Real-world complex networks are composed of non-random quantitative interactions. Identifying communities of nodes that tend to interact more with each other than the network as a whole is a key research focus across multiple disciplines, yet many community detection algorithms only use information about the presence or absence of interactions between nodes. Weighted modularity is a potential method for evaluating the quality of community partitions in quantitative networks. In this framework, the optimal community partition of a network can be found by searching for the partition that maximizes modularity. Attempting to find the partition that maximizes modularity is a computationally hard problem requiring the use of algorithms. QuanBiMo is an algorithm that has been proposed to maximize weighted modularity in bipartite networks. This paper introduces two new algorithms, LPAwb+ and DIRTLPAwb+, for maximizing weighted modularity in bipartite networks. LPAwb+ and DIRTLPAwb+ robustly identify partitions with high modularity scores. DIRTLPAwb+ consistently matched or outperformed QuanBiMo, while the speed of LPAwb+ makes it an attractive choice for detecting the modularity of larger networks. Searching for modules using weighted data (rather than binary data) provides a different and potentially insightful method for evaluating network partitions.

Microplastics, plastics particles <5 mm in length, are a widespread pollutant of the marine environment. Oral ingestion of microplastics has been reported for a wide range of marine biota, but uptake into the body by other routes has received less attention. Here, we test the hypothesis that the shore crab (Carcinus maenas) can take up microplastics through inspiration across the gills as well as ingestion of pre-exposed food (common mussel Mytilus edulis). We used fluorescently labeled polystyrene microspheres (8-10 μm) to show that ingested microspheres were retained within the body tissues of the crabs for up to 14 days following ingestion and up to 21 days following inspiration across the gill, with uptake significantly higher into the posterior versus anterior gills. Multiphoton imaging suggested that most microspheres were retained in the foregut after dietary exposure due to adherence to the hairlike setae and were found on the external surface of gills following aqueous exposure. Results were used to construct a simple conceptual model of particle flow for the gills and the gut. These results identify ventilation as a route of uptake of microplastics into a common marine nonfilter feeding species.

The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 2020 1-4 . Mitigation and suppression of new infections have emerged as the two predominant public health control strategies 5 . Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests 6,7 to identify and deploy recovered individuals 8 as focal points for sustaining safer interactions via interaction substitution, developing what we term 'shield immunity' at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services 9 while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence 10,11 and in the potential development of plasma-based therapies 12-15 .In the absence of reliable pharmaceutical interventions against SARS-CoV-2, multiple public health strategies are being deployed to slow the coronavirus pandemic 1,5,16 . These strategies can be broadly grouped into two approaches: mitigation and suppression. Mitigation includes a combination of social distancing (including school and university closures), case testing and symptomatic case isolation to reduce epidemic spread and burden on hospitals. Mitigation is intended to lessen an outbreak. However, the number of cases might still overwhelm health services 5 . Some jurisdictions have either preemptively or reactively adopted a combination of travel restrictions (shown to be effective in curtailing dispersion if implemented early enough 17,18 ) and suppression, which involves imposing complete shutdowns of the bulk of non-essential services for extended periods. Suppression strategies have led to marked decreases in new case rates in the short term by combining case isolation, quarantine, use of separate facilities for treating COVID-19 patients and large-scale

One contribution of 11 to a Theme Issue 'Modelling biological evolution: recent progress, current challenges and future direction'. 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 phages can be ranked by their range of resistance and infectivity, respectively. A qualitatively different multi-scale 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 frequencydependent selection causes diversification of hosts (to escape phages) and phages (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 visualized 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.

Long-term stability of picocyanobacteria in the open oceans is maintained by a balance between synchronous division and death on daily timescales. Viruses are considered a major source of microbial mortality, however, current methods to measure infection have significant methodological limitations. Here we describe a method that pairs flow-cytometric sorting with a PCR-based polony technique to simultaneously screen thousands of taxonomically resolved individual cells for intracellular virus DNA, enabling sensitive, high-throughput, and direct quantification of infection by different virus lineages. Under controlled conditions with picocyanobacteria-cyanophage models, the method detected infection throughout the lytic cycle and discriminated between varying infection levels. In North Pacific subtropical surface waters, the method revealed that only a small percentage of Prochlorococcus (0.35–1.6%) were infected, predominantly by T4-like cyanophages, and that infection oscillated 2-fold in phase with the diel cycle. This corresponds to 0.35–4.8% of Prochlorococcus mortality daily. Cyanophages were 2–4-fold more abundant than Prochlorococcus, indicating that most encounters did not result in infection and suggesting infection is mitigated via host resistance, reduced phage infectivity and inefficient adsorption. This method will enable quantification of infection for key microbial taxa across oceanic regimes and will help determine the extent that viruses shape microbial communities and ecosystem level processes.

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.

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We show that neither the Piggyback-the-Winner model nor coral reef virome data presented in Knowles et al. [1] support a mechanistic link between increases in lysogeny, suppression of lysis, and the decline of the virus-to-microbial cell ratio (VMR) at high microbial cell densities across environmental and humanassociated systems..