Antagonistic pleiotropy and the evolution of extraordinary lifespans in eusocial organisms

Queens of eusocial species live extraordinarily long compared to their workers. So far, it has been argued that these lifespan divergences are readily explained by the classical evolutionary theory of ageing. As workers predominantly perform risky tasks, such as foraging and nest defense, and queens stay in the well-protected nests, selection against harmful genetic mutations expressed in old age should be weaker in workers than in queens due to caste differences in extrinsic mortality risk, and thus, lead to the evolution of longer queen and shorter worker lifespans. However, these arguments have not been supported by formal models. Here, we present a model for the evolution of caste-specific ageing in social insects, based on Williams’ antagonistic pleiotropy theory of ageing. In individual-based simulations, we assume that mutations with antagonistic fitness effects can act within castes, that is, mutations in early life are accompanied by an antagonistic effect acting in later life, or between castes, where antagonistic effects emerge due to caste antagonism or indirect genetic effects between castes. In monogynous social insect species with sterile workers, large lifespan divergences between castes evolved under all different scenarios of antagonistic effects, but regardless of the degree of caste-specific extrinsic mortality. Mutations with antagonistic fitness effects within castes reduced lifespans of both castes, while mutations with between-caste antagonistic effects decreased worker lifespans more than queen lifespans, and consequently increased lifespan divergences. Our results challenge the central explanatory role of extrinsic mortality for caste-specific ageing in eusocial organisms and suggest that antagonistic pleiotropy affects castes differently due to reproductive monopolization by queens, hence, reproductive division of labor. Finally, these findings provide new insights into the evolution of tissue-specific ageing in multicellular organisms in general

The evolution of ageing in cooperative breeders

Cooperatively breeding animals live longer than their solitary counterparts. The traditional explanation for this is that cooperative breeding evolves more readily in long-lived species. Here, we reverse this argument and show that long lifespans are an evolutionary consequence of cooperative breeding. Natural selection favours a delayed onset of senescence in cooperative breeders, relative to solitary breeders, because cooperative breeders have a delayed age of first reproduction due to reproductive queueing. Especially long lifespans evolve in cooperative breeders with age-dependent reproductive queueing. Finally, we show that lower genetic relatedness among group members leads to the evolution of longer lifespans. This is because selection against higher mortality is weaker when mortality reduces competition between relatives. Our results link the evolutionary theory of ageing with kin selection theory, demonstrating that the evolution of ageing in cooperative breeders is driven by the timing of reproduction and kin structure within breeding territories

Resource sharing leads to the emergence of division of labour

Division of labour occurs in a broad range of organisms. Yet, how division of labour can emerge in the absence of pre-existing interindividual differences is poorly understood. Using a simple but realistic model, we show that in a group of initially identical individuals, division of labour emerges spontaneously if returning foragers share part of their resources with other group members. In the absence of resource sharing, individuals follow an activity schedule of alternating between foraging and other tasks. If non-foraging individuals are fed by other individuals, their alternating activity schedule becomes interrupted, leading to task specialisation and the emergence of division of labour. Furthermore, nutritional differences between individuals reinforce division of labour. Such differences can be caused by increased metabolic rates during foraging or by dominance interactions during resource sharing. Our model proposes a plausible mechanism for the self-organised emergence of division of labour in animal groups of initially identical individuals. This mechanism could also play a role for the emergence of division of labour during the major evolutionary transitions to eusociality and multicellularity

Image-Guided Raman Spectroscopic Recovery of Canine Cortical Bone Contrast in Situ

Raman scattering provides valuable biochemical and molecular markers for studying bone tissue composition with use in predicting fracture risk in osteoporosis. Raman tomography can image through a few centimeters of tissue but is limited by low spatial resolution. X-ray computed tomography (CT) imaging can provide high-resolution image-guidance of the Raman spectroscopic characterization, which enhances the quantitative recovery of the Raman signals, and this technique provides additional information to standard imaging methods. This hypothesis was tested in data measured from Teflon tissue phantoms and from a canine limb. Image-guided Raman spectroscopy (IG-RS) of the canine limb using CT images of the tissue to guide the recovery recovered a contrast of 145:1 between the cortical bone and background. Considerably less contrast was found without the CT image to guide recovery. This study presents the first known IG-RS results from tissue and indicates that intrinsically high contrasts (on the order of a hundred fold) are available

MODELING THE ROOT-KNOT NEMATODE/NUTSEDGE PEST COMPLEX: PERSPECTIVES FROM WEED SCIENCE, NEMATOLOGY AND STATISTICS

Previous research by the authors has established that southern root-knot nematode (SRKN, Meloidogyne incognita (Kofoid & White) Chitwood) and yellow and purple nutsedge (YNS, Cyperus esculentus L. and PNS, C. rotundus L.) form a pest-complex that adversely affects a wide variety of crops in the southern and western U.S. These pests appear to have co-evolved a mutually-beneficial relationship that promotes the survival of both nematodes and weeds to the detriment of crops. Traditional management has usually targeted one pest at a time, but managing this pest complex requires that all members of the complex be managed simultaneously. A series of experiments was performed to determine if this specific pest complex could be managed through crop-rotation using a non-dormant M. incognita-resistant variety of alfalfa (Medicago sativa) which can aggressively compete with, and hence decrease, occurrence of both species of nutsedges (NS), and subsequently decrease SRKN by decreasing the availability of root systems of host plants. A previous journal article discussed predicting counts of SRKN second-stage juveniles (SRKN-J2) as a function of YNS and PNS plant counts from a two-year alfalfa rotation experiment, using the Poisson distribution and a scale parameter to handle problems of overdispersion. In this paper, we examine three generalizations of the Poisson distribution that allow for the count variance being larger than the mean count: the Generalized Poisson, the Zero-Inflated Poisson (ZIP), and the Poisson Hurdle. The ZIP and Hurdle Poisson distributions both account for zero counts as a separate part of the distribution, while the Generalized Poisson incorporates a separate parameter that increases the variance relative to the mean. Different biological scenarios are presented for which each of these three general Poisson distributions might be logically appropriate. In addition, we use the alfalfa rotation data to present comparisons of fitted regression models of the three general Poisson distributions to the results from the previous analysis using the Poisson. For this data, there was no single probability distribution that worked best for all six sampling dates (three in each of the two years). This is not surprising in that over time the alfalfa rotation was, as planned, decreasing both nutsedge and nematode counts, thus presenting a moving target for the modeling process

Multiscale Modeling, Simulations, and Experiments of Coating Growth on Nanofibers. Part Ii. Deposition

This work is Part II of an integrated experimental/modeling investigation of a procedure to coat nanofibers and core-clad nanostructures with thin-film materials using plasma-enhanced physical vapor deposition. In the experimental effort, electrospun polymer nanofibers are coated with aluminum materials under different operating conditions to observe changes in the coating morphology. This procedure begins with the sputtering of the coating material from a target. Part I [J. Appl. Phys. 98, 044303 (2005)] focused on the sputtering aspect and transport of the sputtered material through the reactor. That reactor level model determines the concentration field of the coating material. This field serves as input into the present species transport and deposition model for the region surrounding an individual nanofiber. The interrelationships among processing factors for the transport and deposition are investigated here from a detailed modeling approach that includes the salient physical and chemical phenomena. Solution strategies that couple continuum and atomistic models are used. At the continuum scale, transport dynamics near the nanofiber are described. At the atomic level, molecular dynamics (MD) simulations are used to study the deposition and sputtering mechanisms at the coating surface. Ion kinetic energies and fluxes are passed from the continuum sheath model to the MD simulations. These simulations calculate sputtering and sticking probabilities that in turn are used to calculate parameters for the continuum transport model. The continuum transport model leads to the definition of an evolution equation for the coating-free surface. This equation is solved using boundary perturbation and level set methods to determine the coating morphology as a function of operating conditions. (c) 2005 American Institute of Physics

Non-Invasive Raman Tomographic Imaging of Canine Bone Tissue

Raman spectroscopic diffuse tomographic imaging has been demonstrated for the first time. It provides a noninvasive, label-free modality to image the chemical composition of human and animal tissue and other turbid media. This technique has been applied to image the composition of bone tissue within an intact section of a canine limb. Spatially distributed 785-nm laser excitation was employed to prevent thermal damage to the tissue. Diffuse emission tomography reconstruction was used, and the location that was recovered has been confirmed by micro-computed tomography (micro-CT) images. With recent advances, diffuse tomography shows promise for in vivo clinical imaging.1, 2 In principle, algorithms developed for fluorescence imaging in tissue can be applied to Raman signals. Although the Raman effect is weaker than fluorescence, the scattered signal is detectable, and thus tomography is achievable. Here we demonstrate the first diffuse tomography reconstructions based on Raman scatter. Raman mapping and imaging are well-established techniques for examining material surfaces.3 Subsurface mapping of simple planar objects was reported recently4, 5 using fiber optic probes with spatially separated injection and collection fibers.6 Noninvasive measurements of bone Raman spectra were demonstrated at depths of5mm role= presentation \u3e5mm below the skin.5 Bone is promising for Raman tomography because the spectra are rich in compositional information,7 which reflects bone maturity and health. Spectroscopically measured bone composition changes have been correlated with aging8 and susceptibility to osteoporotic fracture.9 The Raman spectrum of bone mineral is easily distinguished from the spectra of proteins and other organic tissue constituents, facilitating recovery of even weak signals by multivariate techniques. Assessments of bone quantity and quality are essential to detect and monitor fracture risk and fracture healing with disease or injury. Common sites for fracture with osteoporosis are the spine, proximal femur, and distal radius. Stress fractures are most frequently seen in the weight-bearing sites of the tibia and metatarsals. Fracture risk depends on bone geometry, architecture, and material properties, as well as the nature of applied load (magnitude, rate, and direction). As a result, noninvasive imaging and nondestructive analysis methods have been developed to assess many of these bone attributes that are increasingly important to clinical practice and basic research in orthopedics.10 Current clinical in vivo methods include dual-energy x-ray absorptiometry (DXA), quantitative computed tomography (QCT), magnetic resonance imaging (MRI), ultrasound, and most recently, high-resolution peripheral QCT. Ex vivo analyses of bone specimens from patients or animals have also utilized these and other techniques. In this study, we couple micro-computed tomography (micro-CT) and diffuse optical tomography with Raman spectroscopy to recover spatial and composition information from bone tissue ex vivo. We demonstrate the first reconstruction-based recovery of Raman signals through thick tissues to yield molecular information about subsurface bone tissue. Reconstructions from transcutaneous Raman measurements are challenging, because layers of skin, muscle, fat, and connective tissue lie over the bone sites of interest. These layers have different optical properties and thus variably scatter and polarize the injected light. We chose a canine model because of specimen availability and a bone size similar to human bone. We selected the tibia, a site that is clinically important and has relatively few overlying soft tissues. Measurements were made on the medial surface, where the only additional optical barrier is the crural extensor retinaculum ligament. The canine hind limb was harvested from an animal euthanized in an approved (UCUCA) University of Michigan study. The section of the limb distal to the knee was excised and scanned using in vivo micro-CT (eXplore Locus RS, GE Healthcare, Ontario, Canada). The tibia was scanned at80kV role= presentation \u3e80kV and 450μA role= presentation \u3e450μA with an exposure time of 100ms role= presentation \u3e100ms using a 360-deg scan technique. The image was reconstructed at a 93-μm role= presentation \u3e93-μm voxel resolution [Fig. 1a ]