Lilach Hadany

In recent years, senescence is increasingly understood as a process of damage accumulation that accelerates with age throughout an organism's lifespan. That understanding has rarely been introduced to senescence evolution theory. In classic models, including Mutation accumulation and Antagonistic pleiotropy, the intensity of selection over genes is determined by the timing of their effect on mortality. They conclude senescence evolution occurs because of weak selection on late‐acting genes. Here we explore, consistent with recent evidence, an alternative model: where genes affect mortality throughout an organism's lifespan, and the shape of this effect determines selection. We expanded Hamilton's classic model of senescence evolution using these notions. Our model takes into account evolutionary dynamics between external mortality risk, potential mortality risk from internal damage, reproduction start age, and reproduction rate. The analysis of the model suggests biological limitations on reducing the potential mortality risk from internal damage can lead to a positive feedback loop in senescence evolution where genes that slow senescence can increase selection for further senescence retardation. Our model sheds light on several phenomena, not fully explained by classic theory, including Peto's paradox, Strehler—Mildvan correlation, and negligible senescence.

Insects rely on plants’ visual, chemical, tactile, and electrical cues when making various decisions. A recent study demonstrated that dehydrated plants emit ultrasonic sounds within the auditory sensitivity range of many moth species. In this study, we sought to determine whether insects also rely on plant acoustic signals when making decisions. We investigated whether female moths rely on ultrasonic clicks which are typically produced by dehydrated plants when deciding where to oviposit. In the absence of an actual plant, the moths indeed preferred to lay their eggs in proximity to acoustic signals which represent dehydrating plants. Tracking the moths’ behavior prior to the decision showed that they examined both sides of the arena and gradually spent more time on the acoustic-playback side. Interestingly, when actual plants were added to the arena, the oviposition preference was reversed and the moths preferred silent plants, which is in accordance with their a priori preference for hydrated plants. Deafening the moths eliminated their preference, confirming that the choice was based on hearing. Moreover, the presence of male moths, including their auditory signals, did not affect their oviposition decision, suggesting that the response was specific to plant sound emissions. We reveal evidence for a first acoustic interaction between moths and plants, but as plants emit various sounds, our findings hint at the existence of more currently unknown insect-plant acoustic interactions.

Conflicts between individuals of the same species are common in nature and are mostly resolved with limited aggression. Several theoretical studies, such as the Hawk–Dove (HD) game model, investigate the evolution of limited aggression expressed during conflicts between individuals. These studies mainly focus on the individuals involved in the conflict and their genes. Recently accumulating evidence indicates that microbes are associated with diverse functions of their host and can affect host behavior. Here we extend the classic HD game model to include both the hosts and their microbes, examining how natural selection acts on the microbes. We find that nonaggressive host behavior is more likely to evolve and spread in a population when induced by the microbes residing in the host, compared to nonaggressive behavior induced by host genes. Horizontal transmission allows microbes to colonize new hosts, making their success dependent on the fitness of both the host and its opponent. Therefore, selection on the microbes favors reduced host aggressiveness under wider conditions compared to selection acting on genes alone. Our results suggest that microbes may help explain the ubiquity of nonviolent conflict resolution. Consequently, factors that alter the microbial composition within hosts may affect the aggressiveness level in host populations.

Recent studies revealed mechanisms by which the microbiome affects its host’s brain, behavior and wellbeing, and that dysbiosis – persistent microbiome-imbalance – is associated with the onset and progress of various chronic diseases, including addictive behaviors. Yet, understanding of the ecological and evolutionary processes that shape the host-microbiome ecosystem and affect the host state, is still limited. Here we propose that competition dynamics within the microbiome, associated with host-microbiome mutual regulation, may promote dysbiosis and aggravate addictive behaviors. We construct a mathematical framework, modeling the dynamics of the host-microbiome ecosystem in response to alterations. We find that when this ecosystem is exposed to substantial perturbations, the microbiome may shift towards a composition that reinforces the new host state. Such a positive feedback loop augments post-perturbation imbalances, hindering attempts to return to the initial equilibrium, promoting relapse episodes and prolonging addictions. We show that the initial microbiome composition is a key factor: a diverse microbiome enhances the ecosystem’s resilience, whereas lower microbiome diversity is more prone to lead to dysbiosis, exacerbating addictions. This framework provides evolutionary and ecological perspectives on host-microbiome interactions and their implications for host behavior and health, while offering verifiable predictions with potential relevance to clinical treatments.

Recent studies revealed mechanisms by which the microbiome affects its host’s brain, behavior and wellbeing, and that dysbiosis – persistent microbiome-imbalance – is associated with the onset and progress of various chronic diseases, including addictive behaviors. Yet, understanding of the ecological and evolutionary processes that shape the host-microbiome ecosystem and affect the host state, is still limited. Here we propose that competition dynamics within the microbiome, associated with host-microbiome mutual regulation, may promote dysbiosis and aggravate addictive behaviors. We constructed a mathematical framework, modeling the dynamics of the host-microbiome ecosystem in response to alterations. We find that when this ecosystem is exposed to substantial perturbations, the microbiome may shift towards a composition that reinforces the new host state. Such positive feedback loop augments post-perturbation imbalances, hindering attempts to return to the initial equilibrium, thus promoting relapse episodes and prolonged addictions. We also find that the initial microbiome composition is a key factor: a diverse microbiome enhances the ecosystem’s resilience, whereas lower microbiome diversity is more prone to reach dysbiosis, exacerbating addictions. This framework provides novel evolutionary and ecological perspectives on host-microbiome interactions and their implications for host behavior and health, while offering verifiable predictions with potential relevance to clinical treatments.

Background and objectives: Social and behavioral non-pharmaceutical interventions (NPIs), such as mask-wearing, social distancing and travel restrictions, as well as diagnostic tests, have been broadly implemented in response to the COVID-19 pandemic. Epidemiological models and data analysis affirm that wide adoption of NPIs helps to control the pandemic. However, SARS-CoV-2 has extensively demonstrated its ability to evolve. Therefore, it is crucial to examine how NPIs may affect the evolution of the virus. Such evolution could have important effects on the spread and impact of the pandemic. Methodology: We used evo-epidemiological models to examine the effect of NPIs and testing on two evolutionary trajectories for SARS-CoV-2: attenuation and test evasion. Results: Our results show that when stronger measures are taken, selection may act to reduce disease severity. Additionally, the timely application of NPIs could significantly affect the competition between viral strains, favoring the milder strain. Furthermore, a higher testing rate can select for a test-evasive viral strain, even if that strain is less infectious than the detectable competing strain. Importantly, if a less detectable strain evolves, epidemiological metrics such as confirmed daily cases may distort our assessment of the pandemic. Conclusions and implications: Our results highlight the important implications NPIs can have on the evolution of SARS-CoV-2. Lay Summary: We used evo-epidemiological models to examine the effect of non-pharmaceutical interventions and testing on two evolutionary trajectories for SARS-CoV-2: attenuation and test evasion. Our results show that when stronger measures are taken, selection may act to reduce disease severity.

Summary: Locust plagues are a notorious, ancient phenomenon. These swarming pests tend to aggregate and perform long migrations, decimating cultivated fields along their path. When population density is low, however, the locusts will express a cryptic, solitary, non‐aggregating phenotype that is not considered a pest. Although the transition from the solitary to the gregarious phase has been well studied, associated shifts in the locust's microbiome have yet to be addressed. Here, using 16S rRNA amplicon sequencing, we compared the bacterial composition of solitary desert locusts before and after a phase transition. Our findings revealed that the microbiome is altered during the phase transition, and that a major aspect of this change is the acquisition of Weissella (Firmicutes). Our findings led us to hypothesize that the locust microbiome plays a role in inducing aggregation behaviour, contributing to the formation and maintenance of a swarm. Employing a mathematical model, we demonstrate the potential evolutionary advantage of inducing aggregation under different conditions; specifically, when the aggregation‐inducing microbe exhibits a relatively high horizontal transmission rate. This is the first report of a previously unknown and important aspect of locust phase transition, demonstrating that the phase shift includes a shift in the gut and integument bacterial composition.

The global decline in plant biodiversity throughout recent human history has attracted broad scientific attention, as biodiversity plays a key role in promoting a productive ecosystem. Pollination is a major factor in plant survival but carries an additional cost for locally rare plant species: they are likely to receive high levels of incompatible pollen that does not contribute to reproduction and can even impair seed production. Therefore, floral traits that diminish the risk of incompatible pollen receipt may be favoured by natural selection. We developed a theoretical framework to explore the influence of floral morphological complexity on competition for pollinator services between self‐incompatible simultaneously flowering plant species. We show that when a rare plant species is morphologically complex, it may persist in competition with a more common species. Synthesis. The results show that, through its influence on pollinator foraging behaviour, complex floral morphology can contribute to the maintenance of plant diversity.

Social and behavioral non-pharmaceutical interventions (NPIs), such as mask-wearing, social distancing, and travel restrictions, as well as diagnostic tests, have been broadly implemented in response to the COVID-19 pandemic. Epidemiological models and data analysis affirm that wide adoption of NPIs helps to control the pandemic. However, SARS-CoV-2 has extensively demonstrated its ability to evolve. Therefore, it is crucial to examine how NPIs may affect the evolution of the virus. Such evolution could have important effects on the spread and impact of the pandemic. We used evo-epidemiological models to examine the effect of non-pharmaceutical interventions and testing on two evolutionary trajectories for SARS-CoV-2: attenuation and test evasion. Our results show that when stronger measures are taken, selection may act to reduce virulence. Additionally, the timely application of NPIs could significantly affect the competition between viral strains, favoring reduced virulence. Furthermore, a higher testing rate can select for a test-evasive viral strain, even if that strain is less infectious than the detectable competing strain. Importantly, if a less detectable strain evolves, epidemiological metrics such as confirmed daily cases may distort our assessment of the pandemic. Our results highlight the important implications NPIs can have on the evolution of SARS-CoV-2.