Structured foraging of soil predators unveils functional responses to bacterial defenses.

Predators and their foraging strategies often determine ecosystem structure and function. Yet, the role of protozoan predators in microbial soil ecosystems remains elusive despite the importance of these ecosystems to global biogeochemical cycles. In particular, amoebae-the most abundant soil protozoan predator of bacteria-remineralize soil nutrients and shape the bacterial community. However, their foraging strategies and their role as microbial ecosystem engineers remain unknown. Here, we present a multiscale approach, connecting microscopic single-cell analysis and macroscopic whole ecosystem dynamics, to expose a phylogenetically widespread foraging strategy, in which an amoeba population spontaneously partitions between cells with fast, polarized movement and cells with slow, unpolarized movement. Such differentiated motion gives rise to efficient colony expansion and consumption of the bacterial substrate. From these insights, we construct a theoretical model that predicts how disturbances to amoeba growth rate and movement disrupt their predation efficiency. These disturbances correspond to distinct classes of bacterial defenses, which allows us to experimentally validate our predictions. All considered, our characterization of amoeba foraging identifies amoeba mobility, and not amoeba growth, as the core determinant of predation efficiency and a key target for bacterial defense systems.

A PDE Model for Protocell Evolution and the Origin of Chromosomes via Multilevel Selection.

The evolution of complex cellular life involved two major transitions: the encapsulation of self-replicating genetic entities into cellular units and the aggregation of individual genes into a collectively replicating genome. In this paper, we formulate a minimal model of the evolution of proto-chromosomes within protocells. We model a simple protocell composed of two types of genes: a "fast gene" with an advantage for gene-level self-replication and a "slow gene" that replicates more slowly at the gene level, but which confers an advantage for protocell-level reproduction. Protocell-level replication capacity depends on cellular composition of fast and slow genes. We use a partial differential equation to describe how the composition of genes within protocells evolves over time under within-cell and between-cell competition, considering an infinite population of protocells that each contain infinitely many genes. We find that the gene-level advantage of fast replicators casts a long shadow on the multilevel dynamics of protocell evolution: no level of between-protocell competition can produce coexistence of the fast and slow replicators when the two genes are equally needed for protocell-level reproduction. By introducing a "dimer replicator" consisting of a linked pair of the slow and fast genes, we show analytically that coexistence between the two genes can be promoted in pairwise multilevel competition between fast and dimer replicators, and provide numerical evidence for coexistence in trimorphic competition between fast, slow, and dimer replicators. Our results suggest that dimerization, or the formation of a simple chromosome-like dimer replicator, can help to overcome the shadow of lower-level selection and work in concert with deterministic multilevel selection in protocells featuring high gene copy number to allow for the coexistence of two genes that are complementary at the protocell level but compete at the level of individual gene-level replication. These results for the PDE model complement existing results on the benefits of dimerization in the case of low genetic copy number, for which it has been shown that genetic linkage can help to overcome the stochastic loss of necessary genetic templates.

Mechanistic theory predicts the effects of temperature and humidity on inactivation of SARS-CoV-2 and other enveloped viruses.

Ambient temperature and humidity strongly affect inactivation rates of enveloped viruses, but a mechanistic, quantitative theory of these effects has been elusive. We measure the stability of SARS-CoV-2 on an inert surface at nine temperature and humidity conditions and develop a mechanistic model to explain and predict how temperature and humidity alter virus inactivation. We find SARS-CoV-2 survives longest at low temperatures and extreme relative humidities (RH); median estimated virus half-life is >24 hr at 10°C and 40% RH, but ∼1.5 hr at 27°C and 65% RH. Our mechanistic model uses fundamental chemistry to explain why inactivation rate increases with increased temperature and shows a U-shaped dependence on RH. The model accurately predicts existing measurements of five different human coronaviruses, suggesting that shared mechanisms may affect stability for many viruses. The results indicate scenarios of high transmission risk, point to mitigation strategies, and advance the mechanistic study of virus transmission.

Asynchrony between virus diversity and antibody selection limits influenza virus evolution.

Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously-infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within-host. They also suggest new avenues for improving influenza control.

Mechanistic theory predicts the effects of temperature and humidity on inactivation of SARS-CoV-2 and other enveloped viruses.

Environmental conditions affect virus inactivation rate and transmission potential. Understanding those effects is critical for anticipating and mitigating epidemic spread. Ambient temperature and humidity strongly affect the inactivation rate of enveloped viruses, but a mechanistic, quantitative theory of those effects has been elusive. We measure the stability of the enveloped respiratory virus SARS-CoV-2 on an inert surface at nine temperature and humidity conditions and develop a mechanistic model to explain and predict how temperature and humidity alter virus inactivation. We find SARS-CoV-2 survives longest at low temperatures and extreme relative humidities; median estimated virus half-life is over 24 hours at 10 °C and 40 % RH, but approximately 1.5 hours at 27 °C and 65 % RH. Our mechanistic model uses simple chemistry to explain the increase in virus inactivation rate with increased temperature and the U-shaped dependence of inactivation rate on relative humidity. The model accurately predicts quantitative measurements from existing studies of five different human coronaviruses (including SARS-CoV-2), suggesting that shared mechanisms may determine environmental stability for many enveloped viruses. Our results indicate scenarios of particular transmission risk, point to pandemic mitigation strategies, and open new frontiers in the mechanistic study of virus transmission.

Eco-evolutionary significance of "loners".

Loners-individuals out of sync with a coordinated majority-occur frequently in nature. Are loners incidental byproducts of large-scale coordination attempts, or are they part of a mosaic of life-history strategies? Here, we provide empirical evidence of naturally occurring heritable variation in loner behavior in the model social amoeba Dictyostelium discoideum. We propose that Dictyostelium loners-cells that do not join the multicellular life stage-arise from a dynamic population-partitioning process, the result of each cell making a stochastic, signal-based decision. We find evidence that this imperfectly synchronized multicellular development is affected by both abiotic (environmental porosity) and biotic (signaling) factors. Finally, we predict theoretically that when a pair of strains differing in their partitioning behavior coaggregate, cross-signaling impacts slime-mold diversity across spatiotemporal scales. Our findings suggest that loners could be critical to understanding collective and social behaviors, multicellular development, and ecological dynamics in D. discoideum. More broadly, across taxa, imperfect coordination of collective behaviors might be adaptive by enabling diversification of life-history strategies.