Biology subjects

Swift, S. O. I.

Publications and source records attributed to Swift, S. O. I..

4 recordsLinked to original sources

bioRxiv2026

Soil Resistomes in a Tropical Watershed are Indirectly Structured by Bacterial Community Interactions with Soil Properties

Soils are recognized as reservoirs of antibiotic resistance genes (ARGs) with the potential to transfer to clinical pathogens, creating antimicrobial resistance (AMR) that poses a threat to human health. While large-scale AMR surveys have profiled how diverse biomes shape soil resistomes, less is known about the influence of specific soil properties. Here, we combined metagenomics and 16S rRNA amplicon sequencing with isolate-based approaches to investigate drivers of soil AMR across a tropical watershed from beach to mountaintop in Waimea Valley, Oahu, Hawai{square}i. We leveraged functional- and taxonomic-classification of resistances to unravel how soil properties interact with bacterial taxa to structure resistomes. Metagenomic- and isolate-resistomes showed remarkable consistency, including a general gradient of increasing AMR from ridge to beach. Resistome functional composition was significantly correlated with total bacterial community structure. The relationship between resistances and soil properties was primarily dictated by taxonomic composition of each resistance. Rifampin- and Vancomycin-ARGs associated with Actinomycetes negatively correlated with soil physical properties, while resistant genes and isolates from Gammaproteobacteria positively correlated with enzymatic activity metrics. These findings indicate that soil properties structure the resistome indirectly through taxonomic filtering of microbial hosts and challenge the notion that AMR is decoupled from phylogenetic relatedness.

ecology↗

bioRxiv2025

Diversity, connectivity and negative interactions define robust microbiome networks across land, stream, and sea

In this era of rapid global change, factors influencing the stability of ecosystems and their functions have come into the spotlight. For decades the relationship between stability and complexity has been investigated in modeled and empirical systems, yet results remain largely context dependent. To overcome this we leverage a multiscale inventory of fungi and bacteria ranging from single sites along an environmental gradient, to habitats inclusive of land, sea and stream, to an entire watershed. We use networks to assess the relationship between microbiome complexity and robustness and identify fundamental principles of stability. We demonstrate that while some facets of complexity are positively associated with robustness, others are not. Beyond positive biodiversity x robustness relationships we find that the number of "gatekeeper" species or those that are highly connected and central within their networks, and the proportion of predicted negative interactions are universal indicators of robust microbiomes. With the potential promise of microbiome engineering to address global challenges ranging from human to ecosystem health we identify properties of microbiomes for future experimental studies that may enhance their stability. We emphasize that features beyond biodiversity and additional characteristics beyond stability such as adaptability should be considered in these efforts.

ecology↗

bioRxiv2021

specificity : an R package for generalized specificity analysis, with example analyses of Hawaiian foliar endophytic Fungi, human gut microbiome bacteria, and Antarctic glacier bacteria.

BackgroundUnderstanding the factors that influence microbes environmental distributions is important for deter-mining drivers of microbial community composition. These include environmental variables like temperature and pH, and higher-dimensional variables like geographic distance and host species phylogeny. In microbial ecology, "specificity" is often described in the context of symbiotic or host parasitic interactions, but specificity can be more broadly used to describe the extent to which a species occupies a narrower range of an environmental variable than expected by chance. Using a standardization we describe here, Raos (1982, 2010) Quadratic Entropy can be conveniently applied to calculate specificity of a feature, such as a species, to many different environmental variables. ResultsWe present our R package specificity for performing the above analyses, and apply it to four real-life microbial data sets to demonstrate its application. We found that many fungi within the leaves of native Hawaiian plants had strong specificity to rainfall and elevation, even though these variables showed minimal importance in a previous analysis of fungal beta-diversity. In Antarctic cryoconite holes, our tool revealed that many bacteria have specificity to co-occurring algal community composition. Similarly, in the human gut microbiome, many bacteria showed specificity to the composition of bile acids. Finally, our analysis of the Earth Microbiome Project data set showed that most bacteria show strong ontological specificity to sample type. Our software performed as expected on synthetic data as well. Conclusionsspecificity is well-suited to analysis of microbiome data, both in synthetic test cases, and across multiple environment types and experimental designs. The analysis and software we present here can reveal patterns in microbial taxa that may not be evident from a community-level perspective. These insights can also be visualized and interactively shared among researchers using specificitys companion package, specificity.shiny.

microbiology↗

bioRxiv2019

Fungal communities living within leaves of native Hawaiian dicots are structured by landscape-scale variables as well as by host plants

ABSTRACTA phylogenetically diverse array of fungi live within healthy leaf tissue of dicotyledonous plants. Many studies have examined these endophytes within a single plant species and/or at small spatial scales, but landscape-scale variables that determine their community composition are not well understood, either across geographic space, across climatic conditions, or in the context of host plant phylogeny. Here, we evaluate the contributions of these variables to endophyte beta diversity using a survey of foliar endophytic fungi in native Hawaiian dicots sampled across the Hawaiian archipelago. We used Illumina technology to sequence fungal ITS1 amplicons to characterize foliar endophyte communities across five islands and 80 host plant genera. We found that communities of foliar endophytic fungi showed strong geographic structuring between distances of seven and 36 km. Endophyte community structure was most strongly associated with host plant phylogeny and evapotranspiration, and was also significantly associated with NDVI, elevation, and solar radiation. Additionally, our bipartite network analysis revealed that the five islands we sampled each harbored significantly specialized endophyte communities. These results demonstrate how the interaction of factors at large and small spatial and phylogenetic scales shape fungal symbiont communities.Competing Interest StatementThe authors have declared no competing interest.View Full Text

ecology↗