Biology subjects

Hamilton, T.

Publications and source records attributed to Hamilton, T..

15 recordsLinked to original sources

bioRxiv2026

Traumatic Brain Injury induces persistent behavioural deficits that are rescued by the antiepileptic drug Levetiracetam

Traumatic Brain Injury (TBI) produces acute challenges including seizures and neuroinflammation, and these then exacerbate lifelong difficulties including epilepsy, dementias, and anxiety. Applying antiepileptic drugs (AED) to manage acute seizures after TBI has promise to slow these progressive deficits. Levetiracetam (LEV) is an AED that mitigates seizures and neuroinflammation in various contexts. Here, we explore the utility of the larval zebrafish TBI model by documenting long term behavioural deficits (if any) induced by larval neurotrauma and whether they can be mitigated by LEV. We induced a mild blast TBI in three days-post-fertilization larvae, administered LEV (3 x 10-2 mM) for two days, and assessed behaviour in adults (9 +/- 1 or 22 +/- 1 months later). In open field tests, adult zebrafish that experienced TBI as larvae exhibited increased anxiety-like behaviour compared to sham-treated larvae, but this resolved by later adulthood. LEV treatment immediately following larval TBI did not significantly alter these outcomes. Novel object approach tests revealed sustained deficits in exploratory behaviour: adults that experienced larval TBI spent significantly less time investigating a novel object compared to sham controls throughout adulthood; this suggests long-term alterations in fear-related cognitive processing or threat evaluation. LEV treatment increased time spent near the novel object in early adulthood, but not later adulthood, suggesting a time-dependent efficacy of early pharmacological intervention. In sum, the larval zebrafish TBI model is suitable for investigating the progression and treatment of behavioural deficits. LEV showed only limited efficacy, but adjusted AED regimens have potential to mitigate long-term behavioural outcomes of TBI.

neuroscience↗

bioRxiv2026

Elevation shapes alpine snow algal blooms and their influence on albedo reduction

Snow algae darken snowpacks and accelerate melt worldwide. Although elevation strongly structures the physical conditions of mountain snowfields, its influence on snow algal traits and their effects on snowpack reflectance remains unclear. Here, we investigated snow algal composition, cellular traits, and optical properties in summer blooms across an elevational range of 1,059-3,423 m a.s.l. in the western United States, spanning two elevational gradients in the Cascade Range (CA, OR, WA) and the Rocky Mountains (UT, WY, MT). Across all samples (n = 294), snow albedo declined strongly with increasing algal cell density, indicating that total biomass, rather than pigment composition, is the dominant driver of albedo reduction. However, within Sanguina-dominated blooms (117 of 206 samples bloom samples identified across the dataset), neither relative abundance nor algal cell density varied systematically with elevation. Instead, mean cell size increased with elevation, while per-cell pigment concentrations declined, leading to higher astaxanthin:chlorophyll-a ratios driven primarily by reductions in chlorophyll-a per cell. These elevation-dependent shifts in cell size and pigment balance were consistent across both mountain ranges, indicating phenotypic acclimation to increasing environmental stress with elevation. Together, these findings link cellular-scale acclimation of a widespread snow alga to radiative processes shaping mountain snowpacks.

microbiology↗

bioRxiv2026

Environmental filtering, dispersal limitation, and competition control the distribution of acidophilic iron oxidizers

Acid mine drainage is a global pollution problem characterized by low pH and high concentrations of metals. Active remediation is often cost-prohibitive, but Fe(II) oxidizing microbes may be used for passive bioremediation. To leverage these species, we must understand the factors that control their distribution. Here, we examine the environmental and ecological factors that control these species with the aim of determining if microbial seeding is a viable remediation strategy. Although stochastic processes appear to control the distribution of majority of taxa inhabiting AMD ecosystems, the distribution of Fe(II) oxidizers is driven by environmental filtering and competition. The abundance of all the major Fe(II) oxidizing genera have significant relationships with pH, with pH explaining 10 - 38% of the variation in their abundance. The genera appear to have pH preferences with Acidithiobacillus and Leptospirillum preferring environments below pH 3, Gallionella, Sideroxydans, and Ferritrophicum preferring environments above pH 3.5, and Ferrovum preferring intermediate pH environments. Once the effect of pH is removed, genera that share pH preferences are negatively correlated, indicating that they are likely competing for the Fe(II) oxidizing niche in their preferred environments. Communities are also shaped by dispersal limitation, which suggests that microbial seeding is possible in these environments. Future seeding attempts should consider species interactions and ecology more generally to inform their efforts.

microbiology↗

bioRxiv2026

Prostaglandin E2 Reverses Myofibroblast Differentiation in Eosinophilic Esophagitis

Background & AimsUnchecked inflammation in Eosinophilic esophagitis (EoE) leads to esophageal fibrosis and eventual stricture. Differentiated fibroblasts, termed myofibroblasts, are the main effector cells in fibrosis, responsible for secreting extracellular matrix proteins leading to tissue stiffness. Regulating myofibroblasts has not been explored as a therapeutic possibility in the fibrostenotic esophagus. Herein, we aim to investigate the efficacy of Prostaglandin E2 (PGE2) in dedifferentiation of the EoE myofibroblast. MethodsWe evaluated the efficacy and mechanism of myofibroblast dedifferentiation using fetal esophageal fibroblasts (FEF3), patient-derived fibroblasts, and a murine model of EoE. ResultsFibrosis markers (SMA, FN1, and COL1A1) and contractility of myofibroblasts were significantly decreased by PGE2 via the cAMP pathway. PGE2 treatment decreased nuclear accumulation of phospho-Smad2/3-YAP complex and induced phospho-YAP proteasomal degradation. Transcriptome analyses of FEF3 treated with TGF{beta} or PGE2 revealed that the Integrin1 pathway, and specifically thrombospondin 1 (THBS-1), was significantly upregulated by TGF{beta} and downregulated by PGE2, as supported by pseudo-bulk single-cell RNA-seq of EoE biopsies. THBS-1 was shown to be regulated by PGE2 via the cAMP/YAP pathway, and its knockdown induced myofibroblasts dedifferentiation. In a murine model of EoE, Butaprost, agonist of the E-prostanoid G protein-coupled receptor 2, treatment significantly reduced the expression of THBS-1, SMA, and FN1 along with a decrease in YAP nuclear translocation. Additionally, collagen fiber organization in the lamina propria was markedly reduced. ConclusionPGE2 promotes dedifferentiation of myofibroblasts in EoE via the cAMP/YAP/ THBS-1 pathway. Our data suggest that PGE2 is a promising treatment strategy for EoE with stenosis. What You Need to KnowO_ST_ABSBackground and ContextC_ST_ABSIn Eosinophilic esophagitis, unchecked inflammation and tissue stiffness drives fibroblast differentiation and fibrostenosis of the esophagus, yet targeting myofibroblasts as regulators of extracellular matrix deposition in fibrostenotic disease remains clinically unexplored. New FindingsProstaglandin E2 promotes dedifferentiation of myofibroblasts in eosinophilic esophagitis via the cAMP/YAP pathway, with Thrombospondin-1 identified as a critical YAP regulated target driving fibrostenosis. LimitationsThis study focused on fibroblast-specific mechanisms. The effects of PGE2 on esophageal epithelial differentiation, barrier function, and immune cell recruitment in EoE remain to be determined. Clinical Research RelevanceThis study demonstrates proof-of-concept that pharmacological reversal of established fibrosis is achievable in EoE. PGE2 and its EP2-selective agonists represent translatable therapeutic targets for fibrostenotic EoE--a patient population that remains treatment-refractory to current immunosuppressive approaches. Basic Research RelevanceThe cAMP/YAP/THBS-1 signaling in fibroblasts emerges as a critical therapeutic target for esophageal fibrosis. Importantly, this work demonstrates that terminally differentiated myofibroblasts retain remarkable plasticity and can dedifferentiate--challenging the paradigm that fibrosis is irreversible.

cell biology↗

bioRxiv2025

DeepAtlas: a tool for effective manifold learning

Manifold learning builds on the "manifold hypothesis," which posits that data in high-dimensional datasets are drawn from lower-dimensional manifolds. Current tools generate global embeddings of data, rather than the local maps used to define manifolds mathematically. These tools also cannot assess whether the manifold hypothesis holds true for a dataset. Here, we describe DeepAtlas, an algorithm that generates lower-dimensional representations of the datas local neighborhoods, then trains deep neural networks that map between these local embeddings and the original data. Topological distortion is used to determine whether a dataset is drawn from a manifold and, if so, its dimensionality. Application to test datasets indicates that DeepAtlas can successfully learn manifold structures. Interestingly, many real datasets, including single-cell RNA-sequencing, do not conform to the manifold hypothesis. In cases where data is drawn from a manifold, DeepAtlas builds a model that can be used generatively and promises to allow the application of powerful tools from differential geometry to a variety of datasets.

systems biology↗

bioRxiv2024

Laboratory experiments suggests limited impact of increased nitrogen deposition on snow algae blooms

Snow algal blooms decrease snow albedo and increase local melt rates. However, the causes behind the size and frequency of these blooms are still not well understood. One factor that is likely contributing is nutrient availability, specifically nitrogen (N) and phosphorus (P). However, the nutrient requirements of the taxa responsible for these blooms is not known. Here, we assessed the growth of three commercial strains of snow algae under 24 different nutrient treatments that varied in both absolute and relative concentrations of N and P. After 38 days of incubation, we measured total biomass and cell size and estimated their effective albedo reduction surface (EARS). Snow algal strains tended to respond similarly and achieved bloom-like cell densities over a wide range of NP conditions. However, the molar ratio of N:P at which maximum biomass was achieved was between 4 and 7. Our data indicate a high requirement for P for snow algae and suggest that additional N inputs into the ecosystem may not significantly impact the productivity and abundance of snow algae blooms. This highlights P availability as a critical factor influencing the frequency and extent of snow algae blooms and their potential contribution to snow melt through altered albedo.

microbiology↗

bioRxiv2024

Maintenance of haematopoietic stem cells by JAK inhibition and increased tyrosine-unphosphorylated STAT5

Normal and malignant hematopoietic stem cells (HSCs) are controlled by extracellular cues including cytokine signalling through the JAK/STAT pathway. Here, we show that STAT5-deficient HSCs exhibit an unusual phenotype: while reduced multi-lineage repopulation and reduced self-renewal are commonly associated with overproliferation and exhaustion, they are instead associated with reduced cell-cycle progression and increased differentiation in STAT5-deficient HSCs. Mechanistic studies show that unphosphorylated-STAT5 (uSTAT5) contributes to this phenotype by constraining HSC differentiation, promoting HSC maintenance and upregulating transcriptional programs associated with stemness. The JAK1/2 inhibitor ruxolitinib increases levels of uSTAT5, constrains differentiation and proliferation of murine HSCs, promotes their maintenance and upregulates transcriptional programs associated with stemness. Ruxolitinib also enhances clonogenicity of normal human HSPCs, CALR-mutant murine HSCs and HSPCs from patients with myelofibrosis. Our results therefore reveal a previously unrecognized role for uSTAT5 in controlling HSC function, highlight JAK inhibition as a strategy for enhancing HSC function and provide insights into the failure of JAK inhibitors to eradicate myeloproliferative neoplasms.

cell biology↗

bioRxiv2023

Novel metrics reveal new structure and unappreciated heterogeneity in C. elegans development

High throughput experimental approaches are increasingly allowing for the quantitative description of cellular and organismal phenotypes. Distilling these large volumes of complex data into meaningful measures that can drive biological insight remains a central challenge. In the quantitative study of development, for instance, one can resolve phenotypic measures for single cells onto their lineage history, enabling joint consideration of heritable signals and cell fate decisions. Most attempts to analyze this type of data, however, discard much of the information content contained within lineage trees. In this work we introduce a generalized metric, which we term the branch distance, that allows us to compare any two embryos based on phenotypic measurements in individual cells. This approach aligns those phenotypic measurements to the underlying lineage tree, providing a flexible and intuitive framework for quantitative comparisons between, for instance, Wild-Type (WT) and mutant developmental programs. We apply this novel metric to data on cell-cycle timing from over 1300 WT and RNAi-treated Caenorhabditis elegans embryos. Our new metric revealed surprising heterogeneity within this data set, including subtle batch effects in WT embryos and dramatic variability in RNAi-induced developmental phenotypes, all of which had been missed in previous analyses. Further investigation of these results suggests a novel, quantitative link between pathways that govern cell fate decisions and pathways that pattern cell cycle timing in the early embryo. Our work demonstrates that the branch distance we propose, and similar metrics like it, have the potential to revolutionize our quantitative understanding of organismal phenotype.

developmental biology↗

bioRxiv2022

A lack of distinct cell identities in single-cell measurements: revisiting Waddington's landscape

The prevailing interpretation of Waddingtons landscape is that attractors in gene expression space produce and stabilize distinct cell types. This notion is often applied in single-cell omics, where transcriptome data is clustered to produce models of cell types. Here we apply graph theory to characterize the distribution of cells in epigenetic space, using data from various tissues, organisms, and single-cell omics technologies. We find that cells of different types exist in the same regions of epigenetic space, with highly heterogeneous density distributions that are inconsistent with expected densities near an attractor. The lack of attractor structure could not be explained by technical noise, scale variance among genes, nor the subset of genes that were used; nor could it be rescued by any standard set of transformations. These findings pose a challenge for the robust analysis of single-cell data and open the possibility for alternative explanations of canalization during development.

systems biology↗

bioRxiv2022

Summer dynamics of microbial diversity on a mountain glacier

Under climate change, glaciers are rapidly receding worldwide. A melting cryosphere will dramatically alter global sea levels, carbon cycling, and water resource availability. Glaciers also host rich biotic communities that are dominated by microbial diversity and this biodiversity can impact surface albedo, thereby driving a feedback loop between biodiversity and cryosphere melt. However, the microbial diversity of glacier ecosystems remains largely unknown outside of major ice sheets, particularly from a temporal perspective. Here, we characterized temporal dynamics of bacteria, eukaryotes, and algae on the Paradise Glacier, Mount Rainier, USA, over the summer melt season. During our study, the glacier surface steadily darkened as seasonal snow melted and darkening agents accumulated until new snow fell in late September. From a community-wide perspective, the bacterial community remained generally constant and eukaryotes exhibited a clear temporal progression of community change while fungal diversity was intermediate. Individual taxonomic groups, however, exhibited considerable stochasticity. We found little support for our a priori prediction that autotroph abundance would peak before heterotrophs. Notably, two different trends in snow algae emerged--an abundant early-and late-season OTU with a different mid-summer OTU that peaked in August. Overall, our results highlight the need for temporal sampling to clarify microbial diversity on glaciers and that caution should be exercised when interpreting results from single or few timepoints.

microbiology↗

bioRxiv2021

Comparative genomics of Acinetobacter baumannii and therapeutic bacteriophages from a patient undergoing phage therapy

In 2016, a 68-year-old patient with a disseminated multi-drug resistant Acinetobacter baumannii infection was treated using lytic bacteriophages in one of the first modern human clinical uses of phage therapy in the United States. Due to the emergency nature of the treatment there was little time to thoroughly characterize the phages used in this intervention or the pathogen itself. Here we report the genomes of the nine phages used for treatment and three strains of A. baumannii isolated prior to and during treatment. The eight phages used in the initial treatment were found to be a group of closely related T4-like myophages; the ninth phage, AbTP3{Phi}1, was found to be an unrelated Fri1-like podophage. Analysis of 19 A. baumannii isolates collected before and during phage treatment showed that resistance to the T4-like phages appeared as early as two days following the start of treatment. Three A. baumannii strains (TP1, TP2 and TP3) collected before and during treatment were sequenced to closure, and all contained a 3.9 Mb chromosome of sequence type 570 with a KL116 capsule locus and identical 8.7 kb plasmids. Phage-insensitive mutants of A. baumannii strain TP1 were generated in vitro and the majority of identified mutations were located in the bacterial capsule locus. The presence of the same mutation in both the in vitro mutants and in phage-insensitive isolates TP2 and TP3, which evolved in vivo during phage treatment, indicate that in vitro investigations can produce results that are relevant and predictive for the in vivo environment.

microbiology↗

bioRxiv2021

Binomial models uncover biological variation during feature selection of droplet-based single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) aims to characterize how variation in gene expression is distributed across cells in tissues and organisms. Yet, effective comprehension of these extremely high-dimensional datasets remains a critical barrier to progress in biological research. In standard analyses of scRNA-seq data, feature selection steps aim to reduce the dimensionality of the data by focusing on a subset of genes that are the most biologically variable across a set of cells. Ideally, these features provide the genes that are the most informative for partitioning groups of transcriptionally distinct cells, each representing a different cell type or identity. In this work, we propose a simple feature selection model where a binomial sampling process for each mRNA species produces a null model of technical variation. To compare our model to existing methods, we use scRNA-seq data where cell identities have been established a priori for each cell, and characterize whether different feature sets retain biologically varying genes, distort neighborhood structures, and allow popular clustering algorithms to partition groups of cells into their established classes. We find that our model of biological variation, which we term "Differentially Distributed Genes" or DDGs, outperforms existing methods, and enables dimensionality reduction without loss of critical structure within the data set.

bioinformatics↗

bioRxiv2020

Distribution and functional potential of photoautotrophic bacteria in alkaline hot springs

Alkaline hot springs in Yellowstone National Park (YNP) provide a framework to study the relationship between photoautotrophs and temperature. Previous work has focused on cyanobacteria (oxygenic phototrophs), but anoxygenic phototrophs are critical parts of the evolutionary history of life on Earth and and are abundant across temperature gradients in alkaline hot springs. However, many questions remain regarding the ecophysiology of anoxygenic photosynthesis due to the taxonomic and metabolic diversity of these taxa. Here, we examined the distribution of genes involved in phototrophy and carbon and nitrogen fixation in eight alkaline (pH 7.3-9.4) hot spring sites approaching the upper temperature limit of photosynthesis (~72{degrees}C) in YNP using metagenome sequencing. Genes associated with cyanobacteria are abundant throughout our data and more diverse at temperatures > 63{degrees}C, genes for autotrophic Chloroflexi are more abundant in sites > 63{degrees}C and genes associated with phototrophic Chloroflexi are abundant throughout. Additionally, we recovered deep branching nitrogen fixation genes from our metagenomes, which could inform the evolutionary history of nitrogen fixation. Lastly, we recovered 25 metagenome assembled genomes of Chloroflexi. We found distinct differences in carbon fixation genes in Roseiflexus and Chloroflexus bins, in addition to several novel Chloroflexi bins. Our results highlight the physiological diversity and evolutionary history of the understudied, anoxygenic autotrophic Chloroflex. Furthermore, we provide evidence that genes involved in nitrogen fixation in Chloroflexi is more widespread than previously assumed. IMPORTANCEPhotosynthetic bacteria in hot springs are of great importance to both microbial evolution and ecology because they are responsible for the rise of oxygen and are critical to nutrient cycling. While a large body of work has focused on the oxygenic photosynthesis in cyanobacteria, many questions remain regarding the metabolic potential of anoxygenic phototrophs but are further compounded by their metabolic and taxonomic diversity. Here, we have recovered several novel metagenome bins and quantified the distribution of key genes involved in carbon and nitrogen metabolism in both oxygenic and anoxygenic phototrophs. Together, our results add to the body of work focusing on photosynthetic bacteria in hot springs in Yellowstone National Park.

microbiology↗

bioRxiv2019

Intra-genus metabolic diversity facilitates co-occurrence of multiple Ferrovum species at an acid mine drainage site

BackgroundFerrovum spp. are abundant in acid mine drainage sites globally where they play an important role in biogeochemical cycling. All known taxa in this genus are Fe(II) oxidizers. Thus, co-occurring members of the genus could be competitors within the same environment. However, we found multiple, co-occurring Ferrovum spp. in Cabin Branch, an acid mine drainage site in the Daniel Boone National Forest, KY.\n\nResultsHere we describe the distribution of Ferrovum spp. within the Cabin Branch communities and metagenome assembled genomes (MAGs) of two new Ferrovum spp.. In contrast to previous studies, we recovered multiple 16S rRNA gene sequence variants suggesting the commonly used 97% cutoff may not be appropriate to differentiate Ferrovum spp. We also retrieved two nearly-complete Ferrovum spp. genomes from metagenomic data. The genomes of these taxa differ in several key ways relating to nutrient cycling, motility, and chemotaxis.\n\nConclusionsPreviously reported Ferrovum genomes are also diverse with respect to these categories suggesting that the genus Ferrovum contains substantial metabolic diversity. This diversity likely explains how the members of this genus successfully co-occur in Cabin Branch and why Ferrovum spp. are abundant across geochemical gradients.

microbiology↗

bioRxiv2019

A novel metric reveals previously unrecognized distortion in dimensionality reduction of scRNA-Seq data

High-dimensional data are becoming increasingly common in nearly all areas of science. Developing approaches to analyze these data and understand their meaning is a pressing issue. This is particularly true for single-cell RNA-seq (scRNA-seq), a technique that simultaneously measures the expression of tens of thousands of genes in thousands to millions of single cells. Popular analysis pipelines significantly reduce the dimensionality of the dataset before performing downstream analysis. One problem with this approach is that dimensionality reduction can introduce substantial distortion into the data, particularly by disrupting the local neighborhoods of certain points. Since many scRNA-seq analyses like cell type clustering or trajectory inference rely on these near-neighbor relationships, distortion in this aspect of the data could significantly influence the outcomes of these analyses. Here, we introduce a straightforward approach to quantifying this distortion by comparing the local neighborhoods of points before and after dimensionality reduction. We found that popular techniques like t-SNE and UMAP introduce substantial distortion even for simple simulated data sets. For scRNA-seq data, we found the distortion in local neighborhoods was often greater than 95%, and that there was no consistent set of neighborhoods across the various steps in the consensus scRNA-seq analysis pipeline. We also found that this distortion had profound impacts on the outcomes of cell type clustering and other downstream analyses. Our findings suggest that caution must be applied when interpreting results in terms of 2-D visualizations produced by tools like UMAP, and that there is a critical need for new dimensionality reduction tools that more effectively preserve the local topological structure of the data.

bioinformatics↗