTEWORTHYWe examined small and long transcriptomics in skeletal muscle and serum-derived extracellular vesicles before and after a single exposure to traditional combined exercise (TRAD) and high-intensity tactical training (HITT). Across 40 young adults, we found more consistent protein-coding gene responses to TRAD, whereas HITT elicited differential expression of microRNA enriched in brain regions. Follow-up analysis revealed relationships and temporal dynamics across transcript networks, highlighting potential avenues for research into mechanisms of exercise response and adaptation.

bioinformatics↗

bioRxiv2022

Differential metabolism between biofilm and suspended Pseudomonas aeruginosa cultures in bovine synovial fluid by 2D NMR-based metabolomics

Total joint arthroplasty is a common surgical procedure resulting in improved quality of life; however, a leading cause of surgery failure is periprosthetic joint infection. Periprosthetic infection often involves biofilms, making treatment challenging. Periprosthetic joint infections are difficult to diagnose by traditional culturing methods and there are no clinical biomarkers for the presence of biofilms. Further, the metabolic state of pathogens in the joint space is difficult to diagnose, the mechanism of their tolerance to antibiotics and host defenses is not well understood, and their culturing in the laboratory is challenging. Thus, there is a critical need for improved pathogen- and phenotype-specific diagnosis as well as improved treatment strategies toward better patient outcomes. Here, we present a quantitative, untargeted NMR-based metabolomics strategy for Pseudomonas aeruginosa suspended culture and biofilm phenotypes grown in bovine synovial fluid. We identified 21 unique metabolites as potential markers of P. aeruginosa and one unique marker of the biofilm phenotype in synovial fluid. Significant differences in metabolic pathways were found between the suspended culture and biofilm phenotypes including creatine, glutathione, alanine, and choline metabolism and the tricarboxylic acid cycle. These unique metabolite and pathway differences have the potential to serve as targets for P. aeruginosa and specifically biofilm diagnosis and biofilm control in synovial fluid. Author SummaryJoint replacement surgery is a common procedure frequently required in later stages of life due to damage in the joint. Over one million joint replacement surgeries are performed annually with rates increasing every year. A devastating complication associated with joint replacement is the development of infection around the implant device in the joint space, known as a periprosthetic joint infection. Bacteria in the joint space can form a biofilm, which is a gel-like matrix encasing the cells that increases resistance to treatment and exacerbates chronic infections. A particular challenge for the diagnosis of biofilm-mediated periprosthetic joint infections is the slowly growing nature of biofilm-mediated phenotypes, resulting in frequent failure to detect these bacteria by clinical microbiological culturing methods. Small molecule metabolites are uniquely produced by strains of bacteria in the biofilm versus planktonic or suspended culture phenotype. Identification of metabolites as specific markers of infection and biofilm could allow a new culture-free diagnostic approach to diagnose infection by biofilm. Furthermore, knowledge of metabolic pathway populations in biofilm in joint fluid could point to specific targets to prevent biofilm formation in the joint space.

microbiology↗

bioRxiv2022

Modeling COVID-19 disease biology to identify drug treatment candidates

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, there are a limited number of effective treatments. A variety of drugs that have been approved for other diseases are being tested for the treatment of COVID-19, and thus far only remdesevir, dexamethasone, baricitinib, tofacitinib, tocilizumab, and sarilumab have been recommended by the National Institutes of Health (NIH) COVID-19 Treatment Guidelines Panel for the therapeutic management of hospitalized adults with COVID-19. Using a disease biology modeling approach, we constructed a protein-protein interactome network based on COVID-19- associated genes/proteins described in research literature together with known protein-protein interactions in epithelial cells. Phenotype and disease enrichment analysis of the COVID-19 disease biology model demonstrated strong statistical enrichments consistent with patients clinical presentation. The model was used to interrogate host biological response induced by SARS-CoV-2 and identify COVID-19 drug treatment candidates that may inform on drugs currently being evaluated or provide insight into possible targets for potential new therapeutic agents. We focused on cancer drugs as they are often used to control inflammation, inhibit cell division, and modulate the host microenvironment to control the disease. From the top 30 COVID-19 drug candidates, twelve have a role as an antineoplastic agent, seven of which are approved for human use. Altogether, nearly 40% of the drugs identified by our model have been identified by others for COVID-19 clinical trials. Disease biology modeling incorporating disease-associated genes/proteins discussed in the research literature together with known molecular interactions in relevant cell types is a useful method to better understand disease biology and identify potentially effective therapeutic interventions.

systems biology↗

bioRxiv2022

Rapid aggregation of Staphylococcus aureus in synovial fluid is influenced by synovial fluid concentration, viscosity, and fluid dynamics-with evidence of polymer bridging

Early bacterial survival in the post-surgical joint is still a mystery. Recently, synovial fluid-induced aggregation was proposed as a potential mechanism of bacterial protection upon entry into the joint. As synovial fluid is secreted back into the joint cavity following surgery, rapid fluctuations in synovial fluid concentration, composition, and viscosity occur. These changes, along with fluid movement from post-operative joint motion, will modify the environment and potentially affect the kinetics of aggregate formation. Through this work, we sought to evaluate the influence of exposure time, synovial fluid concentration, viscosity, and fluid dynamics on aggregation. Furthermore, we aimed to elucidate the primary mechanism of aggregate formation by assessing the interaction of bacterial adhesins with synovial fluid polymer, fibrinogen. Following incubation in each simulated post-operative joint condition, the aggregates were imaged using confocal microscopy. Our analysis revealed the formation of two distinct aggregate phenotypes dependent on whether the incubation was conducted under static or dynamic conditions. Using a surface adhesin mutant, we have narrowed down the genetic determinants for synovial fluid aggregate formation and identified essential host polymers required. We report here that synovial fluid-induced aggregation is influenced by various changes specific to the post-surgical joint environment. While we now have evidence that select synovial fluid polymers facilitate bridging aggregation through essential bacterial adhesins, we suspect that their utility is limited by the increasing viscosity under static conditions. Furthermore, dynamic fluid movement recovers the ability of the bacteria with present surface proteins to aggregate under high viscosity conditions, yielding large, globular aggregates. ImportanceInfection is a major complication of knee and hip joint replacement surgery which is used to treat arthritis or joint damage. We have shown that Staphylococcus aureus, a common bacterial pathogen, aggregates upon contact with synovial fluid. Within seconds, the bacterial cells will interact with synovial fluid polymers in the joint fluid through their cell wall adhesins. The rapid formation of these aggregates likely aids in early bacterial survival in the joint-potentially contributing to the likelihood of developing an infection. By strengthening our basic understanding of the mechanics of synovial fluid aggregate formation under clinically relevant conditions, we hope to expand the knowledge of how to prevent or disrupt aggregation and reduce and more successfully treat these joint infections.

microbiology↗

bioRxiv2021

Escaping the Fate of Sisyphus: Assessing Resistome Hybridization Baits for Antimicrobial Resistance Gene Capture

Finding, characterizing, and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive, and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19,933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3,565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. We provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement. Originality-Significance StatementThis work is applicable to a wide range of research. It helps to define conditions under which hybridization capture is useful regarding not only antimicrobial resistance specifically, but also more generally how to assess the ongoing utility of existing bait sets - giving objective criteria for when and by what strategies baits should be updated. We also provide a method for quantifying and comparing antimicrobial resistance genes (ARGs) similar to what is used for RNAseq experiments. This approach improves comparison of ARGs across environments. Thus, the work provides an improved foundation for ARG future studies, while cutting across traditional areas of microbiology and extending beyond.

microbiology↗

bioRxiv2021

ePlant in 2021: New Species, Viewers, Data Sets, and Widgets

ePlant was introduced in 2017 for exploring large Arabidopsis thaliana data sets from the kilometre to nanometre scales. In the past four years we have used the ePlant framework to develop ePlants for 15 agronomically-important species: maize, poplar, tomato, Camelina sativa, soybean, potato, barley, Medicago truncatula, eucalyptus, rice, willow, sunflower, Cannabis sativa, wheat and sugarcane. We also updated the interface to improve performance and accessibility, and added two new views to the Arabidopsis ePlant - the Navigator and Pathways viewers. The former shows phylogenetic relationships between homologs in other species and their expression pattern similarities, with links to view data for those genes in the respective ePlants. The latter shows Plant Reactome metabolic reactions. We also describe new Arabidopsis data sets including single cell RNA-seq data from roots, and how to embed ePlant eFP expression pictographs into any web page.

bioinformatics↗

bioRxiv2021

Alpha-synuclein alters the faecal viromes of rats in a gut-initiated model of Parkinson's disease

Parkinsons disease (PD) is a chronic neurological disorder associated with the misfolding of alpha-synuclein (-syn) into Lewy body aggregates within nerve cells that contribute to their neurodegeneration. Recent evidence suggests -syn aggregation may begin in the gut and travel to the brain along the vagus nerve, with microbes a potential trigger initiating the misfolding of -syn. However, changes in the gut virome in response to -syn alterations have not been investigated. In this study, we show longitudinal changes in the faecal virome of rats administered either monomeric or preformed fibrils (PFF) of -syn directly into their enteric nervous system. Differential changes in rat viromes were observed when comparing monomeric and PFF -syn. The virome {beta}-diversity changes after -syn treatment were compounded by the addition of LPS as an adjunct. Changes in the diversity of rat faecal viromes were observed after one month and did not resolve within the studys five month observational period. Overall, these results suggest that microbiome alterations associated with PD may, partially, be reactive to host -syn associated changes.

microbiology↗