Biology subjects

Johnson, C. G. M.

Publications and source records attributed to Johnson, C. G. M..

3 recordsLinked to original sources

bioRxiv2025

EcoKMER: One-stop shop for spatio-temporal metagenomic exploration using DataFed

Spatially distributed environmental sampling generates highly complex and multidimensional datasets illuminating key insights into microbial diversity, evolutionary-coevolutionary processes, and host-pathogen interactions. While these sampling methods generate high value datasets, dataset size, the dataset integration, visualization, analysis, and provenance tracking present significant bottlenecks to scientific discovery. To address this bottleneck, we developed EcoKMER, an R-Shiny front-end application designed to streamline metagenomic data accessibility and provide geospatial context to data in support of hypothesis-driven investigations into environmental sampling, supported by DataFed as its back-end data management platform. EcoKMER enables interactive visualization and filtering of harmonized metagenomic data and metadata using an interoperable approach, allowing users to extract spatially distributed sample-based metadata on top of environmental parameters such as geolocation, temperature, pH, for investigating ecological changes across time and space enhancing sample processing methods. As an example, we deployed this tool to track analysis of metagenomes from the organisms in the Salish Sea Estuary, consistent with existing community-accepted standards. Built on top of DataFed, a flexible and robust scientific data management system built for data lakehouse architectures, EcoKMER is positioned as a powerful tool to improve sampling strategy decision making, accelerate new insights for collaborative biological and environmental research, and fostering AI-ready analyses designed to enhance discovery and guidance for bioeconomic engineering. The published manuscript is available at https://www.osti.gov/biblio/3412938

bioinformatics↗

bioRxiv2025

Sampling Microbial Dynamics in the Salish Sea Estuary: Evaluating Methods to Capture Cyanobacteria and Cyanophage

Picocyanobacteria from the genera Prochlorococcus and Synechococcus thrive across the globe in aqueous environments, have relatively small genomes, and have growth dynamics regulated by both viral interactions and abiotic conditions, making them excellent model organisms for exploring host-pathogen coevolution. The Salish Sea, located in the Western coastal waters bordering the USA and Canada, is at the current northern boundary (defined by Prochlorococcus versus Synechococcus prevalence ratios) of the range of Prochlorococcus. Predictions suggest that this boundary will shift northward as warmer waters move northward, providing an excellent system to study host-pathogen dynamics and coevolution in a changing environmental context. In preparation for such studies, we developed and refined methods to sample and sequence cyanobacteria, cyanophages, and their abiotic environment. In addition to basic methodological questions focused on the physical sampling, filtering, viral precipitation, DNA extraction, and technical replicability, we explored how well our filtering and extraction protocols enrich for our main target, picocyanobacteria. The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons. Our preferred final protocol at the conclusion of these experiments based on yield and processing time is presented. We recovered substantial Prochlorococcus, Synechococcus and amoeba-like sequences in most samples, and preliminary exploration of relative taxon sequence read recoveries across locations, over time, and tidal conditions are also discussed. Approaches described here may be useful to other efforts such as harmful algal bloom monitoring, species isolation and enrichment, water quality assessments, anti-viral discovery, and understanding picocyanobacterial population changes over space and time.

microbiology↗

bioRxiv2021

ChemChaste: Simulating spatially inhomogenous biochemical reaction-diffusion systems for modelling cell-environment feedbacks

MotivationSpatial organisation plays an important role in the function of many biological systems, from cell fate specification in animal development to multi-step metabolic conversions in microbial communities. The study of such systems benefits from the use of spatially explicit computational models that combine a discrete description of cells with a continuum description of one or more chemicals diffusing within a surrounding bulk medium. These models allow the in silico testing and refinement of mechanistic hypotheses. However, most existing models of this type do not account for concurrent bulk and intracellular biochemical reactions and their possible coupling. ResultsHere, we describe ChemChaste, an extension for the open-source C++ computational biology library Chaste. ChemChaste enables the spatial simulation of both multicellular and bulk biochemistry by expanding on Chastes existing capabilities. In particular, ChemChaste enables: (i) simulation of an arbitrary number of spatially diffusing chemicals; (ii) spatially heterogeneous chemical diffusion coefficients; and (iii) inclusion of both bulk and intracellular biochemical reactions and their coupling. ChemChaste also introduces a file-based interface that allows users to define the parameters relating to these functional features without the need to interact directly with Chastes core C++ code. We describe ChemChaste and demonstrate its functionality using a selection of chemical and biochemical exemplars, with a focus on demonstrating increased ability in modelling bulk chemical reactions and their coupling with intracellular reactions. Availability and implementationChemChaste is a free, open-source C++ library, available via GitHub at https://github.com/OSS-Lab/ChemChaste under the BSD license. ContactO.Soyer@warwick.ac.uk or a.g.fletcher@sheffield.ac.uk

systems biology↗