Biology subjects

Quinn, R.

Publications and source records attributed to Quinn, R..

8 recordsLinked to original sources

bioRxiv2025

ClusterApp to visualize, organize, and navigate metabolomics data

BackgroundClustering analysis is a foundational step in exploratory data analysis workflows, with dimensionality reduction methods commonly used to visualize multidimensional data in lower-dimensional spaces and infer sample clustering. Principal Component Analysis (PCA) is widely applied in metabolomics but is often suboptimal for clustering visualization. Metabolomics data often require specialized manipulations such as blank removal, quality control adjustments, and data transformations that demand efficient visualization tools. However, the lack of user-friendly tools for clustering without computational expertise presents a challenge for metabolomics researchers. ClusterApp addresses this gap as a web application that performs Principal Coordinate Analysis (PCoA), expanding clustering alternatives in metabolomics. Built on a QIIME 2 Docker image, it enables PCoA computation and Emperor plot visualization. The app supports data input from GNPS, GNPS2, or user-provided spreadsheets. Freely available, ClusterApp can be locally installed as a Docker image or integrated into Jupyter notebooks, offering accessibility and flexibility to diverse users. ResultsTo demonstrate the data preprocessing techniques available in ClusterApp, we analyzed two Liquid Chromatography coupled to Tandem Mass Spectrometry (LC-MS/MS) metabolomics datasets: one exploring metabolomic differences in mouse tissue samples and another investigating coral life history stages. Among the dissimilarity measures available, the Bray-Curtis measure effectively highlighted key metabolomic variations and patterns across both datasets. Targeted filtering significantly enhanced data reliability by retaining biologically relevant features, 10,617 in the coral dataset and 7,341 in the mouse dataset while eliminating noise. The combination of Total Ion Current (TIC) normalization and auto-scaling improved clustering resolution, revealing distinct separations in tissue types and life stages. ClusterApps flexible features, such as customizable blank removal and group selection, provided tailored analyses, enhancing visualization and interpretation of metabolomic profiles. ConclusionClusterApp addresses the need for accessible, dynamic tools for exploratory data analysis in metabolomics. By coupling data transformation capabilities with PCoA on multiple dissimilarity matrices, it provides a versatile solution for clustering analysis. Its web interface and Docker-based deployment offer flexibility, accommodating a wide range of use cases through graphical or programmatic interactions. ClusterApp empowers researchers to uncover meaningful patterns and relationships in metabolomics data without requiring cumbersome data manipulation or advanced bioinformatics expertise.

bioinformatics↗

bioRxiv2024

Data-driven analysis identifies female-specific social modulation deficit after chronic social defeat stress

BackgroundChronic social defeat stress is a widely used depression model in male mice. Several proposed adaptations extend this model to females with variable, often marginal effects. We examine the if widely used male-defined metrics of stress are suboptimal in females and reveal sex-specific adaptations. MethodsUsing a data-driven method we comprehensively classified social interaction behavior in 761 male and female mice after chronic social witness/defeat stress, examining social modulation of behavioral frequencies and associations with conventional metrics (i.e., social interaction (SI) ratio). ResultsSocial stress induces distinct behavioral adaptation patterns in males and females. SI ratio leads to underpowered analyses in females with limited utility to differentiate susceptibility/resilience. Data-driven analyses reveal failure of social adaptation in stressed female mice that is captured in attenuated velocity change from no target to target tests ({Delta}Velocity) and validate this in three female social stress models. Combining SI ratio and {Delta}Velocity optimally differentiates susceptibility/ resilience in females and this metric reveals resilient-specific adaptation in a resilience-associated neural circuit in female mice. ConclusionsWe demonstrate that psychological or physical social defeat stress induces similar deficits in females that is qualitatively distinct from male deficits and inadequately sampled by male-defined metrics. We identify modulation of locomotion as a robust and easily implementable metric for rigorous research in female mice. Overall, our findings highlight the need to critically evaluate sex differences in behavior and implement sex-based considerations in preclinical model design.

neuroscience↗

bioRxiv2023

dFLASH; dual FLuorescent transcription factor Activity Sensor for Histone integrated live-cell reporting and high-content screening

Live-cell reporting of regulated transcription factor (TF) activity has a wide variety of applications in synthetic biology, drug discovery, and functional genomics. As a result, there is high value in the generation of versatile, sensitive, robust systems that can function across a range of cell types and be adapted toward diverse TF classes. Here we present the dual FLuorescent transcription factor Activity Sensor for Histone integrated live-cell reporting (dFLASH), a modular sensor for TF activity that can be readily integrated into cellular genomes. We demonstrate readily modified dFLASH platforms that homogenously, robustly, and specifically sense regulation of endogenous Hypoxia Inducible Factor (HIF) and Progesterone receptor (PGR) activities, as well as regulated coactivator recruitment to a synthetic DNA-Binding Domain-Activator Domain fusion proteins. The dual-colour nuclear fluorescence produced normalised dynamic live-cell TF activity sensing with facile generation of high-content screening lines, strong signal:noise ratios and reproducible screening capabilities (Z = 0.68-0.74). Finally, we demonstrate the utility of this platform for functional genomics applications by using CRISPRoff to modulate the HIF regulatory pathway, and for drug screening by using high content imaging in a bimodal design to isolate activators and inhibitors of the HIF pathway from a [~]1600 natural product library.

synthetic biology↗

bioRxiv2021

Intrapopulation adaptive variance supports selective breeding in a reef-building coral

The long-term persistence of coral reefs under climate change requires heritable drivers of thermal tolerance which support adaptation. The genomic basis of thermal tolerance has been evaluated across strong spatial and environmental gradients, but this variation also exists within populations due to neutral evolutionary processes. Small scale heterogeneity in coral bleaching is ubiquitous, so we used corals from a single reef to examine genomic signatures of bleaching performance, their biochemical correlates and the downstream consequences of selective breeding. In the absence of directional selection due to environmental differences, adult corals from a single population exhibit strong genomic patterns related to natural bleaching tolerance and symbiosis state, including functional differentiation in signaling pathways, protein and amino acid modification and metabolism. Conversely, growth, development and innate immune responses did not distinguish bleaching tolerance in adult corals. The genomic signatures of these gene ontologies influence biochemical patterns in healthy corals, primarily via cell-signaling pathway impacts on peptides and amino acids. Thermal tolerance in this population is highly heritable, with significantly higher survivorship under temperature stress in larvae and juveniles reared from thermally tolerant parents than those from sensitive parents. Using a select and re-sequence approach, certain gene ontologies were reproducibly impacted, while antioxidant activity and cell signaling ontologies were disproportionately selected in thermally tolerant corals, demonstrating the genomic drivers of successful selective breeding. These data show that intrapopulation variance in the absence of historical selection supports the adaptive capacity of coral reefs under climate change.

ecology↗

bioRxiv2020

A three-dimensional musculoskeletal model of the dog

Dogs are an interesting object of investigation because of the wide range of body size, body mass, and physique. In the last several years, the number of clinical and biomechanical studies on dog locomotion has increased. However, the relationship between body structure and joint load during locomotion, as well as between joint load and degenerative diseases of the locomotor system (e.g. dysplasia), are not sufficiently understood. In vivo measurements/records of joint forces and loads or deep/small muscles are complex, invasive, and sometimes ethically questionable. The use of detailed musculoskeletal models may help in filling that knowledge gap. We describe here the methods we used to create a detailed musculoskeletal model with 84 degrees of freedom and 134 muscles. Our model has three key-features: Three-dimensionality, scalability, and modularity. We tested the validity of the model by identifying forelimb muscle synergies of a beagle at walk. We used inverse dynamics and static optimization to estimate muscle activations based on experimental data. We identified three muscle synergy groups by using hierarchical clustering. Predicted activation patterns exhibited good agreement with experimental data for most of the forelimb muscles. We expect that our model will speed up the analysis of how body size, physique, agility, and disease influence joint neuronal control and loading in dog locomotion.

bioengineering↗

bioRxiv2019

Repository-scale Co- and Re-analysis of Tandem Mass Spectrometry Data

Metabolomics data are difficult to find and reuse, even in public repositories. We, therefore, developed the Reanalysis of Data User (ReDU) interface (https://redu.ucsd.edu/), a community- and data-driven approach that solves this problem at the repository scale. ReDU enables public data discovery and co- or re-analysis via uniformly formatted, publicly available MS/MS data and metadata in the Global Natural Product Social Molecular Networking Platform (GNPS), consistent with findable, accessible, interoperable, and reusable (FAIR) principles.1

bioinformatics↗

bioRxiv2019

MASST: A Web-based Basic Mass Spectrometry Search Tool for Molecules to Search Public Data.

CorrespondenceWe introduce a web-enabled small-molecule mass spectrometry (MS) search engine. To date, no tool can query all the public small-molecule tandem MS data in metabolomics repositories, greatly limiting the utility of these resources in clinical, environmental and natural product applications. Therefore, we introduce a Mass Spectrometry Search Tool (MASST) (https://proteosafe-extensions.ucsd.edu/masst/), that enables the discovery of molecular relationships among accessible public metabolomics and natural product tandem mass spectrometry data (MS/MS).

bioinformatics↗

bioRxiv2018

Untargeted Mass Spectrometry-Based Metabolomics Tracks Molecular Changes in Raw and Processed Foods and Beverages

A major aspect of our daily lives is the need to acquire, store and prepare our food. Storage and preparation can have drastic effects on the compositional chemistry of our foods, but we have a limited understanding of the temporal nature of processes such as storage, spoilage, fermentation and brewing on the chemistry of the foods we eat. Here, we performed a temporal analysis of the chemical changes in foods during common household preparations using untargeted mass spectrometry and novel data analysis approaches. Common treatments of foods such as home fermentation of yogurt, brewing of tea, spoilage of meats and ripening of tomatoes altered the chemical makeup through time, through both chemical and biological processes. For example, brewing tea altered its composition by increasing the diversity of molecules, but this change was halted after 4 min of brewing. The results indicate that this is largely due to differential extraction of the material from the tea and not modification of the molecules during the brewing process. This is in contrast to the preparation of yogurt from milk, spoilage of meat and the ripening of tomatoes where biological transformations directly altered the foods molecular composition. Comprehensive assessment of chemical changes using multivariate statistics showed the varied impacts of the different food treatments, while analysis of individual chemical changes show specific alterations of chemical families in the different food types. The methods developed here represent novel approaches to studying the changes in food chemistry that can reveal global alterations in chemical profiles and specific transformations at the chemical level.\n\nO_LSTHighlightsC_LSTO_LIWe created a reference data set for tomato, milk to yogurt, tea, coffee, turkey and beef.\nC_LIO_LIWe show that normal preparation and handling affects the molecular make-up.\nC_LIO_LITea preparation is largely driven by differential extraction.\nC_LIO_LIFormation of yogurt involves chemical transformations.\nC_LIO_LIThe majority of meat molecules are not altered in 5 days at room temperature.\nC_LI

biochemistry↗