Search for: All records

Abstract Affinity precipitation is a powerful separation method in that it combines the binding selectivity of affinity chromatography with precipitation of captured biomolecules via phase separation triggered by small changes in the environment, e.g., pH, ionic strength, temperature, light, etc. Elastin‐like polypeptides (ELPs) are thermally responsive biopolymers composed of pentapeptide repeats VPGVG that undergo reversible phase separation, where they aggregate when temperature and/or salt concentration are increased. Here we describe the generation of an ELP fusion to a soluble streptavidin mutant that enables rapid purification of anyStrep‐tag II fusion protein of interest. This heterobifunctional protein takes advantage of the native tetrameric structure of streptavidin, leading to binding‐induced multivalent crosslinking upon protein capture. The efficient biotin‐mediated dissociation of the boundStrep‐tag II fusion protein from the streptavidin‐ELP capturing scaffold allows for mild elution conditions. We also show that this platform is particularly effective in the purification of a virus‐like particle (VLP)‐like E2 protein nanoparticle, likely because the high valency of the protein particle causes binding‐induced crosslinking and precipitation. Considering the importance of VLP for gene therapy applications, we believe this is a particularly exciting advance. We demonstrated this feasibility by the efficient purification of a VLP‐like E2 protein nanoparticle as a surrogate. 

Mechanical bonds arise between molecules that contain interlocked subunits, such as one macrocycle threaded through another. Within polymers, these linkages will confer distinctive mechanical properties and other emergent behaviors, but polymerizations that form mechanical bonds efficiently and use simple monomeric building blocks are rare. In this work, we introduce a solid-state polymerization in which one monomer infiltrates crystals of another to form a macrocycle and mechanical bond at each repeat unit of a two-dimensional (2D) polymer. This mechanically interlocked 2D polymer is formed as a layered solid that is readily exfoliated in common organic solvents, enabling spectroscopic characterization and atomic-resolution imaging using advanced electron microscopy techniques. The 2D mechanically interlocked polymer is easily prepared on multigram scales, which, along with its solution processibility, enables the facile fabrication of composite fibers with Ultem that exhibit enhanced stiffness and strength. 

Most large carnivores feed on prey infrequently and may expend large amounts of energy to locate, capture and kill their prey. This makes them probabilistically vulnerable to fluctuating rates of energy acquisition over time, especially within the increasingly human-altered landscapes that dominate their remaining range. Consequently, quantifying their hunting behaviors and success rates is critical, yet direct observation of these events is rarely feasible. We theorized that we could determine prey pursuit and capture in African wild dogs(Lycaon pictus)using a mechanistic approach by constructing Boolean algorithms applied to accelerometer data derived from collar-mounted tags. Here, we used this method and then iteratively improved algorithms by testing them on observed hunts and kills of collared packs. Using this approach on 47 days of acceleration from three wild dogs in three packs, we identified 29 hunts with 10 kills, all of which were confirmed by direct observation except for a single kill. Our results demonstrate that hunting effort and success can largely be determined from acceleration data using a mechanistic approach. This is particularly valuable when such behaviors are rarely quantified and offers a template for research on foraging in canid species, while also contributing to the expanding body of literature that employs similar methods to quantify hunting in large carnivores. 

Large herbivores are in decline in much of the world, including sub-Saharan Africa, and true apex carnivores like the lion (Panthera leo) decline in parallel with their prey. As a consequence, competitively subordinate carnivores like the African wild dog (Lycaon pictus) are simultaneously experiencing a costly reduction in resources and a beneficial reduction in dominant competitors. The net effect is not intuitively obvious, but wild dogs’ density, survival, and reproduction are all low in areas that are strongly affected by prey depletion. To assess whether these correlations are causal, we tested the hypothesized mechanism, using data from 13 wild dog packs in two ecosystems to relate the energetic costs and benefits of hunting to variation in prey density, while controlling for the effects of local lion density, pack size, the number of dependent pups, and the level of protection. All of these variables affected the energetic costs and benefits of hunting. In areas with low prey density, the magnitude of movements and vectorial dynamic body acceleration (a measure of energy expenditure) both increased, the mass of killed prey decreased, and the number of kills per day did not change detectably. Programs to reduce or reverse the decline of large herbivore populations should be an effective means of improving the status of endangered subordinate competitors like the wild dog, and should be a high priority. Our results demonstrate the utility of research that integrates data from biomonitoring with direct, long-term observation of endangered species, their competitors, and their resources. 

ABSTRACT Prey depletion threatens many carnivore species across the world and can especially threaten low‐density subordinate competitors, particularly if subordinates are limited to low densities by their dominant competitors. Understanding the mechanisms that drive responses of carnivore density to prey depletion is not only crucial for conservation but also elucidates the balance between top‐down and bottom‐up limitations within the large carnivore guild. To avoid predation, competitively subordinate African wild dogs typically avoid their dominant competitors (lions) and the prey rich areas they are associated with, but no prior research has tested whether this pattern persists in ecosystems with anthropogenically‐reduced prey density, and reduced lion density as a result. We used spatial data from wild dogs and lions in the prey‐depleted Greater Kafue Ecosystem to test if wild dogs continue to avoid lions (despite their low density), and consequently avoid habitats with higher densities of their dominant prey species. We found that although lion density is 3X lower than comparable ecosystems, wild dogs continue to strongly avoid lions, and consequently avoid habitats associated with their two most important prey species. Although the density of lions in the GKE is low due to prey depletion, their competitive effects on wild dogs remain strong. These effects are likely compounded by prey‐base homogenization, as lions in the GKE now rely heavily on the same prey preferred by wild dogs. These results suggest that a reduction in lion density does not necessarily reduce competition, and helps explain why wild dogs decline in parallel with their dominant competitors in ecosystems suffering from anthropogenic prey depletion. Protecting prey populations within the few remaining strongholds for wild dogs is vitally important to avoid substantial population declines. Globally, understanding the impacts of prey depletion on carnivore guild dynamics should be an increasingly important area of focus for conservation. 

Abstract Many African large carnivore populations are declining due to decline of the herbivore populations on which they depend. The densities of apex carnivores like the lion and spotted hyena correlate strongly with prey density, but competitively subordinate carnivores like the African wild dog benefit from competitive release when the density of apex carnivores is low, so the expected effect of a simultaneous decrease in resources and dominant competitors is not obvious.Wild dogs in Zambia's South Luangwa Valley Ecosystem occupy four ecologically similar areas with well‐described differences in the densities of prey and dominant competitors due to spatial variation in illegal offtake.We used long‐term monitoring data to fit a Bayesian integrated population model (IPM) of the demography and dynamics of wild dogs in these four regions. The IPM used Leslie projection to link a Cormack–Jolly–Seber model of area‐specific survival (allowing for individual heterogeneity in detection), a zero‐inflated Poisson model of area‐specific fecundity and a state‐space model of population size that used estimates from a closed mark–capture model as the counts from which (latent) population size was estimated.The IPM showed that both survival and reproduction were lowest in the region with the lowest density of preferred prey (puku,Kobus vardoniiand impala,Aepyceros melampus), despite little use of this area by lions. Survival and reproduction were highest in the region with the highest prey density and intermediate in the two regions with intermediate prey density. The population growth rate () was positive for the population as a whole, strongly positive in the region with the highest prey density and strongly negative in the region with the lowest prey density.It has long been thought that the benefits of competitive release protect African wild dogs from the costs of low prey density. Our results show that the costs of prey depletion overwhelm the benefits of competitive release and cause local population decline where anthropogenic prey depletion is strong. Because competition is important in many guilds and humans are affecting resources of many types, it is likely that similarly fundamental shifts in population limitation are arising in many systems. 

Groundwater discharge from high tropical islands can have a significant influence on the biochemistry of reef ecosystems. Recent studies have suggested that a portion of groundwater may underflow the reefs to be discharged, either through the reef flat or toward the periphery of the reef system. Understanding of this potential discharge process is limited by the characterization of subsurface reef structures in these environments. A geophysical method was used in this study to profile the reef surrounding the high volcanic island of Mo’orea, French Polynesia. Boat-towed continuous resistivity profiling (CRP) revealed electrically resistive features at about 10–15 m depth, ranging in width from 30 to 200 m. These features were repeatable in duplicate survey lines, but resolution was limited by current-channeling through the seawater column. Anomalous resistivity could represent the occurrence of freshened porewater confined within the reef, but a change in porosity due to secondary cementation cannot be ruled out. Groundwater-freshened reef porewater has been observed near-shore on Mo’orea and suggested elsewhere using similar geophysical surveys, but synthetic models conducted as part of this study demonstrate that CRP alone is insufficient to draw these conclusions. These CRP surveys suggest reefs surrounding high islands may harbor pathways for terrestrial groundwater flow, but invasive sampling is required to demonstrate the role of groundwater in terrestrial runoff. 

Abstract Polymers are ubiquitous to almost every aspect of modern society and their use in medical products is similarly pervasive. Despite this, the diversity in commercial polymers used in medicine is stunningly low. Considerable time and resources have been extended over the years towards the development of new polymeric biomaterials which address unmet needs left by the current generation of medical-grade polymers. Machine learning (ML) presents an unprecedented opportunity in this field to bypass the need for trial-and-error synthesis, thus reducing the time and resources invested into new discoveries critical for advancing medical treatments. Current efforts pioneering applied ML in polymer design have employed combinatorial and high throughput experimental design to address data availability concerns. However, the lack of available and standardized characterization of parameters relevant to medicine, including degradation time and biocompatibility, represents a nearly insurmountable obstacle to ML-aided design of biomaterials. Herein, we identify a gap at the intersection of applied ML and biomedical polymer design, highlight current works at this junction more broadly and provide an outlook on challenges and future directions. 

Many African large carnivore populations are declining due to decline of the herbivore populations on which they depend. We recently noted that the densities of true apex carnivores like the lion and spotted hyena correlate strongly with prey density, but competitively subordinate carnivores like the African wild dog benefit from competitive release when density of apex carnivores is low, so the expected effect of a simultaneous decrease in resources and dominant competitors is not obvious. We found that when prey density drops below a tipping point, the relationship of wild dog density to prey density changes sign, and wild dog density declines. We also noted that ‘prey depletion provides a mechanistically direct explanation of patterns in wild dog dynamics that have been attributed to climate change’ (Creel et al., 2023). Woodroffe et al. concur that prey depletion is an important threat, but suggest that we fail to understand the logic of their assertion that “climate change is likely to cause population collapse” (Rabaiotti et al., 2022), because the “identification of climate change as a threat is not based upon observed temporal trends in wild dog demography”. This statement misses our fundamental point. The data that Woodroffe et al. analyzed were collected over a period with rising temperatures and declining prey populations, so whether or not one tests for a time trend in demography, the data themselves are affected by two patterns: