The chimpanzee and cynomolgus monkey erythrocyte immune adherence receptors are encoded by CR1-like genes

The human erythrocyte immune adherence (IA) receptor is the Mr 220,000 type one complement receptor, or CR1. Nonhuman primate IA receptors are comprised of a family of smaller erythrocyte complement receptors (E-CRs) of unknown origin. Recently, the Mr 65,000 baboon E-CR was identified as a glycophosphatidylinositol (GPI)-linked protein encoded by a partially duplicated CR1 gene termed CR1-like. The purpose of this study was to determine the genetic origin of the Mr 75,000 chimpanzee E-CR. Two previously identified cDNAs, an alternative splice product of CR1 termed CR1a and a chimpanzee form of CR1-like, were synthesized and amplified from chimpanzee bone marrow RNA, and transiently expressed in COS-7 cells. By SDS-PAGE, the CR1a protein had a relative mobility slightly greater than chimpanzee E-CR, whereas that of the CR1-like protein was slightly less. Affinity chromatography demonstrated that little chimpanzee CR1a bound to human C3i linked to activated thiol-Sepharose (C3i-ATS), while over 50% of both chimpanzee CR1-like and chimpanzee E-CR bound to C3i-ATS. Treatment with phosphatidylinositol-specific phospholipase C (PIPLC) to assess GPI linkage released E-CR from chimpanzee erythrocytes, and E-CR from cynomolgus monkey erythrocytes. Based on size, ligand-binding specificity, and PIPLC sensitivity, we conclude that the chimpanzee E-CR is encoded by the CR1-like gene. Furthermore, based on PIPLC sensitivity, the cynomolgus monkey E-CR is also likely encoded by a CR1-like sequence. Thus, CR1-like, which is a genetic element of unknown significance in humans, is the gene that encodes the erythrocyte IA receptor of many nonhuman primates.     

Semiochemicals Influencing the Host-finding Behaviour of Varroa Destructor

Studies of Varroa destructor orientation to honey bees were undertaken to isolate discrete chemical compounds that elicit host-finding activity. Petri dish bioassays were used to study cues that evoked invasion behaviour into simulated brood cells and a Y-tube olfactometer was used to evaluate varroa orientation to olfactory volatiles. In Petri dish bioassays, mites were highly attracted to live L5 worker larvae and to live and freshly freeze-killed nurse bees. Olfactometer bioassays indicated olfactory orientation to the same type of hosts, however mites were not attracted to the odour produced by live pollen foragers. The odour of forager hexane extracts also interfered with the ability of mites to localize and infest a restrained nurse bee host. Varroa mites oriented to the odour produced by newly emerged bees (<16 h old) when choosing against a clean airstream, however in choices between the odours of newly emerged workers and nurses, mites readily oriented to nurses when newly emerged workers were <3 h old. The odour produced by newly emerged workers 18–20 h of age was equally as attractive to mites as that of nurse bees, suggesting a changing profile of volatiles is produced as newly emerged workers age. Through fractionation and isolation of active components of nurse bee-derived solvent washes, two honey bee Nasonov pheromone components, geraniol and nerolic acid, were shown to confuse mite orientation. We suggest that V. destructor may detect relative concentrations of these compounds in order to discriminate between adult bee hosts, and preferentially parasitize nurse bees over older workers in honey bee colonies. The volatile profile of newly emerged worker bees also may serve as an initial stimulus for mites to disperse before being guided by allomonal cues produced by older workers to locate nurses. Fatty acid esters, previously identified as putative kairomones for varroa, proved to be inactive in both types of bioassays.     

Increasing sensor flexibility through neuromodulation

Both biological and man-made motor control networks require input from sensors to allow for modification of the motor program. Real sensory neurons are more flexible than typical robotic sensors because they are dynamic rather than static. The membrane properties of neurons and hence their excitability can be modified by the presence of neuromodulatory substances. In the case of a sensory neuron, this can change, in a functionally significant way, the code used to describe a stimulus. For instance, extension of the neuron's dynamic range or modification of its filtering characteristics can result. This flexibility has an apparent cost. The code used may be situation-dependent and hence difficult to interpret. To address this issue and to understand how neuromodulation is used effectively in a motor control network, I am studying the GPR2 stretch receptor in the crustacean stomatogastric nervous system. Several different neuromodulatory substances can modify its encoding properties. Comparisons of physiological and anatomical evidence suggest that neuromodulation can be effected both by GPR2 itself and by other neurons in the network. These results suggest that the analog of neuromodulation might be useful for improving sensor performance in an artificial motor control system.