Biology subjects

Ray, J. L.

Publications and source records attributed to Ray, J. L..

4 recordsLinked to original sources

bioRxiv2024

Enhanced Prediction of Seafloor Ecological State Using 16S Nanopore Sequencing

Anthropogenic stress on benthic habitats, particularly from aquaculture, calls for accurate and efficient monitoring of the macrofauna ecological state. Recent advancements in Oxford Nanopore Technology (ONT) together with environmental DNA offers cost-effective and rapid, on-site monitoring of such ecosystems. Previous studies have demonstrated that Nanopore sequencing provides sufficient precision for predicting ecological state, despite reported challenges with sequencing accuracy. In this study, we aim to predict the seafloor ecological state with both Illumina and Nanopore 16S rRNA gene sequencing data and using a combination of machine learning and feature selection. We analyzed 88 seafloor samples from aquaculture sites located on a north-south gradient along the Norwegian coast. Both sequencing methods were evaluated in combination with various bioinformatic approaches in the context of predicting the normalized EQR index (nEQR, standard ecological index based on macroinvertebrate counting) as a metric of seafloor ecosystem status. Our results show that the predictive performance of Illumina and Nanopore sequencing platforms are comparable, establishing Nanopore as a feasible alternative to illumina sequencing. By employing a stabilized LASSO regression, the feature set (potential taxa) was efficiently optimized from thousands to 40-60 OTUs. The feature selection reduced prediction errors to less than half of what was obtained through full feature modeling. This feature set demonstrated strong predictive accuracy across both sequencing technologies, with a high correlation between observed and predicted nEQR values. The Pearson correlation coefficient of 0.98 for Illumina and 0.95 (mean prediction error: {+/-}0.04) for Nanopore data (mean prediction error: {+/-}0.06). This study demonstrates that continual improvements in Nanopore sequencing accuracy, in combination with optimized feature selection on a broader set of samples, provides a precise and cost-effective monitoring method for marine benthic environments.

ecology↗

bioRxiv2024

A Targeted Reference Database for Improved Analysis of Environmental 16S rRNA Oxford Nanopore Sequencing Data

The Oxford Nanopore Technologies (ONT) sequencing platform is compact and efficient, making it suitable for rapid biodiversity assessments in remote areas. Despite its long reads, ONT has a higher error rate compared to other platforms, necessitating high-quality reference databases for accurate taxonomic assignments. However, the absence of targeted databases for underexplored habitats, such as the seafloor, limits ONTs broader applicability for exploratory analysis. To address this, we propose an approach for building environmentally-targeted databases to improve 16S rRNA gene (16S) analysis using Oxford Nanopore Technologies (ONT), using seafloor sediment samples from the Norwegian coast as an example. We started by using Illumina short-read data to create a database of full-length or near full-length 16S sequences from seafloor samples. Initially, amplicons are mapped to the SILVA database, with matches added to our database. Unmatched amplicons are reconstructed using METASEED and Barrnap methodologies with amplicon and metagenome data. Finally, if the previous strategies did not succeed, we included the short-read sequences in the database. This resulted in AQUAeD-DB, which contains 14 545 16S sequences clustered at 95% identity. Comparative database analysis reveal that AQUAeD-DB provides consistent results for both Illumina and Nanopore read assignments (median correlation coefficient: 0.50), whereas a standard database showed a substantially weaker correlation. These findings also emphasize its potential to recognize both high and low-abundance taxa, which could be key indicators in environmental studies. This work highlights the necessity of targeted databases for environmental analysis, especially for ONT-based studies, and lays foundations for future extension of the database.

bioinformatics↗

bioRxiv2024

Key roles of microbial sulfur and ammonium oxidizers for the coastal seafloor ecological state

Recent evidence suggests that there is a major switch in coastal seafloor microbial ecology already at a mildly deteriorated macrofaunal state. This knowledge is of critical value in the management and conservation of the coastal seafloor. We therefore aimed to determine the relationships between seafloor microbiota and macrofauna on a regional scale. We compared prokaryote, macrofauna, chemical, and geographical data from 1,546 seafloor samples which varied in their exposure to aquaculture activities along the Norwegian and Icelandic coasts. We found that the seafloor samples contained either a sulfur oxidizer network (42.4% of samples, n=656), or an ammonium oxidizer network of microbes (44.0% of samples, n=681). Very few samples contained neither network (9.8% of samples, n=151), or both (3.8% of samples, n=58). Samples with a sulfur oxidizer network had a tenfold higher risk of macrofauna loss (odds ratios, 95% CI: 9.5 to 15.6), while those with an ammonium oxidizer network had a tenfold lower risk (95% CI: 0.068 to 0.11). The sulfur oxidizer network was negatively correlated to distance from Norwegian aquaculture sites (Spearman rho = -0.42, p < 0.01), and was present in all Icelandic samples (n=274). The ammonium oxidizer network was absent from Icelandic samples, and positively correlated to distance from Norwegian aquaculture sites (Spearman rho = 0.67, p < 0.01). Based on 357 high-quality metagenome-assembled genomes (MAGs), we found that the main metabolic process for the ammonium oxidizer network was cobalamin-dependent, while the sulfur oxidizer network was associated with both ammonium retention and sulfur metabolism. In conclusion, our findings highlight the critical roles of sulfur and ammonium oxidizers in mild macrofauna deterioration, which should be included as an essential part of seafloor surveillance.

microbiology↗

bioRxiv2024

scRNA-seq identifies unique macrophage population in murine model of ozone induced asthma exacerbation

Ozone (O3) inhalation triggers asthmatic airway hyperresponsiveness (AHR), but the mechanisms by which this occurs are unknown. Previously, we developed a murine model of dust mite, ragweed, and aspergillus (DRA)-induced allergic lung inflammation followed by O3 exposure for mechanistic investigation. The present study used single cell RNA-sequencing for unbiased profiling of immune cells within the lungs of mice exposed to DRA, O3, or DRA+O3, to identify the components of the immune cell niche that contribute to AHR. Alveolar macrophages (AMs) had the greatest number of differentially expressed genes following DRA+O3, most of which were unique to the 2-hit exposure. Following DRA+O3, AMs activated transcriptional pathways related to cholesterol biosynthesis, degradation of the extracellular matrix, endosomal TLR processing, and various cytokine signals. We also identified AM and monocyte subset populations that were unique to the DRA+O3 group. These unique AMs activated gene pathways related to inflammation, sphingolipid metabolism, and bronchial constriction. The unique monocyte population had a gene signature that suggested phospholipase activation and increased degradation of the extracellular matrix. Flow cytometry analysis of BAL immune cells showed recruited monocyte-derived AMs after DRA and DRA+O3, but not after O3 exposure alone. O3 alone increased BAL neutrophils but this response was attenuated in DRA+O3 mice. DRA-induced changes in the airspace immune cell profile were reflected in elevated BAL cytokine/chemokine levels following DRA+O3 compared to O3 alone. The present work highlights the role of monocytes and AMs in the response to O3 and suggests that the presence of distinct subpopulations following allergic inflammation may contribute to O3-induced AHR.

pharmacology and toxicology↗