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Foraging mammals exhibit a familiar yet poorly characterized phenomenon, ‘alternation’, a pause to sniff in the air preceded by the animal rearing on its hind legs or raising its head. Rodents spontaneously alternate in the presence of airflow, suggesting that alternation serves an important role during plume-tracking. To test this hypothesis, we combine fully resolved simulations of turbulent odor transport and Bellman optimization methods for decision-making under partial observability. We show that an agent trained to minimize search time in a realistic odor plume exhibits extensive alternation together with the characteristic cast-and-surge behavior observed in insects. Alternation is linked with casting and occurs more frequently far downwind of the source, where the likelihood of detecting airborne cues is higher relative to ground cues. Casting and alternation emerge as complementary tools for effective exploration with sparse cues. A model based on marginal value theory captures the interplay between casting, surging, and alternation.

We consider the problem of olfactory searches in a turbulent environment. We focus on agents that respond solely to odor stimuli, with no access to spatial perception nor prior information about the odor. We ask whether navigation to a target can be learned robustly within a sequential decision making framework. We develop a reinforcement learning algorithm using a small set of interpretable olfactory states and train it with realistic turbulent odor cues. By introducing a temporal memory, we demonstrate that two salient features of odor traces, discretized in a few olfactory states, are sufficient to learn navigation in a realistic odor plume. Performance is dictated by the sparse nature of turbulent odors. An optimal memory exists which ignores blanks within the plume and activates a recovery strategy outside the plume. We obtain the best performance by letting agents learn their recovery strategy and show that it is mostly casting cross wind, similar to behavior observed in flying insects. The optimal strategy is robust to substantial changes in the odor plumes, suggesting minor parameter tuning may be sufficient to adapt to different environments. Many animals use odors to locate mates, food, and to avoid danger. Unlike light, which travels in straight lines, odors are carried by turbulent air or water, leading to intermittent whiffs separated by long gaps with no detectable scent. These patchy odor landscapes can make it difficult for animals to decide which direction to move in. Despite these challenges, animals are remarkably good at using odors to navigate. While previous studies have modelled this behavior computationally, the most principled models often relied on complex concepts of memory, that were not directly interpretable. In particular, what must be remembered about past odor detections and for how long remained unclear. To investigate this, Rando et al. developed an algorithm that enables agents to learn to navigate by trial and error, responding only to a short excerpt of past odor detections. Agents had no prior knowledge about the odor nor access to spatial information, other than their ability to orient relative to the wind. The simulated environment mimicked realistic odor plumes in turbulent air and the algorithm was given a short-term memory to track changes in a limited set of specific odor-related signals over time. Analysis showed that there is an optimal length of memory that helps the agent ignore temporary gaps in the odor signal while still recognizing when it has fully exited the plume. This allowed the agent to activate a strategy to return to the scent plume only when truly necessary. When it was allowed to learn behavior both within and outside the plume, it performed better than when using fixed strategies based on animal behavior. Interestingly, the learned strategy often resembled the casting behavior, seen in flying insects, which involves a side-to-side search in the crosswind direction to relocate odor plumes. Overall, the work of Rando et al. shows that simple odor signals and a basic form of temporal memory are enough to learn effective navigation in turbulent environments with no prior knowledge of the odor environment. The algorithm performed reliably, reaching the odor source in 90% to 100% of trials. These findings help explain how animals might use short-memory of odor to navigate in space, even in unknown or variable environments and could be used to develop search algorithms for robots in complex real-world settings like disaster zones or polluted areas.

Most of the world's bacteria exist in robust, sessile communities known as biofilms, ubiquitously adherent to environmental surfaces from ocean floors to human teeth and notoriously resistant to antimicrobial agents. We report the surprising observation that Bacillus subtilis biofilm colonies and pellicles are extremely non-wetting, greatly surpassing the repellency of Teflon toward water and lower surface tension liquids. The biofilm surface remains nonwetting against up to 80% ethanol as well as other organic solvents and commerical biocides across a large and clinically important concentration range. We show that this property limits the penetration of antimicrobial liquids into the biofilm, severely compromising their efficacy. To highlight the mechanisms of this phenomenon, we performed experiments with mutant biofilms lacking ECM components and with functionalized polymeric replicas of biofilm microstructure. We show that the nonwetting properties are a synergistic result of ECM composition, multiscale roughness, reentrant topography, and possibly yet other factors related to the dynamic nature of the biofilm surface. Finally, we report the impenetrability of the biofilm surface by gases, implying defense capability against vapor-phase antimicrobials as well. These remarkable properties of B. subtilis biofilm, which may have evolved as a protection mechanism against native environmental threats, provide a new direction in both antimicrobial research and bioinspired liquid-repellent surface paradigms.

Animal behavior and neural recordings show that the brain is able to measure both the intensity and the timing of odor encounters. However, whether intensity or timing of odor detections is more informative for olfactory-driven behavior is not understood. To tackle this question, we consider the problem of locating a target using the odor it releases. We ask whether the position of a target is best predicted by measures of timing vs intensity of its odor, sampled for a short period of time. To answer this question, we feed data from accurate numerical simulations of odor transport to machine learning algorithms that learn how to connect odor to target location. We find that both intensity and timing can separately predict target location even from a distance of several meters; however, their efficacy varies with the dilution of the odor in space. Thus, organisms that use olfaction from different ranges may have to switch among different modalities. This has implications on how the brain should represent odors as the target is approached. We demonstrate simple strategies to improve accuracy and robustness of the prediction by modifying odor sampling and appropriately combining distinct measures together. To test the predictions, animal behavior and odor representation should be monitored as the animal moves relative to the target, or in virtual conditions that mimic concentrated vs dilute environments.

Bacterial biofilms are interface-associated colonies of bacteria embedded in an extracellular matrix that is composed primarily of polymers and proteins. They can be viewed in the context of soft matter physics: the rigid bacteria are analogous to colloids, and the extracellular matrix is a cross-linked polymer gel. This perspective is beneficial for understanding the structure, mechanics, and dynamics of the biofilm. Bacteria regulate the water content of the biofilm by controlling the composition of the extracellular matrix, and thereby controlling the mechanical properties. The mechanics of well-defined soft materials can provide insight into the mechanics of biofilms and, in particular, the viscoelasticity. Furthermore, spatial heterogeneities in gene expression create heterogeneities in polymer and surfactant production. The resulting concentration gradients generate forces within the biofilm that are relevant for biofilm spreading and survival.

Bacterial biofilms are organized communities of cells living in association with surfaces. The hallmark of biofilm formation is the secretion of a polymeric matrix rich in sugars and proteins in the extracellular space. In Bacillus subtilis, secretion of the exopolysaccharide (EPS) component of the extracellular matrix is genetically coupled to the inhibition of flagella-mediated motility. The onset of this switch results in slow expansion of the biofilm on a substrate. Different strains have radically different capabilities in surface colonization: Flagella-null strains spread at the same rate as wild type, while both are dramatically faster than EPS mutants. Multiple functions have been attributed to the EPS, but none of these provides a physical mechanism for generating spreading. We propose that the secretion of EPS drives surface motility by generating osmotic pressure gradients in the extracellular space. A simple mathematical model based on the physics of polymer solutions shows quantitative agreement with experimental measurements of biofilm growth, thickening, and spreading. We discuss the implications of this osmotically driven type of surface motility for nutrient uptake that may elucidate the reduced fitness of the matrix-deficient mutant strains.

Jellyfish and sea anemones fire single-use, venom-covered barbs to immobilize prey or predators. We previously showed that the anemone Nematostella vectensis uses a specialized voltage-gated calcium (Ca V ) channel to trigger stinging in response to synergistic prey-derived chemicals and touch (Weir et al., 2020). Here, we use experiments and theory to find that stinging behavior is suited to distinct ecological niches. We find that the burrowing anemone Nematostella uses uniquely strong Ca V inactivation for precise control of predatory stinging. In contrast, the related anemone Exaiptasia diaphana inhabits exposed environments to support photosynthetic endosymbionts. Consistent with its niche, Exaiptasia indiscriminately stings for defense and expresses a Ca V splice variant that confers weak inactivation. Chimeric analyses reveal that Ca V β subunit adaptations regulate inactivation, suggesting an evolutionary tuning mechanism for stinging behavior. These findings demonstrate how functional specialization of ion channel structure contributes to distinct organismal behavior.

Background The initial step of a number of human or plant fungal infections requires active penetration of host tissue. For example, active penetration of intestinal epithelia by Candida albicans is critical for dissemination from the gut into the bloodstream. However, little is known about how this fungal pathogen copes with resistive forces upon host cell invasion. Results In the present study, we have used PDMS micro-fabrication to probe the ability of filamentous C. albicans cells to penetrate and grow invasively in substrates of different stiffness. We show that there is a threshold for penetration that corresponds to a stiffness of ~ 200 kPa and that invasive growth within a stiff substrate is characterized by dramatic filament buckling, along with a stiffness-dependent decrease in extension rate. We observed a striking alteration in cell morphology, i.e., reduced cell compartment length and increased diameter during invasive growth, that is not due to depolarization of active Cdc42, but rather occurs at a substantial distance from the site of growth as a result of mechanical compression. Conclusions Our data reveal that in response to this compression, active Cdc42 levels are increased at the apex, whereas active Rho1 becomes depolarized, similar to that observed in membrane protrusions. Our results show that cell growth and morphology are altered during invasive growth, suggesting stiffness dictates the host cells that C. albicans can penetrate.

Because of their microscopic size, the forcibly ejected spores of ascomycete fungi are quickly brought to rest by drag. Nonetheless some apothecial species, including the pathogen Sclerotinia sclerotiorum, disperse with astonishing rapidity between ephemeral habitats. Here we show that by synchronizing the ejection of thousands of spores, these fungi create a flow of air that carries spores through the nearly still air surrounding the apothecium, around intervening obstacles, and to atmospheric currents and new infection sites. High-speed imaging shows that synchronization is self-organized and likely triggered by mechanical stresses. Although many spores are sacrificed to produce the favorable airflow, creating the potential for conflict among spores, the geometry of the spore jet physically targets benefits of the airflow to spores that cooperate maximally in its production. The ability to manipulate a local fluid environment to enhance spore dispersal is a previously overlooked feature of the biology of fungal pathogens, and almost certainly shapes the virulence of species including S. sclerotiorum. Synchronous spore ejection may also provide a model for the evolution of stable, self-organized behaviors.

Many types of bacteria form colonies that grow into physically robust and strongly adhesive aggregates known as biofilms. A distinguishing characteristic of bacterial biofilms is an extracellular polymeric substance (EPS) matrix that encases the cells and provides physical integrity to the colony. The EPS matrix consists of a large amount of polysaccharide, as well as protein filaments, DNA and degraded cellular materials. The genetic pathways that control the transformation of a colony into a biofilm have been widely studied, and yield a spatiotemporal heterogeneity in EPS production. Spatial gradients in metabolites parallel this heterogeneity in EPS, but nutrient concentration as an underlying physiological initiator of EPS production has not been explored. Here, we study the role of nutrient depletion in EPS production in Bacillus subtilis biofilms. By monitoring simultaneously biofilm size and matrix production, we find that EPS production increases at a critical colony thickness that depends on the initial amount of carbon sources in the medium. Through studies of individual cells in liquid culture we find that EPS production can be triggered at the single-cell level by reducing nutrient concentration. To connect the single-cell assays with conditions in the biofilm, we calculate carbon concentration with a model for the reaction and diffusion of nutrients in the biofilm. This model predicts the relationship between the initial concentration of carbon and the thickness of the colony at the point of internal nutrient deprivation.