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Quantifying viral traits—including the adsorption rate, burst size, and latent period—is critical to characterize viral infection dynamics and develop predictive models of viral impacts across scales from cells to ecosystems. Here, we revisit the gold standard of viral trait estimation—the one-step growth curve—to assess the extent to which assumptions at the core of viral infection dynamics lead to ongoing and systematic biases in inferences of viral traits. We show that latent period estimates obtained via one-step growth curves systematically underestimate the mean latent period and, in turn, overestimate the rate of viral killing at population scales. By explicitly incorporating trait variability into a dynamical inference framework that leverages both virus and host time series, we provide a practical route to improve estimates of the mean and variance of viral traits across diverse virus–microbe systems.

Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants. Serological testing remains a passive component of the current public health response to the COVID-19 pandemic. Using a mathematical model, the authors examine how testing for antibodies could have enabled policies in which seropositive individuals increased their relative levels of social interaction while offsetting transmission risks

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics. This study shows that a multitrophic community model jointly recapitulates diel rhythms in abundances of Prochlorococcus picocyanobacteria, as well as viral infection, viral abundances and grazer abundances. Model-data integration implies that grazing predominantly controls Prochlorococcus abundances in surface waters of the North Pacific Subtropical Gyre, despite high viral densities.

Photosynthetic picoeukaryotes in the genus Micromonas show among the widest latitudinal distributions on Earth, experiencing large thermal gradients from poles to tropics. Micromonas comprises at least four different species often found in sympatry. While such ubiquity might suggest a wide thermal niche, the temperature response of the different strains is still unexplored, leaving many questions as for their ecological success over such diverse ecosystems. Using combined experiments and theory, we characterize the thermal response of eleven Micromonas strains belonging to four 1 species. We demonstrate that the variety of specific responses to temperature in the Micromonas genus makes this environmental factor an ideal marker to describe its global distribution and diversity. We then propose a diversity model for the genus Micromonas, which proves to be representative of the whole phytoplankton diversity. This prominent primary producer is therefore a sentinel organism of phytoplankton diversity at the global scale. We use the diversity within Micromonas to anticipate the potential impact of global warming on oceanic phytoplankton. We develop a dynamic, adaptive model and ran forecast simulations, exploring a range of adaptation time scales, to probe the likely responses to climate change. Results stress how biodiversity erosion depends on the ability of organisms to adapt rapidly to temperature increase.

The genus Micromonas comprises phytoplankton that show among the widest latitudinal distributions on Earth, and members of this genus are recurrently infected by prasinoviruses in contrasted thermal ecosystems. In this study, we assessed how temperature influences the interplay between the main genetic clades of this prominent microalga and their viruses. The growth of three Micromonas strains (Mic-A, Mic-B, Mic-C) and the stability of their respective lytic viruses (MicV-A, MicV-B, MicV-C) were measured over a thermal range of 4–32.5 °C. Similar growth temperature optima (Topt) were predicted for all three hosts but Mic-B exhibited a broader thermal tolerance than Mic-A and Mic-C, suggesting distinct thermoacclimation strategies. Similarly, the MicV-C virus displayed a remarkable thermal stability compared with MicV-A and MicV-B. Despite these divergences, infection dynamics showed that temperatures below Topt lengthened lytic cycle kinetics and reduced viral yield and, notably, that infection at temperatures above Topt did not usually result in cell lysis. Two mechanisms operated depending on the temperature and the biological system. Hosts either prevented the production of viral progeny or maintained their ability to produce virions with no apparent cell lysis, pointing to a possible switch in the viral life strategy. Hence, temperature changes critically affect the outcome of Micromonas infection and have implications for ocean biogeochemistry and evolution.

Synechococcus is the second most abundant phytoplanktonic organism on Earth, and its wide genetic diversity allowed it to colonize all the oceans except for polar waters, with different clades colonizing distinct oceanic niches. In recent years, the use of global metagenomics data sets has greatly improved our knowledge of “who is where” by describing the distribution of Synechococcus clades or ecotypes in the open ocean. Marine Synechococcus comprise a numerically and ecologically prominent phytoplankton group, playing a major role in both carbon cycling and trophic networks in all oceanic regions except in the polar oceans. Despite their high abundance in coastal areas, our knowledge of Synechococcus communities in these environments is based on only a few local studies. Here, we use the global metagenome data set of the Ocean Sampling Day (June 21 st , 2014) to get a snapshot of the taxonomic composition of coastal Synechococcus communities worldwide, by recruitment on a reference database of 141 picocyanobacterial genomes, representative of the whole Prochlorococcus , Synechococcus , and Cyanobium diversity. This allowed us to unravel drastic community shifts over small to medium scale gradients of environmental factors, in particular along European coasts. The combined analysis of the phylogeography of natural populations and the thermophysiological characterization of eight strains, representative of the four major Synechococcus lineages (clades I to IV), also brought novel insights about the differential niche partitioning of clades I and IV, which most often co-dominate the Synechococcus community in cold and temperate coastal areas. Altogether, this study reveals several important characteristics and specificities of the coastal communities of Synechococcus worldwide. IMPORTANCE Synechococcus is the second most abundant phytoplanktonic organism on Earth, and its wide genetic diversity allowed it to colonize all the oceans except for polar waters, with different clades colonizing distinct oceanic niches. In recent years, the use of global metagenomics data sets has greatly improved our knowledge of “who is where” by describing the distribution of Synechococcus clades or ecotypes in the open ocean. However, little is known about the global distribution of Synechococcus ecotypes in coastal areas, where Synechococcus is often the dominant phytoplanktonic organism. Here, we leverage the global Ocean Sampling Day metagenomics data set to describe Synechococcus community composition in coastal areas worldwide, revealing striking community shifts, in particular along the coasts of Europe. As temperature appears as an important driver of the community composition, we also characterize the thermal preferenda of 8 Synechococcus strains, bringing new insights into the adaptation to temperature of the dominant Synechococcus clades.

The cyanobacterium Prochlorococcus is an essential member of global ocean ecosystems. Light rhythms drive Prochlorococcus photosynthesis, ecology, and interactions with potentially lethal viruses. At present, the impact of light on Prochlorococcus -virus interactions is not well understood. Here, we analyzed Prochlorococcus and virus population dynamics with a light-driven population model and compared our results with experimental data. Our approach revealed that light profoundly drives both cellular- and population-level dynamics for some host-virus systems. However, we also found that additional mechanisms, including lysis saturation, are required to explain observed host-virus dynamics at the population scale. This study provides the basis for future work to understand the intertwined fates of Prochlorococcus and associated viruses in the surface ocean. Prochlorococcus cyanobacteria grow in diurnal rhythms driven by diel cycles. Their ecology depends on light, nutrients, and top-down mortality processes, including lysis by viruses. Cyanophage, viruses that infect cyanobacteria, are also impacted by light. For example, the extracellular viability and intracellular infection kinetics of some cyanophage vary between light and dark conditions. Nonetheless, it remains unclear whether light-dependent viral life history traits scale up to influence population-level dynamics. Here, we examined the impact of diel forcing on both cellular- and population-scale dynamics in multiple Prochlorococcus -phage systems. To do so, we developed a light-driven population model, including both cellular growth and viral infection dynamics. We then tested the model against measurements of experimental infection dynamics with diel forcing to examine the extent to which population level changes in both viral and host abundances could be explained by light-dependent life history traits. Model-data integration reveals that light-dependent adsorption can improve fits to population dynamics for some virus-host pairs. However, light-dependent variation alone does not fully explain realized host and virus population dynamics. Instead, we show evidence consistent with lysis saturation at relatively high virus-to-cell ratios. Altogether, our study represents a quantitative approach to integrate mechanistic models to reconcile Prochlorococcus -virus dynamics spanning cellular-to-population scales. IMPORTANCE The cyanobacterium Prochlorococcus is an essential member of global ocean ecosystems. Light rhythms drive Prochlorococcus photosynthesis, ecology, and interactions with potentially lethal viruses. At present, the impact of light on Prochlorococcus -virus interactions is not well understood. Here, we analyzed Prochlorococcus and virus population dynamics with a light-driven population model and compared our results with experimental data. Our approach revealed that light profoundly drives both cellular- and population-level dynamics for some host-virus systems. However, we also found that additional mechanisms, including lysis saturation, are required to explain observed host-virus dynamics at the population scale. This study provides the basis for future work to understand the intertwined fates of Prochlorococcus and associated viruses in the surface ocean.

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 . A new study models the potential effects of preferentially deploying recovered individuals, who are seropositive for anti-SARS-CoV-2 antibodies, into the community to reduce the number of interactions between susceptible and infected people, thereby limiting transmission of the virus.