Coevolutionary diversification creates nested-modular structure in phage-bacteria interaction networks

This is a post-print of an article published in Interface Focus. Please cite the published article.Phage and their bacterial hosts are the most diverse and abundant biological entities in the oceans, where their interactions have a major impact on marine ecology and ecosystem function. The structure of interaction networks for natural phage-bacteria communities offers insight into their coevolutionary origin. At small phylogenetic scales, observed communities typically show a nested structure, in which both hosts and phage can be ranked by their range of resistance and infectivity respectively. A qualitatively different multiscale structure is seen at larger phylogenetic scales; a natural assemblage sampled from the Atlantic Ocean displays large-scale modularity and local nestedness within each module. Here we show that such “nested-modular” interaction networks can be produced by a simple model of host-phage coevolution in which infection depends on genetic matching. Negative frequency-dependent selection causes diversification of hosts (to escape phage) and phage (to track their evolving hosts). This creates a diverse community of bacteria and phage, maintained by kill-the-winner ecological dynamics. When the resulting communities are visualised as bipartite networks of who-infects-whom, they show the nested-modular structure characteristic of the Atlantic sample. The statistical significance and strength of this observation varies depending on whether the interaction networks take into account the density of the interacting strains, with implications for interpretation of interaction networks constructed by different methods. Our results suggest that the apparently complex community structures associated with marine bacteria and phage may arise from relatively simple coevolutionary origins.University of Exete

Nestedness and Modularity in Bipartite Networks

Bipartite networks are a useful way of representing interactions between two sets of entities. Understanding the underlying structures of such networks may give insights into the functionality and behaviour of the systems they represent. Two important structural patterns identified in bipartite networks are nestedness and modularity. Nestedness describes a hierarchical ordering of nodes such that more specialised nodes have interactions with a subset of the partners with which the more generalised nodes interact. Modularity captures the community structure of a network as distinct clusters of interactions, such that there are more connections within communities than between communities. While these network architectures are easy to describe in writing, their quantitative measurement for a given network is a difficult task. Several different methods have been proposed in each case and it is currently unclear which of them should be used in practice. This thesis considers the use, measurement and interpretation of nestedness and modularity in bipartite networks. First, it is shown how bipartite networks can be an effective tool for linking data and theory in community ecology, though use of a coevolutionary model of virus-bacteria interactions. Next, a series of studies is presented that push towards clarification of the best procedures to measure nestedness and modularity in bipartite networks. Robustness of nestedness measures is tested on a synthetic ensemble of networks, showing that apparent nestedness depends strongly on the choice of measure, null model and effect size statistics. Recommendations for performing nestedness are made with relation to individual and cross-network comparisons. Additionally, a new algorithm for identifying weighted modularity is proposed that can be shown to outperform existing methods. Crucially, it is shown that quantitative modular structures differ from traditional binary modular structures with implications for how modularity is reported and used. Improving the way in which nestedness and modularity are measured is a necessary step for integrating data and theory in bipartite networks.University of Exete

FALCON: a software package for analysis of nestedness in bipartite networks

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.Nestedness is a statistical measure used to interpret bipartite interaction data in several ecological and evolutionary contexts, e.g. biogeography (species-site relationships) and species interactions (plant-pollinator and host-parasite networks). Multiple methods have been used to evaluate nestedness, which differ in how the metrics for nestedness are determined. Furthermore, several different null models have been used to calculate statistical significance of nestedness scores. The profusion of measures and null models, many of which give conflicting results, is problematic for comparison of nestedness across different studies. We developed the FALCON software package to allow easy and efficient comparison of nestedness scores and statistical significances for a given input network, using a selection of the more popular measures and null models from the current literature. FALCON currently includes six measures and five null models for nestedness in binary networks, and two measures and four null models for nestedness in weighted networks. The FALCON software is designed to be efficient and easy to use. FALCON code is offered in three languages (R, MATLAB, Octave) and is designed to be modular and extensible, enabling users to easily expand its functionality by adding further measures and null models. FALCON provides a robust methodology for comparing the strength and significance of nestedness in a given bipartite network using multiple measures and null models. It includes an “adaptive ensemble” method to reduce undersampling of the null distribution when calculating statistical significance. It can work with binary or weighted input networks. FALCON is a response to the proliferation of different nestedness measures and associated null models in the literature. It allows easy and efficient calculation of nestedness scores and statistical significances using different methods, enabling comparison of results from different studies and thereby supporting theoretical study of the causes and implications of nestedness in different biological contexts

The ecological and biogeochemical state of the North Pacifi c Subtropical Gyre is linked to sea surface height

Sea surface height (SSH) is routinely measured from satellites and used to infer ocean currents, including eddies, that affect the distribution of organisms and substances in the ocean. SSH not only reflects the dynamics of the surface layer, but also is sensitive to the fluctuations of the main pycnocline; thus it is linked to events of nutrient upwelling. Beyond episodic upwelling events, it is not clear if and how SSH is linked to broader changes in the biogeochemical state of marine ecosystems. Our analysis of 23 years of satellite observations and biogeochemical measurements from the North Pacific Subtropical Gyre shows that SSH is associated with numerous biogeochemical changes in distinct layers of the water column. From the sea surface to the depth of the chlorophyll maximum, dissolved phosphorus and nitrogen enigmatically increase with SSH, enhancing the abundance of heterotrophic picoplankton. At the deep chlorophyll maximum, increases in SSH are associated with decreases in vertical gradients of inorganic nutrients, decreases in the abundance of eukaryotic phytoplankton, and increases in the abundance of prokaryotic phytoplankton. In waters below ∼100 m depth, increases in SSH are associated with increases in organic matter and decreases in inorganic nutrients, consistent with predicted consequences of the vertical displacement of isopycnal layers. Our analysis highlights how satellite measurements of SSH can be used to infer the ecological and biogeochemical state of open-ocean ecosystems

Contrasting Controls on Microzooplankton Grazing and Viral Infection of Microbial Prey

The encounter and capture of bacteria and phytoplankton by microbial predators and parasites is fundamental to marine ecosystem organization and activity. Here, we combined classic biophysical models with published laboratory measurements to infer functional traits, including encounter kernel and capture efficiency, for a wide range of marine viruses and microzooplankton grazers. Despite virus particles being orders of magnitude smaller than microzooplankton grazers, virus encounter kernels and adsorption rates were in many cases comparable in magnitude to grazer encounter kernel and clearance, pointing to Brownian motion as a highly effective method of transport for viruses. Inferred virus adsorption efficiency covered many orders of magnitude, but the median virus adsorption efficiency was between 5 and 25% depending on the assumed host swimming speed. Uncertainty on predator detection area and swimming speed prevented robust inference of grazer capture efficiency, but sensitivity analysis was used to identify bounds on unconstrained processes. These results provide a common functional trait framework for understanding marine host-virus and predator-prey interactions, and highlight the value of theory for interpreting measured life-history traits

The Effect of Strain Level Diversity on Robust Inference of Virus-Induced Mortality of Phytoplankton

Infection and lysis of phytoplankton by viruses affects population dynamics and nutrient cycles within oceanic microbial communities. However, estimating the quantitative rates of viral-induced lysis remains challenging in situ. The modified dilution method is the most commonly utilized empirical approach to estimate virus-induced killing rates of phytoplankton. The lysis rate estimates of the modified dilution method are based on models which assume virus-host interactions can be represented by a single virus and a single host population with homogeneous life-history traits. Here, using modeling approaches, we examine the robustness of the modified dilution method in multi-strain, complex communities. We assume that strains differ in their life history traits, including growth rates (of hosts) and lysis rates (by viruses). We show that trait differences affect resulting experimental dynamics such that lysis rates measured using the modified dilution method may be driven by the fastest replicating strains; which are not necessarily the most abundant in situ. We discuss the implications of using the modified dilution method and alternative dilution-based approaches for estimating viral-induced lysis rates in marine microbial communities

Selective hydroxylation of 1,8- and 1,4-cineole using bacterial P450 variants

This study has evaluated the use of the P450 metalloenzymes CYP176A1, CYP101A1 and CYP102A1, together with engineered protein variants of CYP101A1 and CYP102A1, to alter the regioselectivity of 1,8- and 1,4-cineole hydroxylation. CYP176A1 was less selective for 1,4-cineole oxidation when compared to its preferred substrate, 1,8-cineole. The CYP102A1 variants significantly improved the activity over the WT enzyme for oxidation of 1,4- and 1,8-cineole. The CYP102A1 R47L/Y51F/A74G/F87V/L188Q mutant generated predominantly (1S)-6α-hydroxy-1,8-cineole (78% e.e.) from 1,8-cineole. Oxidation of 1,4-cineole by the CYP102A1 R47L/Y51F/F87A/I401P variant generated the 3α product in >90% yield. WT CYP101A1 formed a mixture metabolites with 1,8-cineole and very little product was generated with 1,4-cineole. In contrast the F87W/Y96F/L244A/V247L and F87W/Y96F/L244A variants of CYP101A1 favoured formation of 5α-hydroxy-1,8-cineole (>88%, 1S 86% e.e.) while the F87V/Y96F/L244A variant generated (1S)-6α-hydroxy-1,8-cineole in excess (90% regioselective, >99% e.e.). The CYP101A1 F87W/Y96F/L244A/V247L and F87W/Y96F/L244A mutants improved the oxidation of 1,4-cineole generating an excess of the 3α metabolite (1S > 99% e.e. with the latter). The CYP101A1 F87L/Y96F variant also improved the oxidation of this substrate but shifted the site of oxidation to the isopropyl group, (8-hydroxy-1,4-cineole). When this 8-hydroxy metabolite was generated in significant quantities desaturation of C8C9 to the corresponding alkene was also detected

Exploring High Aspect Ratio Gold Nanotubes as Cytosolic Agents: Structural Engineering and Uptake into Mesothelioma Cells.

The generation of effective and safe nanoagents for biological applications requires their physicochemical characteristics to be tunable, and their cellular interactions to be well characterized. Here, the controlled synthesis is developed for preparing high-aspect ratio gold nanotubes (AuNTs) with tailorable wall thickness, microstructure, composition, and optical characteristics. The modulation of optical properties generates AuNTs with strong near infrared absorption. Surface modification enhances dispersibility of AuNTs in aqueous media and results in low cytotoxicity. The uptake and trafficking of these AuNTs by primary mesothelioma cells demonstrate their accumulation in a perinuclear distribution where they are confined initially in membrane-bound vesicles from which they ultimately escape to the cytosol. This represents the first study of the cellular interactions of high-aspect ratio 1D metal nanomaterials and will facilitate the rational design of plasmonic nanoconstructs as cytosolic nanoagents for potential diagnosis and therapeutic applications.BLF-Papworth Fellowship from the British Lung Foundation and the Victor Dahdaleh Foundation

Contrasting Controls on Microzooplankton Grazing and Viral Infection of Microbial Prey

The encounter and capture of bacteria and phytoplankton by microbial predators and parasites is fundamental to marine ecosystem organization and activity. Here, we combined classic biophysical models with published laboratory measurements to infer functional traits, including encounter kernel and capture efficiency, for a wide range of marine viruses and microzooplankton grazers. Despite virus particles being orders of magnitude smaller than microzooplankton grazers, virus encounter kernels and adsorption rates were in many cases comparable in magnitude to grazer encounter kernel and clearance, pointing to Brownian motion as a highly effective method of transport for viruses. Inferred virus adsorption efficiency covered many orders of magnitude, but the median virus adsorption efficiency was between 5 and 25% depending on the assumed host swimming speed. Uncertainty on predator detection area and swimming speed prevented robust inference of grazer capture efficiency, but sensitivity analysis was used to identify bounds on unconstrained processes. These results provide a common functional trait framework for understanding marine host-virus and predator-prey interactions, and highlight the value of theory for interpreting measured life-history traits